fix: resolve all lint errors after merge with main

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

src/openjarvis/a2a/__init__.py

@@ -1,10 +1,16 @@
 """Agent-to-Agent protocol — Google A2A spec implementation."""
+
 from openjarvis.a2a.client import A2AClient
 from openjarvis.a2a.protocol import A2ARequest, A2AResponse, A2ATask, AgentCard
 from openjarvis.a2a.server import A2AServer
 from openjarvis.a2a.tool import A2AAgentTool
 
 __all__ = [
-    "A2AAgentTool", "A2AClient", "A2ARequest", "A2AResponse",
-    "A2AServer", "A2ATask", "AgentCard",
+    "A2AAgentTool",
+    "A2AClient",
+    "A2ARequest",
+    "A2AResponse",
+    "A2AServer",
+    "A2ATask",
+    "AgentCard",
 ]

src/openjarvis/a2a/client.py

@@ -22,6 +22,7 @@ class A2AClient:
     def discover(self) -> AgentCard:
         """Fetch the agent card from /.well-known/agent.json."""
         import httpx
+
         resp = httpx.get(
             f"{self._base_url}/.well-known/agent.json",
             timeout=self._timeout,
@@ -41,6 +42,7 @@ class A2AClient:
     def send_task(self, input_text: str, **kwargs: Any) -> A2ATask:
         """Send a task to the remote agent and return the result."""
         import httpx
+
         request = A2ARequest(
             method="tasks/send",
             params={
@@ -69,6 +71,7 @@ class A2AClient:
     def get_task(self, task_id: str) -> A2ATask:
         """Get the status of a previously submitted task."""
         import httpx
+
         request = A2ARequest(
             method="tasks/get",
             params={"id": task_id},
@@ -90,6 +93,7 @@ class A2AClient:
     def cancel_task(self, task_id: str) -> A2ATask:
         """Cancel a running task."""
         import httpx
+
         request = A2ARequest(
             method="tasks/cancel",
             params={"id": task_id},

src/openjarvis/a2a/protocol.py

@@ -21,6 +21,7 @@ class TaskState(str, Enum):
 @dataclass(slots=True)
 class AgentCard:
     """Agent discovery card served at /.well-known/agent.json."""
+
     name: str
     description: str = ""
     url: str = ""
@@ -44,6 +45,7 @@ class AgentCard:
 @dataclass
 class A2ATask:
     """An A2A task with state machine."""
+
     task_id: str = field(default_factory=lambda: uuid.uuid4().hex[:16])
     state: TaskState = TaskState.SUBMITTED
     input_text: str = ""
@@ -65,6 +67,7 @@ class A2ATask:
 @dataclass(slots=True)
 class A2ARequest:
     """JSON-RPC 2.0 request for A2A."""
+
     method: str
     params: Dict[str, Any] = field(default_factory=dict)
     request_id: str = field(default_factory=lambda: uuid.uuid4().hex[:8])
@@ -84,6 +87,7 @@ class A2ARequest:
 @dataclass(slots=True)
 class A2AResponse:
     """JSON-RPC 2.0 response for A2A."""
+
     result: Any = None
     error: Optional[Dict[str, Any]] = None
     request_id: str = ""

src/openjarvis/a2a/server.py

@@ -102,7 +102,9 @@ class A2AServer:
         return A2AResponse(result=task.to_dict(), request_id=req_id).to_dict()
 
     def _handle_task_cancel(
-        self, params: Dict[str, Any], req_id: str,
+        self,
+        params: Dict[str, Any],
+        req_id: str,
     ) -> Dict[str, Any]:
         """Handle tasks/cancel — cancel a running task."""
         task_id = params.get("id", "")

src/openjarvis/agents/channel_agent.py

@@ -55,9 +55,7 @@ def classify_query(text: str) -> str:
 # ChannelAgent
 # ---------------------------------------------------------------------------
 
-_ESCALATION_TEMPLATE = (
-    "{preview}...\n\n---\nFull report ready — open in OpenJarvis:\nopenjarvis://research/{session_id}"
-)
+_ESCALATION_TEMPLATE = "{preview}...\n\n---\nFull report ready — open in OpenJarvis:\nopenjarvis://research/{session_id}"
 _LONG_RESPONSE_THRESHOLD = 500
 
 

src/openjarvis/agents/claude_code.py

@@ -35,9 +35,7 @@ _OUTPUT_END = "---OPENJARVIS_OUTPUT_END---"
 _RUNNER_SRC = Path(__file__).resolve().parent / "claude_code_runner"
 if not _RUNNER_SRC.exists():
     _RUNNER_SRC = (
-        Path(__file__).resolve().parents[2]
-        / "_node_modules"
-        / "claude_code_runner"
+        Path(__file__).resolve().parents[2] / "_node_modules" / "claude_code_runner"
     )
 
 

src/openjarvis/agents/deep_research.py

@@ -30,6 +30,7 @@ def _tc_args(tc: dict) -> str:
         return tc["function"]["arguments"]
     return tc["arguments"]
 
+
 DEEP_RESEARCH_SYSTEM_PROMPT = """\
 /no_think
 You are a deep research agent with access to a personal knowledge base \
@@ -201,9 +202,7 @@ class DeepResearchAgent(ToolUsingAgent):
                 # If content is empty but we have prior tool results,
                 # force one more generation without tools to synthesize
                 if not content.strip() and all_tool_results:
-                    messages.append(
-                        Message(role=Role.ASSISTANT, content=content)
-                    )
+                    messages.append(Message(role=Role.ASSISTANT, content=content))
                     messages.append(
                         Message(
                             role=Role.USER,

src/openjarvis/agents/executor.py

@@ -87,7 +87,7 @@ class AgentExecutor:
 
         agent_cls = AgentRegistry.get(agent_type)
         agent = agent_cls(
-            engine=getattr(self._manager, '_engine', None),
+            engine=getattr(self._manager, "_engine", None),
             system_prompt=system_prompt,
             bus=self._bus,
         )
@@ -113,10 +113,13 @@ class AgentExecutor:
             logger.error("Agent %s not found", agent_id)
             return
 
-        self._bus.publish(EventType.AGENT_TICK_START, {
-            "agent_id": agent_id,
-            "agent_name": agent["name"],
-        })
+        self._bus.publish(
+            EventType.AGENT_TICK_START,
+            {
+                "agent_id": agent_id,
+                "agent_name": agent["name"],
+            },
+        )
 
         # Activity tracking: subscribe to tool/inference events
         def _on_activity(event: Any) -> None:
@@ -131,14 +134,16 @@ class AgentExecutor:
 
         def _on_tool_start(event: Any) -> None:
             if event.data.get("agent") == agent_id:
-                trace_steps.append({
-                    "type": "tool_call",
-                    "input": {
-                        "tool": event.data.get("tool"),
-                        "args": event.data.get("args"),
-                    },
-                    "start_time": event.timestamp,
-                })
+                trace_steps.append(
+                    {
+                        "type": "tool_call",
+                        "input": {
+                            "tool": event.data.get("tool"),
+                            "args": event.data.get("args"),
+                        },
+                        "start_time": event.timestamp,
+                    }
+                )
 
         def _on_tool_end(event: Any) -> None:
             if event.data.get("agent") == agent_id and trace_steps:
@@ -175,8 +180,13 @@ class AgentExecutor:
 
             if self._trace_store:
                 self._save_trace(
-                    agent_id, agent, result, error_info,
-                    tick_start, tick_duration, trace_steps,
+                    agent_id,
+                    agent,
+                    result,
+                    error_info,
+                    tick_start,
+                    tick_duration,
+                    trace_steps,
                 )
 
     def _run_with_retries(self, agent: dict) -> AgentResult:
@@ -193,7 +203,11 @@ class AgentExecutor:
                 delay = retry_delay(attempt)
                 logger.info(
                     "Agent %s tick retry %d/%d in %ds: %s",
-                    agent["id"], attempt + 1, _MAX_RETRIES, delay, e,
+                    agent["id"],
+                    attempt + 1,
+                    _MAX_RETRIES,
+                    delay,
+                    e,
                 )
                 time.sleep(delay)
             except Exception as e:
@@ -203,7 +217,11 @@ class AgentExecutor:
                 delay = retry_delay(attempt)
                 logger.info(
                     "Agent %s tick retry %d/%d in %ds: %s",
-                    agent["id"], attempt + 1, _MAX_RETRIES, delay, e,
+                    agent["id"],
+                    attempt + 1,
+                    _MAX_RETRIES,
+                    delay,
+                    e,
                 )
                 time.sleep(delay)
 
@@ -225,17 +243,16 @@ class AgentExecutor:
         engine = self._system.engine if self._system else None
         if engine is None:
             raise FatalError("No engine available in JarvisSystem")
-        model = config.get("model") or (
-            self._system.model
-            if self._system else ""
-        )
+        model = config.get("model") or (self._system.model if self._system else "")
         if not model:
             raise FatalError("No model configured for agent")
 
         logger.info(
             "Agent %s [%s]: using model=%s, engine=%s",
-            agent["name"], agent["id"],
-            model, type(engine).__name__,
+            agent["name"],
+            agent["id"],
+            model,
+            type(engine).__name__,
         )
         self._set_activity(agent["id"], f"Loading model {model}...")
 
@@ -289,7 +306,9 @@ class AgentExecutor:
             if tool_instances:
                 logger.info(
                     "Agent %s: resolved %d/%d tools",
-                    agent["name"], len(tool_instances), len(tool_names),
+                    agent["name"],
+                    len(tool_instances),
+                    len(tool_names),
                 )
 
         # Construct agent instance
@@ -317,7 +336,8 @@ class AgentExecutor:
                 self._manager.mark_message_delivered(m["id"])
             logger.info(
                 "Agent %s: delivering %d pending message(s)",
-                agent["name"], len(pending),
+                agent["name"],
+                len(pending),
             )
             self._set_activity(
                 agent["id"],
@@ -325,8 +345,7 @@ class AgentExecutor:
             )
         else:
             logger.info(
-                "Agent %s: no pending messages, running with "
-                "instruction only",
+                "Agent %s: no pending messages, running with instruction only",
                 agent["name"],
             )
 
@@ -363,7 +382,8 @@ class AgentExecutor:
 
                 if query:
                     results = self._system.memory_backend.retrieve(
-                        query, top_k=ctx_cfg.top_k,
+                        query,
+                        top_k=ctx_cfg.top_k,
                     )
                     memory_results = [
                         r for r in results if r.score >= ctx_cfg.min_score
@@ -383,7 +403,8 @@ class AgentExecutor:
         self._set_activity(agent["id"], "Generating response...")
         logger.info(
             "Agent %s: calling agent.run() with %d chars input",
-            agent["name"], len(input_text),
+            agent["name"],
+            len(input_text),
         )
         _t0 = time.time()
         result = agent_instance.run(input_text, context=agent_ctx)
@@ -392,7 +413,8 @@ class AgentExecutor:
         # Qwen3.5 thinking mode consuming all tokens).
         if not (result.content or "").strip():
             self._set_activity(
-                agent["id"], "Retrying (empty response)...",
+                agent["id"],
+                "Retrying (empty response)...",
             )
             logger.warning(
                 "Agent %s: empty content, retrying once",
@@ -404,7 +426,8 @@ class AgentExecutor:
         logger.info(
             "Agent %s: agent.run() completed in %.1fs, "
             "content_len=%d, turns=%d, tokens=%s",
-            agent["name"], _elapsed,
+            agent["name"],
+            _elapsed,
             len(result.content or ""),
             result.turns,
             result.metadata.get("total_tokens", "?"),
@@ -434,7 +457,9 @@ class AgentExecutor:
             "suggested_action": suggest_action(error),
             "stack_trace_summary": "".join(
                 traceback.format_exception(type(error), error, error.__traceback__)[-3:]
-            )[:1000] if error.__traceback__ else "",
+            )[:1000]
+            if error.__traceback__
+            else "",
         }
 
     def _finalize_tick(
@@ -449,9 +474,9 @@ class AgentExecutor:
         if error is None:
             # Success
             logger.info(
-                "Tick succeeded for agent %s in %.1fs, "
-                "response_len=%d",
-                agent_id, duration,
+                "Tick succeeded for agent %s in %.1fs, response_len=%d",
+                agent_id,
+                duration,
                 len(result.content or "") if result else 0,
             )
             self._manager.end_tick(agent_id)
@@ -466,7 +491,8 @@ class AgentExecutor:
                 )
                 in_tokens = result.metadata.get("prompt_tokens", 0)
                 out_tokens = result.metadata.get(
-                    "completion_tokens", 0,
+                    "completion_tokens",
+                    0,
                 )
                 cost = result.metadata.get("cost", 0.0)
                 budget_kwargs: dict[str, Any] = {"stall_retries": 0}
@@ -481,7 +507,8 @@ class AgentExecutor:
                 self._manager.update_agent(agent_id, **budget_kwargs)
 
                 self._manager.update_summary_memory(
-                    agent_id, result.content[:2000],
+                    agent_id,
+                    result.content[:2000],
                 )
                 self._manager.store_agent_response(agent_id, result.content[:2000])
 
@@ -498,49 +525,68 @@ class AgentExecutor:
                     exceeded = True
                 if exceeded:
                     self._manager.update_agent(agent_id, status="budget_exceeded")
-                    self._bus.publish(EventType.AGENT_BUDGET_EXCEEDED, {
-                        "agent_id": agent_id,
-                        "total_cost": agent_data["total_cost"],
-                        "total_tokens": agent_data["total_tokens"],
-                        "max_cost": max_cost,
-                        "max_tokens": max_tokens,
-                    })
-            self._bus.publish(EventType.AGENT_TICK_END, {
-                "agent_id": agent_id,
-                "duration": duration,
-                "status": "ok",
-            })
+                    self._bus.publish(
+                        EventType.AGENT_BUDGET_EXCEEDED,
+                        {
+                            "agent_id": agent_id,
+                            "total_cost": agent_data["total_cost"],
+                            "total_tokens": agent_data["total_tokens"],
+                            "max_cost": max_cost,
+                            "max_tokens": max_tokens,
+                        },
+                    )
+            self._bus.publish(
+                EventType.AGENT_TICK_END,
+                {
+                    "agent_id": agent_id,
+                    "duration": duration,
+                    "status": "ok",
+                },
+            )
         elif isinstance(error, EscalateError):
             logger.warning(
                 "Tick escalated for agent %s after %.1fs: %s",
-                agent_id, duration, error,
+                agent_id,
+                duration,
+                error,
             )
             self._manager.end_tick(agent_id)
             self._manager.update_agent(agent_id, status="needs_attention")
-            self._bus.publish(EventType.AGENT_TICK_ERROR, {
-                "agent_id": agent_id,
-                "error": str(error),
-                "error_type": "escalate",
-                "duration": duration,
-            })
+            self._bus.publish(
+                EventType.AGENT_TICK_ERROR,
+                {
+                    "agent_id": agent_id,
+                    "error": str(error),
+                    "error_type": "escalate",
+                    "duration": duration,
+                },
+            )
         else:
             logger.error(
                 "Tick failed for agent %s after %.1fs: %s",
-                agent_id, duration, error, exc_info=error,
+                agent_id,
+                duration,
+                error,
+                exc_info=error,
             )
             self._manager.end_tick(agent_id)
             self._manager.update_agent(agent_id, status="error")
             # Write error detail to summary_memory so frontend can display it
             error_msg = str(error)[:2000]
             self._manager.update_summary_memory(agent_id, f"ERROR: {error_msg}")
-            self._bus.publish(EventType.AGENT_TICK_ERROR, {
-                "agent_id": agent_id,
-                "error": str(error),
-                "error_type": (
-                    "fatal" if isinstance(error, FatalError) else "retryable_exhausted"
-                ),
-                "duration": duration,
-            })
+            self._bus.publish(
+                EventType.AGENT_TICK_ERROR,
+                {
+                    "agent_id": agent_id,
+                    "error": str(error),
+                    "error_type": (
+                        "fatal"
+                        if isinstance(error, FatalError)
+                        else "retryable_exhausted"
+                    ),
+                    "duration": duration,
+                },
+            )
 
     def _save_trace(
         self,
@@ -557,17 +603,19 @@ class AgentExecutor:
 
         steps = []
         for s in trace_steps:
-            steps.append(TraceStep(
-                step_type=(
-                    StepType.TOOL_CALL
-                    if s["type"] == "tool_call"
-                    else StepType.GENERATE
-                ),
-                input=s.get("input", {}),
-                output=s.get("output", {}),
-                duration_seconds=s.get("duration", 0),
-                timestamp=s.get("start_time", tick_start),
-            ))
+            steps.append(
+                TraceStep(
+                    step_type=(
+                        StepType.TOOL_CALL
+                        if s["type"] == "tool_call"
+                        else StepType.GENERATE
+                    ),
+                    input=s.get("input", {}),
+                    output=s.get("output", {}),
+                    duration_seconds=s.get("duration", 0),
+                    timestamp=s.get("start_time", tick_start),
+                )
+            )
 
         metadata: dict[str, Any] = {}
         if error is not None:
@@ -590,5 +638,7 @@ class AgentExecutor:
             self._trace_store.save(trace)
         except Exception:
             logger.warning(
-                "Failed to save trace for agent %s", agent_id, exc_info=True,
+                "Failed to save trace for agent %s",
+                agent_id,
+                exc_info=True,
             )

src/openjarvis/agents/loop_guard.py

@@ -13,17 +13,19 @@ from openjarvis.core.events import EventBus, EventType
 @dataclass(slots=True)
 class LoopGuardConfig:
     """Configuration for the loop guard."""
+
     enabled: bool = True
-    max_identical_calls: int = 3       # SHA-256 of (tool_name, arguments)
-    ping_pong_window: int = 6          # detect A-B-A-B cycling
-    poll_tool_budget: int = 5          # max calls to same polling tool
-    max_context_messages: int = 100    # context overflow threshold
-    warn_before_block: bool = True     # warn on first cycle, block on second
+    max_identical_calls: int = 3  # SHA-256 of (tool_name, arguments)
+    ping_pong_window: int = 6  # detect A-B-A-B cycling
+    poll_tool_budget: int = 5  # max calls to same polling tool
+    max_context_messages: int = 100  # context overflow threshold
+    warn_before_block: bool = True  # warn on first cycle, block on second
 
 
 @dataclass(slots=True)
 class LoopVerdict:
     """Result of a loop guard check."""
+
     blocked: bool = False
     reason: str = ""
     warned: bool = False
@@ -54,13 +56,12 @@ class LoopGuard:
 
         try:
             from openjarvis._rust_bridge import get_rust_module
+
             _rust = get_rust_module()
             self._rust_impl = _rust.LoopGuard(
                 max_identical=config.max_identical_calls,
                 max_ping_pong=(
-                    config.ping_pong_window // 2
-                    if config.ping_pong_window > 1
-                    else 2
+                    config.ping_pong_window // 2 if config.ping_pong_window > 1 else 2
                 ),
                 poll_budget=config.poll_tool_budget,
             )
@@ -93,9 +94,7 @@ class LoopGuard:
     def _python_check(self, tool_name: str, arguments: str) -> LoopVerdict:
         """Pure-Python fallback when Rust backend is not available."""
         # 1. Hash tracking — identical calls
-        call_hash = hashlib.sha256(
-            f"{tool_name}:{arguments}".encode()
-        ).hexdigest()[:16]
+        call_hash = hashlib.sha256(f"{tool_name}:{arguments}".encode()).hexdigest()[:16]
         self._call_counts[call_hash] = self._call_counts.get(call_hash, 0) + 1
         if self._call_counts[call_hash] > self._config.max_identical_calls:
             self._emit_triggered("identical_call", tool_name)
@@ -139,12 +138,12 @@ class LoopGuard:
     @staticmethod
     def _is_system(msg: object) -> bool:
         """Check if a message has role == system."""
-        return getattr(msg, 'role', None) == 'system'
+        return getattr(msg, "role", None) == "system"
 
     @staticmethod
     def _is_tool(msg: object) -> bool:
         """Check if a message has role == tool."""
-        return getattr(msg, 'role', None) == 'tool'
+        return getattr(msg, "role", None) == "tool"
 
     def compress_context(self, messages: list) -> list:
         """Apply 4-stage context overflow recovery to message list.
@@ -164,14 +163,19 @@ class LoopGuard:
         for i, msg in enumerate(messages):
             if i < threshold and self._is_tool(msg):
                 from openjarvis.core.types import Message, Role
-                compressed.append(Message(
-                    role=Role.TOOL,
-                    content="[Tool result truncated]",
-                    tool_call_id=getattr(
-                        msg, 'tool_call_id', None,
-                    ),
-                    name=getattr(msg, 'name', None),
-                ))
+
+                compressed.append(
+                    Message(
+                        role=Role.TOOL,
+                        content="[Tool result truncated]",
+                        tool_call_id=getattr(
+                            msg,
+                            "tool_call_id",
+                            None,
+                        ),
+                        name=getattr(msg, "name", None),
+                    )
+                )
             else:
                 compressed.append(msg)
 
@@ -179,16 +183,9 @@ class LoopGuard:
             return compressed
 
         # Stage 2: Sliding window — keep system + recent
-        system_msgs = [
-            m for m in compressed if self._is_system(m)
-        ]
-        non_system = [
-            m for m in compressed
-            if not self._is_system(m)
-        ]
-        window_size = (
-            self._config.max_context_messages - len(system_msgs)
-        )
+        system_msgs = [m for m in compressed if self._is_system(m)]
+        non_system = [m for m in compressed if not self._is_system(m)]
+        window_size = self._config.max_context_messages - len(system_msgs)
         if len(non_system) > window_size:
             non_system = non_system[-window_size:]
         compressed = system_msgs + non_system
@@ -198,24 +195,18 @@ class LoopGuard:
 
         # Stage 3: Drop tool call/result pairs from middle
         keep_start = max(
-            len(system_msgs), len(compressed) // 10,
+            len(system_msgs),
+            len(compressed) // 10,
         )
         keep_end = len(compressed) // 2
-        compressed = (
-            compressed[:keep_start] + compressed[-keep_end:]
-        )
+        compressed = compressed[:keep_start] + compressed[-keep_end:]
 
         if len(compressed) <= self._config.max_context_messages:
             return compressed
 
         # Stage 4: Extreme — system + last 2 exchanges
-        sys_final = [
-            m for m in compressed if self._is_system(m)
-        ]
-        tail = [
-            m for m in compressed
-            if not self._is_system(m)
-        ]
+        sys_final = [m for m in compressed if self._is_system(m)]
+        tail = [m for m in compressed if not self._is_system(m)]
         return sys_final + tail[-4:]
 
     def reset(self) -> None:
@@ -234,7 +225,7 @@ class LoopGuard:
         # Check for period-2 pattern (A-B-A-B)
         for period in (2, 3):
             if n >= period * 2:
-                tail = seq[-period * 2:]
+                tail = seq[-period * 2 :]
                 pattern = tail[:period]
                 if all(tail[i] == pattern[i % period] for i in range(len(tail))):
                     return True

src/openjarvis/agents/native_openhands.py

@@ -284,9 +284,7 @@ class NativeOpenHandsAgent(ToolUsingAgent):
         total_usage = {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}
 
         # Build OpenAI-format tool schemas for native function calling
-        openai_tools = (
-            self._executor.get_openai_tools() if self._tools else []
-        )
+        openai_tools = self._executor.get_openai_tools() if self._tools else []
         # Side dict for Gemini thought_signatures (ToolCall uses slots)
         _thought_sigs: dict[str, bytes] = {}
 

src/openjarvis/agents/scheduler.py

@@ -162,7 +162,11 @@ class AgentScheduler:
         for agent_id, info in due:
             agent = self._manager.get_agent(agent_id)
             if agent is None or agent["status"] in (
-                "paused", "archived", "running", "budget_exceeded", "stalled",
+                "paused",
+                "archived",
+                "running",
+                "budget_exceeded",
+                "stalled",
             ):
                 continue
 
@@ -177,11 +181,12 @@ class AgentScheduler:
                 if agent_id in self._agents:
                     if info["schedule_type"] == "cron":
                         self._agents[agent_id]["next_fire"] = _next_cron_fire(
-                            str(info["schedule_value"]), now,
+                            str(info["schedule_value"]),
+                            now,
                         )
                     elif info["schedule_type"] == "interval":
-                        self._agents[agent_id]["next_fire"] = (
-                            now + float(info["schedule_value"])
+                        self._agents[agent_id]["next_fire"] = now + float(
+                            info["schedule_value"]
                         )
                     # Manual: stays at inf
 
@@ -214,22 +219,30 @@ class AgentScheduler:
                 self._manager.update_agent(agent["id"], status="error")
                 logger.warning(
                     "Agent %s stall retries exhausted (%d/%d), setting error",
-                    agent["id"], current_retries, max_retries,
+                    agent["id"],
+                    current_retries,
+                    max_retries,
                 )
             else:
                 self._manager.end_tick(agent["id"])  # Release concurrency guard
                 self._manager.update_agent(
-                    agent["id"], stall_retries=current_retries + 1,
+                    agent["id"],
+                    stall_retries=current_retries + 1,
                 )
                 if self._bus:
-                    self._bus.publish(EventType.AGENT_STALL_DETECTED, {
-                        "agent_id": agent["id"],
-                        "last_activity_at": last_activity,
-                        "stall_retries": current_retries + 1,
-                    })
+                    self._bus.publish(
+                        EventType.AGENT_STALL_DETECTED,
+                        {
+                            "agent_id": agent["id"],
+                            "last_activity_at": last_activity,
+                            "stall_retries": current_retries + 1,
+                        },
+                    )
                 logger.warning(
                     "Agent %s stalled (retry %d/%d)",
-                    agent["id"], current_retries + 1, max_retries,
+                    agent["id"],
+                    current_retries + 1,
+                    max_retries,
                 )
 
     # -- Learning tick counting ------------------------------------------------
@@ -258,9 +271,12 @@ class AgentScheduler:
         if self._tick_counts[agent_id] >= threshold:
             self._tick_counts[agent_id] = 0
             if self._bus:
-                self._bus.publish(EventType.AGENT_LEARNING_STARTED, {
-                    "agent_id": agent_id,
-                })
+                self._bus.publish(
+                    EventType.AGENT_LEARNING_STARTED,
+                    {
+                        "agent_id": agent_id,
+                    },
+                )
             logger.info(
                 "Learning triggered for agent %s after %d ticks",
                 agent_id,

src/openjarvis/bench/energy.py

@@ -64,9 +64,7 @@ class EnergyBenchmark(BaseBenchmark):
             from openjarvis.telemetry.steady_state import SteadyStateDetector
 
             detector = SteadyStateDetector()
-            energy_method = getattr(
-                energy_monitor, "energy_method", lambda: ""
-            )()
+            energy_method = getattr(energy_monitor, "energy_method", lambda: "")()
 
             for _ in range(num_samples):
                 t0 = time.time()
@@ -78,9 +76,7 @@ class EnergyBenchmark(BaseBenchmark):
                     usage = result.get("usage", {})
                     tokens = usage.get("completion_tokens", 0)
                     energy_j = sample.energy_joules
-                    power_w = (
-                        energy_j / elapsed if elapsed > 0 else 0.0
-                    )
+                    power_w = energy_j / elapsed if elapsed > 0 else 0.0
                     tps = tokens / elapsed if elapsed > 0 else 0.0
                     ept = energy_j / tokens if tokens > 0 else 0.0
 
@@ -145,9 +141,7 @@ class EnergyBenchmark(BaseBenchmark):
             samples=num_samples,
             errors=errors,
             warmup_samples=warmup_samples,
-            steady_state_samples=(
-                ss_result.steady_state_samples if ss_result else 0
-            ),
+            steady_state_samples=(ss_result.steady_state_samples if ss_result else 0),
             steady_state_reached=(
                 ss_result.steady_state_reached if ss_result else False
             ),

src/openjarvis/channels/bluebubbles.py

@@ -96,7 +96,8 @@ class BlueBubblesChannel(BaseChannel):
                 self._publish_sent(channel, content, conversation_id)
                 return True
             logger.warning(
-                "BlueBubbles API returned status %d", resp.status_code,
+                "BlueBubbles API returned status %d",
+                resp.status_code,
             )
             return False
         except Exception:

src/openjarvis/channels/discord_channel.py

@@ -62,7 +62,8 @@ class DiscordChannel(BaseChannel):
             import discord  # noqa: F401
 
             self._listener_thread = threading.Thread(
-                target=self._gateway_loop, daemon=True,
+                target=self._gateway_loop,
+                daemon=True,
             )
             self._listener_thread.start()
             self._status = ChannelStatus.CONNECTED
@@ -107,7 +108,10 @@ class DiscordChannel(BaseChannel):
                 payload["message_reference"] = {"message_id": conversation_id}
 
             resp = httpx.post(
-                url, json=payload, headers=headers, timeout=10.0,
+                url,
+                json=payload,
+                headers=headers,
+                timeout=10.0,
             )
             if resp.status_code < 300:
                 self._publish_sent(channel, content, conversation_id)

src/openjarvis/channels/email_channel.py

@@ -86,7 +86,8 @@ class EmailChannel(BaseChannel):
 
         if self._imap_host:
             self._listener_thread = threading.Thread(
-                target=self._imap_poll_loop, daemon=True,
+                target=self._imap_poll_loop,
+                daemon=True,
             )
             self._listener_thread.start()
 
@@ -121,7 +122,8 @@ class EmailChannel(BaseChannel):
             msg["From"] = self._username
             msg["To"] = channel
             msg["Subject"] = (metadata or {}).get(
-                "subject", "Message from OpenJarvis",
+                "subject",
+                "Message from OpenJarvis",
             )
             if conversation_id:
                 msg["In-Reply-To"] = conversation_id
@@ -166,7 +168,8 @@ class EmailChannel(BaseChannel):
             try:
                 if self._use_tls:
                     imap = imaplib.IMAP4_SSL(
-                        self._imap_host, self._imap_port,
+                        self._imap_host,
+                        self._imap_port,
                     )
                 else:
                     imap = imaplib.IMAP4(self._imap_host, self._imap_port)

src/openjarvis/channels/feishu.py

@@ -81,8 +81,7 @@ class FeishuChannel(BaseChannel):
 
             # Obtain tenant_access_token
             token_url = (
-                "https://open.feishu.cn/open-apis/auth/v3/"
-                "tenant_access_token/internal"
+                "https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal"
             )
             token_resp = httpx.post(
                 token_url,
@@ -119,13 +118,17 @@ class FeishuChannel(BaseChannel):
             }
 
             resp = httpx.post(
-                msg_url, json=payload, headers=headers, timeout=10.0,
+                msg_url,
+                json=payload,
+                headers=headers,
+                timeout=10.0,
             )
             if resp.status_code < 300:
                 self._publish_sent(channel, content, conversation_id)
                 return True
             logger.warning(
-                "Feishu API returned status %d", resp.status_code,
+                "Feishu API returned status %d",
+                resp.status_code,
             )
             return False
         except Exception:

src/openjarvis/channels/gmail.py

@@ -53,10 +53,12 @@ class GmailChannel(BaseChannel):
         bus: Optional[EventBus] = None,
     ) -> None:
         self._credentials_path = credentials_path or os.environ.get(
-            "GMAIL_CREDENTIALS_PATH", "",
+            "GMAIL_CREDENTIALS_PATH",
+            "",
         )
         self._token_path = token_path or os.environ.get(
-            "GMAIL_TOKEN_PATH", "",
+            "GMAIL_TOKEN_PATH",
+            "",
         )
         self._user_id = user_id
         self._poll_interval = poll_interval
@@ -89,7 +91,8 @@ class GmailChannel(BaseChannel):
             creds: Any = None
             if self._token_path and os.path.exists(self._token_path):
                 creds = Credentials.from_authorized_user_file(
-                    self._token_path, SCOPES,
+                    self._token_path,
+                    SCOPES,
                 )
 
             if not creds or not creds.valid:
@@ -101,7 +104,8 @@ class GmailChannel(BaseChannel):
                     self._credentials_path,
                 ):
                     flow = InstalledAppFlow.from_client_secrets_file(
-                        self._credentials_path, SCOPES,
+                        self._credentials_path,
+                        SCOPES,
                     )
                     creds = flow.run_local_server(port=0)
                 else:
@@ -120,7 +124,8 @@ class GmailChannel(BaseChannel):
 
             # Start polling thread
             self._listener_thread = threading.Thread(
-                target=self._poll_loop, daemon=True,
+                target=self._poll_loop,
+                daemon=True,
             )
             self._listener_thread.start()
         except ImportError:
@@ -165,7 +170,8 @@ class GmailChannel(BaseChannel):
             msg["To"] = channel
             msg["From"] = self._user_id
             msg["Subject"] = (metadata or {}).get(
-                "subject", "Message from OpenJarvis",
+                "subject",
+                "Message from OpenJarvis",
             )
 
             raw = base64.urlsafe_b64encode(msg.as_bytes()).decode("utf-8")
@@ -174,7 +180,8 @@ class GmailChannel(BaseChannel):
                 body["threadId"] = conversation_id
 
             self._service.users().messages().send(
-                userId=self._user_id, body=body,
+                userId=self._user_id,
+                body=body,
             ).execute()
 
             self._publish_sent(channel, content, conversation_id)

src/openjarvis/channels/google_chat.py

@@ -39,7 +39,8 @@ class GoogleChatChannel(BaseChannel):
         bus: Optional[EventBus] = None,
     ) -> None:
         self._webhook_url = webhook_url or os.environ.get(
-            "GOOGLE_CHAT_WEBHOOK_URL", "",
+            "GOOGLE_CHAT_WEBHOOK_URL",
+            "",
         )
         self._bus = bus
         self._handlers: List[ChannelHandler] = []
@@ -80,13 +81,16 @@ class GoogleChatChannel(BaseChannel):
             payload: Dict[str, Any] = {"text": content}
 
             resp = httpx.post(
-                self._webhook_url, json=payload, timeout=10.0,
+                self._webhook_url,
+                json=payload,
+                timeout=10.0,
             )
             if resp.status_code < 300:
                 self._publish_sent(channel, content, conversation_id)
                 return True
             logger.warning(
-                "Google Chat API returned status %d", resp.status_code,
+                "Google Chat API returned status %d",
+                resp.status_code,
             )
             return False
         except Exception:

src/openjarvis/channels/imessage_daemon.py

@@ -20,13 +20,9 @@ from typing import Any, Dict, List
 
 logger = logging.getLogger(__name__)
 
-_DEFAULT_DB_PATH = str(
-    Path.home() / "Library" / "Messages" / "chat.db"
-)
+_DEFAULT_DB_PATH = str(Path.home() / "Library" / "Messages" / "chat.db")
 _POLL_INTERVAL = 5
-_PID_FILE = str(
-    Path.home() / ".openjarvis" / "imessage-agent.pid"
-)
+_PID_FILE = str(Path.home() / ".openjarvis" / "imessage-agent.pid")
 
 
 def poll_new_messages(
@@ -37,9 +33,7 @@ def poll_new_messages(
 ) -> List[Dict[str, Any]]:
     """Return new incoming messages since last_rowid."""
     try:
-        conn = sqlite3.connect(
-            f"file:{db_path}?mode=ro", uri=True
-        )
+        conn = sqlite3.connect(f"file:{db_path}?mode=ro", uri=True)
         conn.row_factory = sqlite3.Row
     except sqlite3.OperationalError:
         return []
@@ -68,7 +62,7 @@ def send_imessage(chat_identifier: str, message: str) -> bool:
     escaped = message.replace("\\", "\\\\").replace('"', '\\"')
     script = (
         f'tell application "Messages"\n'
-        f'  set targetChat to a reference to '
+        f"  set targetChat to a reference to "
         f'chat id "{chat_identifier}"\n'
         f'  send "{escaped}" to targetChat\n'
         f"end tell"
@@ -152,12 +146,8 @@ def run_daemon(
 def _get_max_rowid(db_path: str) -> int:
     """Get the current max ROWID from chat.db."""
     try:
-        conn = sqlite3.connect(
-            f"file:{db_path}?mode=ro", uri=True
-        )
-        row = conn.execute(
-            "SELECT MAX(ROWID) FROM message"
-        ).fetchone()
+        conn = sqlite3.connect(f"file:{db_path}?mode=ro", uri=True)
+        row = conn.execute("SELECT MAX(ROWID) FROM message").fetchone()
         conn.close()
         return row[0] or 0
     except sqlite3.OperationalError:

src/openjarvis/channels/line_channel.py

@@ -65,8 +65,7 @@ class LineChannel(BaseChannel):
             import linebot  # noqa: F401
         except ImportError:
             raise ImportError(
-                "line-bot-sdk not installed. Install with: "
-                "uv sync --extra channel-line"
+                "line-bot-sdk not installed. Install with: uv sync --extra channel-line"
             )
         self._status = ChannelStatus.CONNECTED
 

src/openjarvis/channels/mastodon_channel.py

@@ -43,12 +43,8 @@ class MastodonChannel(BaseChannel):
         access_token: str = "",
         bus: Optional[EventBus] = None,
     ) -> None:
-        self._api_base_url = api_base_url or os.environ.get(
-            "MASTODON_API_BASE_URL", ""
-        )
-        self._access_token = access_token or os.environ.get(
-            "MASTODON_ACCESS_TOKEN", ""
-        )
+        self._api_base_url = api_base_url or os.environ.get("MASTODON_API_BASE_URL", "")
+        self._access_token = access_token or os.environ.get("MASTODON_ACCESS_TOKEN", "")
         self._bus = bus
         self._handlers: List[ChannelHandler] = []
         self._status = ChannelStatus.DISCONNECTED

src/openjarvis/channels/matrix_channel.py

@@ -94,13 +94,17 @@ class MatrixChannel(BaseChannel):
             }
 
             resp = httpx.put(
-                url, json=payload, headers=headers, timeout=10.0,
+                url,
+                json=payload,
+                headers=headers,
+                timeout=10.0,
             )
             if resp.status_code < 300:
                 self._publish_sent(channel, content, conversation_id)
                 return True
             logger.warning(
-                "Matrix API returned status %d", resp.status_code,
+                "Matrix API returned status %d",
+                resp.status_code,
             )
             return False
         except Exception:

src/openjarvis/channels/mattermost.py

@@ -91,13 +91,17 @@ class MattermostChannel(BaseChannel):
                 payload["root_id"] = conversation_id
 
             resp = httpx.post(
-                url, json=payload, headers=headers, timeout=10.0,
+                url,
+                json=payload,
+                headers=headers,
+                timeout=10.0,
             )
             if resp.status_code < 300:
                 self._publish_sent(channel, content, conversation_id)
                 return True
             logger.warning(
-                "Mattermost API returned status %d", resp.status_code,
+                "Mattermost API returned status %d",
+                resp.status_code,
             )
             return False
         except Exception:

src/openjarvis/channels/nostr_channel.py

@@ -45,9 +45,7 @@ class NostrChannel(BaseChannel):
         bus: Optional[EventBus] = None,
     ) -> None:
         self._private_key = private_key or os.environ.get("NOSTR_PRIVATE_KEY", "")
-        relays_str = relays or os.environ.get(
-            "NOSTR_RELAYS", "wss://relay.damus.io"
-        )
+        relays_str = relays or os.environ.get("NOSTR_RELAYS", "wss://relay.damus.io")
         self._relays = [r.strip() for r in relays_str.split(",") if r.strip()]
         self._bus = bus
         self._handlers: List[ChannelHandler] = []
@@ -65,8 +63,7 @@ class NostrChannel(BaseChannel):
             import pynostr  # noqa: F401
         except ImportError:
             raise ImportError(
-                "pynostr not installed. Install with: "
-                "uv sync --extra channel-nostr"
+                "pynostr not installed. Install with: uv sync --extra channel-nostr"
             )
         self._status = ChannelStatus.CONNECTED
 

src/openjarvis/channels/reddit_channel.py

@@ -78,8 +78,7 @@ class RedditChannel(BaseChannel):
             import praw  # noqa: F401
         except ImportError:
             raise ImportError(
-                "praw not installed. Install with: "
-                "uv sync --extra channel-reddit"
+                "praw not installed. Install with: uv sync --extra channel-reddit"
             )
         self._status = ChannelStatus.CONNECTED
 

src/openjarvis/channels/signal_channel.py

@@ -44,7 +44,8 @@ class SignalChannel(BaseChannel):
     ) -> None:
         self._api_url = api_url or os.environ.get("SIGNAL_API_URL", "")
         self._phone_number = phone_number or os.environ.get(
-            "SIGNAL_PHONE_NUMBER", "",
+            "SIGNAL_PHONE_NUMBER",
+            "",
         )
         self._bus = bus
         self._handlers: List[ChannelHandler] = []
@@ -94,7 +95,8 @@ class SignalChannel(BaseChannel):
                 self._publish_sent(channel, content, conversation_id)
                 return True
             logger.warning(
-                "Signal API returned status %d", resp.status_code,
+                "Signal API returned status %d",
+                resp.status_code,
             )
             return False
         except Exception:

src/openjarvis/channels/slack.py

@@ -72,7 +72,8 @@ class SlackChannel(BaseChannel):
                 return
 
             self._listener_thread = threading.Thread(
-                target=self._socket_mode_loop, daemon=True,
+                target=self._socket_mode_loop,
+                daemon=True,
             )
             self._listener_thread.start()
             self._status = ChannelStatus.CONNECTED
@@ -120,7 +121,10 @@ class SlackChannel(BaseChannel):
                 payload["thread_ts"] = conversation_id
 
             resp = httpx.post(
-                url, json=payload, headers=headers, timeout=10.0,
+                url,
+                json=payload,
+                headers=headers,
+                timeout=10.0,
             )
             if resp.status_code < 300:
                 data = resp.json()
@@ -130,7 +134,8 @@ class SlackChannel(BaseChannel):
                 logger.warning("Slack API error: %s", data.get("error"))
                 return False
             logger.warning(
-                "Slack API returned status %d", resp.status_code,
+                "Slack API returned status %d",
+                resp.status_code,
             )
             return False
         except Exception:

src/openjarvis/channels/teams.py

@@ -46,9 +46,8 @@ class TeamsChannel(BaseChannel):
     ) -> None:
         self._app_id = app_id or os.environ.get("TEAMS_APP_ID", "")
         self._app_password = app_password or os.environ.get("TEAMS_APP_PASSWORD", "")
-        self._service_url = (
-            service_url
-            or os.environ.get("TEAMS_SERVICE_URL", "https://smba.trafficmanager.net/teams")
+        self._service_url = service_url or os.environ.get(
+            "TEAMS_SERVICE_URL", "https://smba.trafficmanager.net/teams"
         )
         self._bus = bus
         self._handlers: List[ChannelHandler] = []
@@ -99,13 +98,17 @@ class TeamsChannel(BaseChannel):
                 payload["replyToId"] = conversation_id
 
             resp = httpx.post(
-                url, json=payload, headers=headers, timeout=10.0,
+                url,
+                json=payload,
+                headers=headers,
+                timeout=10.0,
             )
             if resp.status_code < 300:
                 self._publish_sent(channel, content, conversation_id)
                 return True
             logger.warning(
-                "Teams API returned status %d", resp.status_code,
+                "Teams API returned status %d",
+                resp.status_code,
             )
             return False
         except Exception:

src/openjarvis/channels/telegram.py

@@ -70,7 +70,8 @@ class TelegramChannel(BaseChannel):
             from telegram.ext import ApplicationBuilder  # noqa: F401
 
             self._listener_thread = threading.Thread(
-                target=self._poll_loop, daemon=True,
+                target=self._poll_loop,
+                daemon=True,
             )
             self._listener_thread.start()
             self._status = ChannelStatus.CONNECTED

src/openjarvis/channels/twilio_sms.py

@@ -45,15 +45,9 @@ class TwilioSMSChannel(BaseChannel):
         phone_number: str = "",
         bus: Optional[EventBus] = None,
     ) -> None:
-        self._account_sid = account_sid or os.environ.get(
-            "TWILIO_ACCOUNT_SID", ""
-        )
-        self._auth_token = auth_token or os.environ.get(
-            "TWILIO_AUTH_TOKEN", ""
-        )
-        self._phone_number = phone_number or os.environ.get(
-            "TWILIO_PHONE_NUMBER", ""
-        )
+        self._account_sid = account_sid or os.environ.get("TWILIO_ACCOUNT_SID", "")
+        self._auth_token = auth_token or os.environ.get("TWILIO_AUTH_TOKEN", "")
+        self._phone_number = phone_number or os.environ.get("TWILIO_PHONE_NUMBER", "")
         self._bus = bus
         self._client: Any = None
         self._handlers: List[ChannelHandler] = []
@@ -61,9 +55,7 @@ class TwilioSMSChannel(BaseChannel):
 
     def connect(self) -> None:
         try:
-            self._client = _create_twilio_client(
-                self._account_sid, self._auth_token
-            )
+            self._client = _create_twilio_client(self._account_sid, self._auth_token)
             self._status = ChannelStatus.CONNECTED
         except Exception:
             logger.exception("Failed to create Twilio client")
@@ -93,9 +85,7 @@ class TwilioSMSChannel(BaseChannel):
             self._publish_sent(channel, content, conversation_id)
             return True
         except Exception:
-            logger.exception(
-                "Failed to send SMS to %s", channel
-            )
+            logger.exception("Failed to send SMS to %s", channel)
             return False
 
     def status(self) -> ChannelStatus:

src/openjarvis/channels/twitch_channel.py

@@ -51,9 +51,7 @@ class TwitchChannel(BaseChannel):
         initial_channels: str = "",
         bus: Optional[EventBus] = None,
     ) -> None:
-        self._access_token = access_token or os.environ.get(
-            "TWITCH_ACCESS_TOKEN", ""
-        )
+        self._access_token = access_token or os.environ.get("TWITCH_ACCESS_TOKEN", "")
         self._client_id = client_id or os.environ.get("TWITCH_CLIENT_ID", "")
         self._nick = nick or os.environ.get("TWITCH_NICK", "")
         self._initial_channels = initial_channels or os.environ.get(
@@ -75,8 +73,7 @@ class TwitchChannel(BaseChannel):
             import twitchio  # noqa: F401
         except ImportError:
             raise ImportError(
-                "twitchio not installed. Install with: "
-                "uv sync --extra channel-twitch"
+                "twitchio not installed. Install with: uv sync --extra channel-twitch"
             )
         self._status = ChannelStatus.CONNECTED
 

src/openjarvis/channels/twitter.py

@@ -55,15 +55,18 @@ class TwitterChannel(BaseChannel):
         bus: Optional[EventBus] = None,
     ) -> None:
         self._bearer_token = bearer_token or os.environ.get(
-            "TWITTER_BEARER_TOKEN", "",
+            "TWITTER_BEARER_TOKEN",
+            "",
         )
         self._api_key = api_key or os.environ.get("TWITTER_API_KEY", "")
         self._api_secret = api_secret or os.environ.get("TWITTER_API_SECRET", "")
         self._access_token = access_token or os.environ.get(
-            "TWITTER_ACCESS_TOKEN", "",
+            "TWITTER_ACCESS_TOKEN",
+            "",
         )
         self._access_secret = access_secret or os.environ.get(
-            "TWITTER_ACCESS_SECRET", "",
+            "TWITTER_ACCESS_SECRET",
+            "",
         )
         self._poll_interval = poll_interval
         self._bus = bus
@@ -99,7 +102,8 @@ class TwitterChannel(BaseChannel):
 
             if self._access_token:
                 self._poll_thread = threading.Thread(
-                    target=self._poll_loop, daemon=True,
+                    target=self._poll_loop,
+                    daemon=True,
                 )
                 self._poll_thread.start()
         except ImportError:
@@ -189,7 +193,8 @@ class TwitterChannel(BaseChannel):
                     continue
 
                 response = self._client.get_users_mentions(
-                    id=user_id, **kwargs,
+                    id=user_id,
+                    **kwargs,
                 )
 
                 if response and response.data:
@@ -225,7 +230,10 @@ class TwitterChannel(BaseChannel):
             self._stop_event.wait(self._poll_interval)
 
     def _publish_sent(
-        self, channel: str, content: str, conversation_id: str,
+        self,
+        channel: str,
+        content: str,
+        conversation_id: str,
     ) -> None:
         """Publish a CHANNEL_MESSAGE_SENT event on the bus."""
         if self._bus is not None:

src/openjarvis/channels/viber_channel.py

@@ -64,8 +64,7 @@ class ViberChannel(BaseChannel):
             import viberbot  # noqa: F401
         except ImportError:
             raise ImportError(
-                "viberbot not installed. Install with: "
-                "uv sync --extra channel-viber"
+                "viberbot not installed. Install with: uv sync --extra channel-viber"
             )
         self._status = ChannelStatus.CONNECTED
 

src/openjarvis/channels/webhook.py

@@ -95,14 +95,18 @@ class WebhookChannel(BaseChannel):
                 headers["X-Webhook-Secret"] = self._secret
 
             resp = httpx.request(
-                self._method, self._url, json=payload,
-                headers=headers, timeout=10.0,
+                self._method,
+                self._url,
+                json=payload,
+                headers=headers,
+                timeout=10.0,
             )
             if resp.status_code < 300:
                 self._publish_sent(channel, content, conversation_id)
                 return True
             logger.warning(
-                "Webhook returned status %d", resp.status_code,
+                "Webhook returned status %d",
+                resp.status_code,
             )
             return False
         except Exception:

src/openjarvis/channels/whatsapp.py

@@ -44,7 +44,8 @@ class WhatsAppChannel(BaseChannel):
     ) -> None:
         self._token = access_token or os.environ.get("WHATSAPP_ACCESS_TOKEN", "")
         self._phone_number_id = phone_number_id or os.environ.get(
-            "WHATSAPP_PHONE_NUMBER_ID", "",
+            "WHATSAPP_PHONE_NUMBER_ID",
+            "",
         )
         self._bus = bus
         self._handlers: List[ChannelHandler] = []
@@ -82,10 +83,7 @@ class WhatsAppChannel(BaseChannel):
         try:
             import httpx
 
-            url = (
-                f"https://graph.facebook.com/v21.0/"
-                f"{self._phone_number_id}/messages"
-            )
+            url = f"https://graph.facebook.com/v21.0/{self._phone_number_id}/messages"
             headers = {
                 "Authorization": f"Bearer {self._token}",
                 "Content-Type": "application/json",
@@ -98,13 +96,17 @@ class WhatsAppChannel(BaseChannel):
             }
 
             resp = httpx.post(
-                url, json=payload, headers=headers, timeout=10.0,
+                url,
+                json=payload,
+                headers=headers,
+                timeout=10.0,
             )
             if resp.status_code < 300:
                 self._publish_sent(channel, content, conversation_id)
                 return True
             logger.warning(
-                "WhatsApp API returned status %d", resp.status_code,
+                "WhatsApp API returned status %d",
+                resp.status_code,
             )
             return False
         except Exception:

src/openjarvis/channels/whatsapp_baileys.py

@@ -109,8 +109,7 @@ class WhatsAppBaileysChannel(BaseChannel):
         pkg_dst = runtime / "package.json"
         pkg_src = _BRIDGE_SRC / "package.json"
         if pkg_src.exists() and (
-            not pkg_dst.exists()
-            or pkg_src.stat().st_mtime > pkg_dst.stat().st_mtime
+            not pkg_dst.exists() or pkg_src.stat().st_mtime > pkg_dst.stat().st_mtime
         ):
             shutil.copy2(pkg_src, pkg_dst)
 
@@ -169,7 +168,8 @@ class WhatsAppBaileysChannel(BaseChannel):
                 bufsize=1,
             )
             self._reader_thread = threading.Thread(
-                target=self._reader_loop, daemon=True,
+                target=self._reader_loop,
+                daemon=True,
             )
             self._reader_thread.start()
             logger.info(
@@ -218,11 +218,13 @@ class WhatsAppBaileysChannel(BaseChannel):
             return False
 
         try:
-            self._write_command({
-                "type": "send",
-                "jid": channel,
-                "text": content,
-            })
+            self._write_command(
+                {
+                    "type": "send",
+                    "jid": channel,
+                    "text": content,
+                }
+            )
             self._publish_sent(channel, content, conversation_id)
             return True
         except Exception:

src/openjarvis/channels/xmpp_channel.py

@@ -70,8 +70,7 @@ class XMPPChannel(BaseChannel):
             import slixmpp  # noqa: F401
         except ImportError:
             raise ImportError(
-                "slixmpp not installed. Install with: "
-                "uv sync --extra channel-xmpp"
+                "slixmpp not installed. Install with: uv sync --extra channel-xmpp"
             )
         self._status = ChannelStatus.CONNECTED
 

src/openjarvis/channels/zulip_channel.py

@@ -71,8 +71,7 @@ class ZulipChannel(BaseChannel):
             import zulip  # noqa: F401
         except ImportError:
             raise ImportError(
-                "zulip not installed. Install with: "
-                "uv sync --extra channel-zulip"
+                "zulip not installed. Install with: uv sync --extra channel-zulip"
             )
         self._status = ChannelStatus.CONNECTED
 

src/openjarvis/cli/__init__.py

@@ -15,8 +15,8 @@ from openjarvis.cli.chat_cmd import chat
 from openjarvis.cli.compose_cmd import compose
 from openjarvis.cli.config_cmd import config
 from openjarvis.cli.connect_cmd import connect
-from openjarvis.cli.deep_research_setup_cmd import deep_research_setup
 from openjarvis.cli.daemon_cmd import restart, start, status, stop
+from openjarvis.cli.deep_research_setup_cmd import deep_research_setup
 from openjarvis.cli.doctor_cmd import doctor
 from openjarvis.cli.eval_cmd import eval_group
 from openjarvis.cli.feedback_cmd import feedback_group

src/openjarvis/cli/_version_check.py

@@ -74,11 +74,15 @@ def _get_latest_version(current: str) -> str | None:
 
     try:
         _CACHE_PATH.parent.mkdir(parents=True, exist_ok=True)
-        _CACHE_PATH.write_text(json.dumps({
-            "last_check": time.time(),
-            "latest_version": latest,
-            "current_version": current,
-        }))
+        _CACHE_PATH.write_text(
+            json.dumps(
+                {
+                    "last_check": time.time(),
+                    "latest_version": latest,
+                    "current_version": current,
+                }
+            )
+        )
     except Exception:
         pass
 

src/openjarvis/cli/add_cmd.py

@@ -70,7 +70,9 @@ _MCP_TEMPLATES = {
 @click.argument("server_name")
 @click.option("--key", default=None, help="API key or token for the server.")
 @click.option(
-    "--args", "extra_args", default=None,
+    "--args",
+    "extra_args",
+    default=None,
     help="Additional arguments (comma-separated).",
 )
 def add(server_name: str, key: str | None, extra_args: str | None) -> None:

src/openjarvis/cli/agent_cmd.py

@@ -72,13 +72,19 @@ def list_agents() -> None:
             tasks = mgr.list_tasks(a["id"])
             bindings = mgr.list_channel_bindings(a["id"])
             status_style = {
-                "idle": "dim", "running": "green", "paused": "yellow",
-                "error": "red", "archived": "dim strike",
+                "idle": "dim",
+                "running": "green",
+                "paused": "yellow",
+                "error": "red",
+                "archived": "dim strike",
             }.get(a["status"], "")
             table.add_row(
-                a["id"], a["name"], a["agent_type"],
+                a["id"],
+                a["name"],
+                a["agent_type"],
                 f"[{status_style}]{a['status']}[/{status_style}]",
-                str(len(tasks)), str(len(bindings)),
+                str(len(tasks)),
+                str(len(bindings)),
             )
         console.print(table)
     except Exception as exc:
@@ -303,8 +309,10 @@ def templates() -> None:
         table.add_column("Description", style="white")
         for t in tpls:
             table.add_row(
-                t.get("id", ""), t.get("name", ""),
-                t.get("source", ""), t.get("description", "")[:60],
+                t.get("id", ""),
+                t.get("name", ""),
+                t.get("source", ""),
+                t.get("description", "")[:60],
             )
         console.print(table)
     except Exception as exc:
@@ -314,6 +322,7 @@ def templates() -> None:
 def _get_system():
     """Build a JarvisSystem for CLI commands that need scheduler/executor."""
     from openjarvis.system import SystemBuilder
+
     try:
         return SystemBuilder().build()
     except RuntimeError as exc:
@@ -332,6 +341,7 @@ def _get_scheduler_and_executor(system=None):
 def launch():
     """Interactive agent launcher."""
     from openjarvis.agents.manager import AgentManager as _AM
+
     templates = _AM.list_templates()
     click.echo("Available templates:")
     for i, t in enumerate(templates, 1):
@@ -363,7 +373,8 @@ def launch():
     manager = _get_manager()
     if template:
         agent_data = manager.create_from_template(
-            template["id"], name=name,
+            template["id"],
+            name=name,
         )
         agent_config = agent_data.get("config", {})
         agent_config.update(config)
@@ -374,7 +385,7 @@ def launch():
         agent_data = manager.create_agent(
             name=name, agent_type=agent_type, config=config
         )
-    click.echo(f"\nAgent \"{agent_data['name']}\" created (ID: {agent_data['id']})")
+    click.echo(f'\nAgent "{agent_data["name"]}" created (ID: {agent_data["id"]})')
 
 
 @agent.command("start")
@@ -391,7 +402,7 @@ def start_agent(agent_id):
         click.echo("Scheduler not available", err=True)
         raise SystemExit(1)
     scheduler.register_agent(agent_id)
-    click.echo(f"Agent \"{agent_data['name']}\" registered with scheduler")
+    click.echo(f'Agent "{agent_data["name"]}" registered with scheduler')
 
 
 @agent.command("stop")
@@ -408,7 +419,7 @@ def stop_agent(agent_id):
         click.echo("Scheduler not available", err=True)
         raise SystemExit(1)
     scheduler.deregister_agent(agent_id)
-    click.echo(f"Agent \"{agent_data['name']}\" deregistered from scheduler")
+    click.echo(f'Agent "{agent_data["name"]}" deregistered from scheduler')
 
 
 @agent.command("run")
@@ -423,7 +434,7 @@ def run_agent(agent_id):
     if agent_data["status"] == "archived":
         click.echo(f"Agent {agent_id} is archived and cannot be run", err=True)
         raise SystemExit(1)
-    click.echo(f"Running tick for \"{agent_data['name']}\"...")
+    click.echo(f'Running tick for "{agent_data["name"]}"...')
     _, executor, _ = _get_scheduler_and_executor()
     if executor is None:
         click.echo("Executor not available", err=True)
@@ -465,9 +476,7 @@ def status():
         max_cost = cfg.get("max_cost", 0)
         if max_cost > 0:
             pct = min(100, int(a.get("total_cost", 0) / max_cost * 100))
-            budget = (
-                f"${a.get('total_cost', 0):.2f}/{max_cost:.0f} ({pct}%)"
-            )
+            budget = f"${a.get('total_cost', 0):.2f}/{max_cost:.0f} ({pct}%)"
         else:
             budget = f"${a.get('total_cost', 0):.2f}"
         # Last seen column
@@ -491,9 +500,7 @@ def status():
 
 @agent.command("learning")
 @click.argument("agent_id")
-@click.option(
-    "--run", "trigger_run", is_flag=True, help="Trigger manual learning run"
-)
+@click.option("--run", "trigger_run", is_flag=True, help="Trigger manual learning run")
 def learning(agent_id, trigger_run):
     """Show learning history or trigger a manual run."""
     import datetime
@@ -505,35 +512,35 @@ def learning(agent_id, trigger_run):
         raise SystemExit(1)
 
     if trigger_run:
-        click.echo(f"Triggering learning for \"{agent_data['name']}\"...")
+        click.echo(f'Triggering learning for "{agent_data["name"]}"...')
         from openjarvis.core.events import EventType, get_event_bus
 
         bus = get_event_bus()
-        bus.publish(
-            EventType.AGENT_LEARNING_STARTED, {"agent_id": agent_id}
-        )
+        bus.publish(EventType.AGENT_LEARNING_STARTED, {"agent_id": agent_id})
         click.echo("Learning triggered.")
         return
 
     logs = manager.list_learning_log(agent_id)
     if not logs:
-        click.echo(f"No learning history for \"{agent_data['name']}\"")
+        click.echo(f'No learning history for "{agent_data["name"]}"')
         return
-    click.echo(f"Learning history for \"{agent_data['name']}\":")
+    click.echo(f'Learning history for "{agent_data["name"]}":')
     for entry in logs:
-        ts = datetime.datetime.fromtimestamp(
-            entry["created_at"]
-        ).strftime("%Y-%m-%d %H:%M")
+        ts = datetime.datetime.fromtimestamp(entry["created_at"]).strftime(
+            "%Y-%m-%d %H:%M"
+        )
         click.echo(
-            f"  {ts}  [{entry['event_type']}] "
-            f"{entry.get('description', '')[:60]}"
+            f"  {ts}  [{entry['event_type']}] {entry.get('description', '')[:60]}"
         )
 
 
 @agent.command("trace")
 @click.argument("agent_id")
 @click.option(
-    "--run", "run_number", default=None, type=int,
+    "--run",
+    "run_number",
+    default=None,
+    type=int,
     help="Specific run number",
 )
 @click.option("--limit", "-n", default=10, help="Number of traces to show")
@@ -551,36 +558,32 @@ def trace(agent_id, run_number, limit):
         raise SystemExit(1)
 
     config = load_config()
-    store = TraceStore(
-        config.traces.db_path or "~/.openjarvis/traces.db"
-    )
+    store = TraceStore(config.traces.db_path or "~/.openjarvis/traces.db")
     traces = store.list_traces(agent=agent_id, limit=limit)
 
     if not traces:
-        click.echo(f"No traces for \"{agent_data['name']}\"")
+        click.echo(f'No traces for "{agent_data["name"]}"')
         return
 
     if run_number is not None and 1 <= run_number <= len(traces):
         t = traces[run_number - 1]
         click.echo(
-            f"Trace #{run_number} — {t.outcome} "
-            f"({t.total_latency_seconds:.1f}s)"
+            f"Trace #{run_number} — {t.outcome} ({t.total_latency_seconds:.1f}s)"
         )
         for i, step in enumerate(t.steps, 1):
             click.echo(
-                f"  Step {i}: [{step.step_type.value}] "
-                f"{step.duration_seconds:.2f}s"
+                f"  Step {i}: [{step.step_type.value}] {step.duration_seconds:.2f}s"
             )
             inp = str(step.input)[:80]
             out = str(step.output)[:80]
             click.echo(f"    In:  {inp}")
             click.echo(f"    Out: {out}")
     else:
-        click.echo(f"Traces for \"{agent_data['name']}\":")
+        click.echo(f'Traces for "{agent_data["name"]}":')
         for i, t in enumerate(traces, 1):
-            ts = datetime.datetime.fromtimestamp(
-                t.started_at
-            ).strftime("%Y-%m-%d %H:%M")
+            ts = datetime.datetime.fromtimestamp(t.started_at).strftime(
+                "%Y-%m-%d %H:%M"
+            )
             click.echo(
                 f"  #{i}  {ts}  {t.outcome}  "
                 f"{t.total_latency_seconds:.1f}s  "
@@ -602,9 +605,9 @@ def logs(agent_id, limit):
         raise SystemExit(1)
     checkpoints = manager.list_checkpoints(agent_id)
     if not checkpoints:
-        click.echo(f"No execution history for \"{agent_data['name']}\"")
+        click.echo(f'No execution history for "{agent_data["name"]}"')
         return
-    click.echo(f"Recent runs for \"{agent_data['name']}\":")
+    click.echo(f'Recent runs for "{agent_data["name"]}":')
     for cp in checkpoints[:limit]:
         ts = datetime.datetime.fromtimestamp(cp["created_at"]).strftime(
             "%Y-%m-%d %H:%M"
@@ -651,8 +654,10 @@ def watch(agent_id):
     click.echo("Watching agent events... (press Ctrl+C to stop)")
     bus = get_event_bus()
     agent_events = [
-        EventType.AGENT_TICK_START, EventType.AGENT_TICK_END,
-        EventType.AGENT_TICK_ERROR, EventType.AGENT_BUDGET_EXCEEDED,
+        EventType.AGENT_TICK_START,
+        EventType.AGENT_TICK_END,
+        EventType.AGENT_TICK_ERROR,
+        EventType.AGENT_BUDGET_EXCEEDED,
     ]
 
     def _on_event(event):

src/openjarvis/cli/auth_cmd.py

@@ -46,16 +46,11 @@ def create_key() -> None:
         content += f'\n[server.auth]\napi_key = "{key}"\n'
 
     config_path.write_text(content)
-    os.chmod(
-        config_path, stat.S_IRUSR | stat.S_IWUSR
-    )  # 0600
+    os.chmod(config_path, stat.S_IRUSR | stat.S_IWUSR)  # 0600
 
     click.echo(f"API key generated: {key}")
     click.echo(f"Stored in: {config_path}")
-    click.echo(
-        "File permissions set to 0600 "
-        "(user-only read/write)."
-    )
+    click.echo("File permissions set to 0600 (user-only read/write).")
 
 
 @auth.command("revoke-key")
@@ -71,8 +66,6 @@ def revoke_key() -> None:
         click.echo("No API key found in config.")
         return
 
-    content = re.sub(
-        r'api_key\s*=\s*"[^"]*"', 'api_key = ""', content
-    )
+    content = re.sub(r'api_key\s*=\s*"[^"]*"', 'api_key = ""', content)
     config_path.write_text(content)
     click.echo("API key revoked.")

src/openjarvis/cli/bench_cmd.py

@@ -61,7 +61,7 @@ def _detect_stat_groups(metrics: dict[str, float]) -> dict[str, dict[str, float]
     for key, val in metrics.items():
         for pfx in _STATS_PREFIXES:
             if key.startswith(pfx):
-                base = key[len(pfx):]
+                base = key[len(pfx) :]
                 groups.setdefault(base, {})[pfx.rstrip("_")] = val
                 break
     return groups
@@ -152,27 +152,46 @@ def bench() -> None:
 @click.option("-m", "--model", "model_name", default=None, help="Model to benchmark.")
 @click.option("-e", "--engine", "engine_key", default=None, help="Engine backend.")
 @click.option(
-    "-n", "--samples", "num_samples", default=10, type=int,
+    "-n",
+    "--samples",
+    "num_samples",
+    default=10,
+    type=int,
     help="Number of samples per benchmark.",
 )
 @click.option(
-    "-b", "--benchmark", "benchmark_name", default=None,
+    "-b",
+    "--benchmark",
+    "benchmark_name",
+    default=None,
     help="Specific benchmark to run (default: all).",
 )
 @click.option(
-    "-o", "--output", "output_path", default=None, type=click.Path(),
+    "-o",
+    "--output",
+    "output_path",
+    default=None,
+    type=click.Path(),
     help="Write JSONL results to file.",
 )
 @click.option(
-    "--json", "output_json", is_flag=True,
+    "--json",
+    "output_json",
+    is_flag=True,
     help="Output JSON summary to stdout.",
 )
 @click.option(
-    "-w", "--warmup", "warmup", default=0, type=int,
+    "-w",
+    "--warmup",
+    "warmup",
+    default=0,
+    type=int,
     help="Number of warmup iterations before measurement.",
 )
 @click.option(
-    "--setup-energy", "setup_energy", is_flag=True,
+    "--setup-energy",
+    "setup_energy",
+    is_flag=True,
     help="Run energy monitor setup script when missing (for energy benchmark).",
 )
 def run(
@@ -250,16 +269,12 @@ def run(
         import platform
 
         setup_script = (
-            Path(__file__).resolve().parents[3]
-            / "scripts"
-            / "setup-energy-monitor.sh"
-        )
-        is_darwin_arm = (
-            platform.system() == "Darwin"
-            and platform.machine() == "arm64"
+            Path(__file__).resolve().parents[3] / "scripts" / "setup-energy-monitor.sh"
         )
+        is_darwin_arm = platform.system() == "Darwin" and platform.machine() == "arm64"
         extra_hint = (
-            "openjarvis[energy-apple]" if is_darwin_arm
+            "openjarvis[energy-apple]"
+            if is_darwin_arm
             else "openjarvis[gpu-metrics]"
             if platform.system() == "Linux"
             else "openjarvis[energy-all]"
@@ -314,8 +329,10 @@ def run(
         f"[bold cyan]Running {len(benchmarks)} benchmark(s)...[/bold cyan]",
     ):
         results = suite.run_all(
-            engine, model_name,
-            num_samples=num_samples, warmup_samples=warmup,
+            engine,
+            model_name,
+            num_samples=num_samples,
+            warmup_samples=warmup,
             energy_monitor=energy_monitor,
         )
 

src/openjarvis/cli/channel_cmd.py

@@ -148,7 +148,9 @@ def channel() -> None:
 
 @channel.command("list")
 @click.option(
-    "--channel-type", default=None, help=_CHANNEL_TYPE_HELP,
+    "--channel-type",
+    default=None,
+    help=_CHANNEL_TYPE_HELP,
 )
 def channel_list(
     channel_type: Optional[str],
@@ -186,7 +188,9 @@ def channel_list(
 @click.argument("target")
 @click.argument("message")
 @click.option(
-    "--channel-type", default=None, help=_CHANNEL_TYPE_HELP,
+    "--channel-type",
+    default=None,
+    help=_CHANNEL_TYPE_HELP,
 )
 def channel_send(
     target: str,
@@ -216,7 +220,9 @@ def channel_send(
 
 @channel.command("status")
 @click.option(
-    "--channel-type", default=None, help=_CHANNEL_TYPE_HELP,
+    "--channel-type",
+    default=None,
+    help=_CHANNEL_TYPE_HELP,
 )
 def channel_status(
     channel_type: Optional[str],

src/openjarvis/cli/channels_cmd.py

@@ -27,12 +27,14 @@ def channels_status() -> None:
 
     if is_running():
         table.add_row(
-            "iMessage", "[green]running[/green]",
+            "iMessage",
+            "[green]running[/green]",
             "Polling chat.db",
         )
     else:
         table.add_row(
-            "iMessage", "[dim]stopped[/dim]",
+            "iMessage",
+            "[dim]stopped[/dim]",
             "jarvis channels imessage-start <contact>",
         )
 
@@ -47,7 +49,8 @@ def channels_status() -> None:
     help="Run in background.",
 )
 def imessage_start(
-    chat_identifier: str, background: bool,
+    chat_identifier: str,
+    background: bool,
 ) -> None:
     """Start the iMessage daemon for CHAT_IDENTIFIER.
 
@@ -61,9 +64,7 @@ def imessage_start(
     console = Console()
 
     if is_running():
-        console.print(
-            "[yellow]iMessage daemon already running.[/yellow]"
-        )
+        console.print("[yellow]iMessage daemon already running.[/yellow]")
         return
 
     if background:
@@ -71,9 +72,11 @@ def imessage_start(
 
         proc = subprocess.Popen(
             [
-                sys.executable, "-m",
+                sys.executable,
+                "-m",
                 "openjarvis.channels.imessage_daemon",
-                "--chat", chat_identifier,
+                "--chat",
+                chat_identifier,
             ],
             stdout=subprocess.DEVNULL,
             stderr=subprocess.DEVNULL,
@@ -88,8 +91,7 @@ def imessage_start(
         )
     else:
         console.print(
-            f"[green]Starting iMessage daemon[/green] "
-            f"— monitoring {chat_identifier}"
+            f"[green]Starting iMessage daemon[/green] — monitoring {chat_identifier}"
         )
         console.print("Press Ctrl+C to stop.\n")
 
@@ -117,13 +119,16 @@ def imessage_start(
             KnowledgeSearchTool(retriever=retriever),
             KnowledgeSQLTool(store=store),
             ScanChunksTool(
-                store=store, engine=engine,
+                store=store,
+                engine=engine,
                 model="qwen3.5:4b",
             ),
             ThinkTool(),
         ]
         agent = DeepResearchAgent(
-            engine=engine, model="qwen3.5:4b", tools=tools,
+            engine=engine,
+            model="qwen3.5:4b",
+            tools=tools,
         )
 
         def handler(text: str) -> str:
@@ -145,6 +150,4 @@ def imessage_stop() -> None:
     if stop_daemon():
         console.print("[green]iMessage daemon stopped.[/green]")
     else:
-        console.print(
-            "[dim]iMessage daemon is not running.[/dim]"
-        )
+        console.print("[dim]iMessage daemon is not running.[/dim]")

src/openjarvis/cli/chat_cmd.py

@@ -162,8 +162,7 @@ def chat(
             continue
         elif cmd == "/model":
             console.print(
-                f"Model: [cyan]{model}[/cyan]  "
-                f"Engine: [cyan]{engine_name}[/cyan]"
+                f"Model: [cyan]{model}[/cyan]  Engine: [cyan]{engine_name}[/cyan]"
             )
             continue
         elif cmd == "/help":
@@ -183,9 +182,7 @@ def chat(
                 for msg in history:
                     role_str = msg.role if isinstance(msg.role, str) else msg.role.value
                     role = role_str.upper()
-                    console.print(
-                        f"[bold]{role}:[/bold] {msg.content[:200]}"
-                    )
+                    console.print(f"[bold]{role}:[/bold] {msg.content[:200]}")
             continue
 
         # Add user message
@@ -196,9 +193,7 @@ def chat(
             if agent is not None:
                 response = agent.run(user_input)
                 content = (
-                    response.content
-                    if hasattr(response, "content")
-                    else str(response)
+                    response.content if hasattr(response, "content") else str(response)
                 )
             else:
                 result = engine.generate(history, model=model)

src/openjarvis/cli/compose_cmd.py

@@ -31,7 +31,10 @@ def compose() -> None:
 
 @compose.command("list")
 @click.option(
-    "-k", "--kind", "kind", default=None,
+    "-k",
+    "--kind",
+    "kind",
+    default=None,
     type=click.Choice(["discrete", "operator"]),
     help="Filter by recipe kind.",
 )
@@ -203,13 +206,19 @@ def compose_run(name: str, query: tuple[str, ...], output_json: bool) -> None:
 
             if output_json:
                 import json as json_mod
+
                 if isinstance(result, str):
                     click.echo(json_mod.dumps({"content": result}, indent=2))
                 else:
-                    click.echo(json_mod.dumps({
-                        "content": result.content,
-                        "turns": getattr(result, "turns", 1),
-                    }, indent=2))
+                    click.echo(
+                        json_mod.dumps(
+                            {
+                                "content": result.content,
+                                "turns": getattr(result, "turns", 1),
+                            },
+                            indent=2,
+                        )
+                    )
             else:
                 content = result if isinstance(result, str) else result.content
                 click.echo(content)
@@ -228,19 +237,33 @@ def compose_run(name: str, query: tuple[str, ...], output_json: bool) -> None:
 @compose.command("bench")
 @click.argument("name")
 @click.option(
-    "-b", "--benchmark", "benchmark", default=None, multiple=True,
+    "-b",
+    "--benchmark",
+    "benchmark",
+    default=None,
+    multiple=True,
     help="Override benchmarks (can specify multiple).",
 )
 @click.option(
-    "-n", "--max-samples", "max_samples", type=int, default=None,
+    "-n",
+    "--max-samples",
+    "max_samples",
+    type=int,
+    default=None,
     help="Maximum samples per benchmark.",
 )
 @click.option(
-    "--judge", "judge_model", default=None,
+    "--judge",
+    "judge_model",
+    default=None,
     help="LLM judge model override.",
 )
 @click.option(
-    "-v", "--verbose", "verbose", is_flag=True, default=False,
+    "-v",
+    "--verbose",
+    "verbose",
+    is_flag=True,
+    default=False,
     help="Verbose logging.",
 )
 def compose_bench(
@@ -302,9 +325,7 @@ def compose_bench(
         results_table.add_column("Errors", justify="right", style="red")
 
         for i, rc in enumerate(run_configs, 1):
-            console.print(
-                f"\n[bold]Run {i}/{len(run_configs)}:[/bold] {rc.benchmark}"
-            )
+            console.print(f"\n[bold]Run {i}/{len(run_configs)}:[/bold] {rc.benchmark}")
             try:
                 summary = _run_single(rc, console=console)
                 results_table.add_row(

src/openjarvis/cli/dashboard.py

@@ -30,6 +30,7 @@ class DashboardApp:
         """Check if textual is available."""
         try:
             import textual  # noqa: F401
+
             return True
         except ImportError:
             return False
@@ -86,21 +87,16 @@ class DashboardApp:
                     classes="panel",
                 )
                 yield Log(
-                    id="events-panel", classes="panel",
+                    id="events-panel",
+                    classes="panel",
                 )
                 yield Static(
-                    "Telemetry\n"
-                    "─────────\n"
-                    "Throughput: --\n"
-                    "Latency: --\n"
-                    "Energy: --",
+                    "Telemetry\n─────────\nThroughput: --\nLatency: --\nEnergy: --",
                     id="telemetry-panel",
                     classes="panel",
                 )
                 yield Static(
-                    "Agent Activity\n"
-                    "──────────────\n"
-                    "No active agents.",
+                    "Agent Activity\n──────────────\nNo active agents.",
                     id="agent-panel",
                     classes="panel",
                 )
@@ -113,6 +109,7 @@ class DashboardApp:
                 # Try to connect to event bus
                 try:
                     from openjarvis.core.events import get_event_bus
+
                     bus = get_event_bus()
 
                     def _on_event(event: Any) -> None:
@@ -124,6 +121,7 @@ class DashboardApp:
                             logger.debug("Event serialization failed: %s", exc)
 
                     from openjarvis.core.events import EventType
+
                     for et in EventType:
                         bus.subscribe(et, _on_event)
                 except Exception:
@@ -137,30 +135,16 @@ class DashboardApp:
                 lines = ["System Status", "─────────────"]
                 try:
                     from openjarvis.core.config import load_config
+
                     config = load_config()
-                    lines.append(
-                        f"Engine: {config.engine.default}"
-                    )
-                    model = (
-                        config.intelligence.default_model
-                        or 'auto'
-                    )
+                    lines.append(f"Engine: {config.engine.default}")
+                    model = config.intelligence.default_model or "auto"
                     lines.append(f"Model: {model}")
-                    backend = (
-                        config.tools.storage.default_backend
-                    )
+                    backend = config.tools.storage.default_backend
                     lines.append(f"Memory: {backend}")
-                    sec = (
-                        'enabled'
-                        if config.security.enabled
-                        else 'disabled'
-                    )
+                    sec = "enabled" if config.security.enabled else "disabled"
                     lines.append(f"Security: {sec}")
-                    tel = (
-                        'enabled'
-                        if config.telemetry.enabled
-                        else 'disabled'
-                    )
+                    tel = "enabled" if config.telemetry.enabled else "disabled"
                     lines.append(f"Telemetry: {tel}")
                 except Exception:
                     lines.append("Config: not loaded")
@@ -175,8 +159,7 @@ def launch_dashboard(config: Optional[Any] = None) -> None:
     app = DashboardApp(config=config)
     if not app.available():
         raise ImportError(
-            "TUI dashboard requires 'textual'. "
-            "Install with: uv sync --extra dashboard"
+            "TUI dashboard requires 'textual'. Install with: uv sync --extra dashboard"
         )
     app.run()
 

src/openjarvis/cli/deep_research_setup_cmd.py

@@ -57,26 +57,32 @@ def detect_local_sources(
 
     notes_path = notes_db_path or _DEFAULT_NOTES_DB
     if notes_path.exists():
-        sources.append({
-            "connector_id": "apple_notes",
-            "display_name": "Apple Notes",
-            "config": {"db_path": str(notes_path)},
-        })
+        sources.append(
+            {
+                "connector_id": "apple_notes",
+                "display_name": "Apple Notes",
+                "config": {"db_path": str(notes_path)},
+            }
+        )
 
     imessage_path = imessage_db_path or _DEFAULT_IMESSAGE_DB
     if imessage_path.exists():
-        sources.append({
-            "connector_id": "imessage",
-            "display_name": "iMessage",
-            "config": {"db_path": str(imessage_path)},
-        })
+        sources.append(
+            {
+                "connector_id": "imessage",
+                "display_name": "iMessage",
+                "config": {"db_path": str(imessage_path)},
+            }
+        )
 
     if obsidian_vault_path and obsidian_vault_path.is_dir():
-        sources.append({
-            "connector_id": "obsidian",
-            "display_name": "Obsidian / Markdown",
-            "config": {"vault_path": str(obsidian_vault_path)},
-        })
+        sources.append(
+            {
+                "connector_id": "obsidian",
+                "display_name": "Obsidian / Markdown",
+                "config": {"vault_path": str(obsidian_vault_path)},
+            }
+        )
 
     return sources
 
@@ -137,11 +143,13 @@ def detect_token_sources(
             continue
         if not data or not any(v for v in data.values() if v):
             continue
-        sources.append({
-            "connector_id": ts["connector_id"],
-            "display_name": ts["display_name"],
-            "config": {},
-        })
+        sources.append(
+            {
+                "connector_id": ts["connector_id"],
+                "display_name": ts["display_name"],
+                "config": {},
+            }
+        )
 
     return sources
 
@@ -154,8 +162,7 @@ def _prompt_connect_sources(console: Console) -> List[Dict[str, Any]]:
 
     while True:
         unconnected = [
-            ts for ts in _TOKEN_SOURCES
-            if not (cdir / ts["creds_file"]).exists()
+            ts for ts in _TOKEN_SOURCES if not (cdir / ts["creds_file"]).exists()
         ]
         if not unconnected:
             console.print("[dim]All token sources already connected.[/dim]")
@@ -165,10 +172,7 @@ def _prompt_connect_sources(console: Console) -> List[Dict[str, Any]]:
             break
 
         names = [ts["connector_id"] for ts in unconnected]
-        labels = [
-            f"{ts['display_name']} ({ts['connector_id']})"
-            for ts in unconnected
-        ]
+        labels = [f"{ts['display_name']} ({ts['connector_id']})" for ts in unconnected]
         console.print("Available:")
         for label in labels:
             console.print(f"  {label}")
@@ -185,11 +189,13 @@ def _prompt_connect_sources(console: Console) -> List[Dict[str, Any]]:
         connector.handle_callback(token.strip())
         console.print(f"  [green]{ts['display_name']}: connected![/green]")
 
-        connected.append({
-            "connector_id": choice,
-            "display_name": ts["display_name"],
-            "config": {},
-        })
+        connected.append(
+            {
+                "connector_id": choice,
+                "display_name": ts["display_name"],
+                "config": {},
+            }
+        )
 
     return connected
 
@@ -203,27 +209,35 @@ def _instantiate_connector(connector_id: str, config: Dict[str, Any]) -> Any:
     """Lazily import and instantiate a connector by ID."""
     if connector_id == "apple_notes":
         from openjarvis.connectors.apple_notes import AppleNotesConnector
+
         return AppleNotesConnector(db_path=config.get("db_path", ""))
     elif connector_id == "imessage":
         from openjarvis.connectors.imessage import IMessageConnector
+
         return IMessageConnector(db_path=config.get("db_path", ""))
     elif connector_id == "obsidian":
         from openjarvis.connectors.obsidian import ObsidianConnector
+
         return ObsidianConnector(vault_path=config.get("vault_path", ""))
     elif connector_id == "gmail_imap":
         from openjarvis.connectors.gmail_imap import GmailIMAPConnector
+
         return GmailIMAPConnector()
     elif connector_id == "outlook":
         from openjarvis.connectors.outlook import OutlookConnector
+
         return OutlookConnector()
     elif connector_id == "slack":
         from openjarvis.connectors.slack_connector import SlackConnector
+
         return SlackConnector()
     elif connector_id == "notion":
         from openjarvis.connectors.notion import NotionConnector
+
         return NotionConnector()
     elif connector_id == "granola":
         from openjarvis.connectors.granola import GranolaConnector
+
         return GranolaConnector()
     else:
         msg = f"Unknown connector: {connector_id}"
@@ -277,8 +291,7 @@ def _launch_chat(store: KnowledgeStore, console: Console) -> None:
     engine = OllamaEngine()
     if not engine.health():
         console.print(
-            "[red]Ollama is not running.[/red] Start it with: "
-            "[bold]ollama serve[/bold]"
+            "[red]Ollama is not running.[/red] Start it with: [bold]ollama serve[/bold]"
         )
         return
 
@@ -404,18 +417,15 @@ def deep_research_setup(obsidian_vault: Optional[str], skip_chat: bool) -> None:
     for src in all_sources:
         try:
             connector = _instantiate_connector(
-                src["connector_id"], src["config"],
+                src["connector_id"],
+                src["config"],
             )
             pipeline = IngestionPipeline(store)
             engine = SyncEngine(pipeline)
             chunks = engine.sync(connector)
-            console.print(
-                f"  {src['display_name']}: [green]{chunks} chunks[/green]"
-            )
+            console.print(f"  {src['display_name']}: [green]{chunks} chunks[/green]")
         except Exception as exc:  # noqa: BLE001
-            console.print(
-                f"  {src['display_name']}: [red]error: {exc}[/red]"
-            )
+            console.print(f"  {src['display_name']}: [red]error: {exc}[/red]")
 
     total = store.count()
     console.print(

src/openjarvis/cli/eval_cmd.py

@@ -28,7 +28,8 @@ KNOWN_BENCHMARKS = {
     "swebench": {"category": "agentic", "description": "SWE-bench code patches"},
     "swefficiency": {"category": "agentic", "description": "SWEfficiency optimization"},
     "terminalbench": {
-        "category": "agentic", "description": "TerminalBench terminal tasks",
+        "category": "agentic",
+        "description": "TerminalBench terminal tasks",
     },
     "terminalbench-native": {
         "category": "agentic",
@@ -98,95 +99,155 @@ def eval_list() -> None:
 
 @eval_group.command("run")
 @click.option(
-    "-c", "--config", "config_path", default=None, type=click.Path(),
+    "-c",
+    "--config",
+    "config_path",
+    default=None,
+    type=click.Path(),
     help="TOML config file for suite runs.",
 )
 @click.option(
-    "-b", "--benchmark", "benchmark", default=None,
+    "-b",
+    "--benchmark",
+    "benchmark",
+    default=None,
     help="Benchmark to run (e.g. supergpqa, gaia, frames, wildchat).",
 )
 @click.option(
-    "-m", "--model", "model", default=None,
+    "-m",
+    "--model",
+    "model",
+    default=None,
     help="Model identifier.",
 )
 @click.option(
-    "-n", "--max-samples", "max_samples", type=int, default=None,
+    "-n",
+    "--max-samples",
+    "max_samples",
+    type=int,
+    default=None,
     help="Maximum samples to evaluate.",
 )
 @click.option(
-    "--backend", "backend", default="jarvis-direct",
+    "--backend",
+    "backend",
+    default="jarvis-direct",
     help="Inference backend (jarvis-direct or jarvis-agent).",
 )
 @click.option(
-    "--agent", "agent_name", default=None,
+    "--agent",
+    "agent_name",
+    default=None,
     help="Agent name for jarvis-agent backend.",
 )
 @click.option(
-    "-e", "--engine", "engine_key", default=None,
+    "-e",
+    "--engine",
+    "engine_key",
+    default=None,
     help="Engine key (ollama, vllm, cloud, ...).",
 )
 @click.option(
-    "--tools", "tools", default="",
+    "--tools",
+    "tools",
+    default="",
     help="Comma-separated tool names.",
 )
 @click.option(
-    "--telemetry/--no-telemetry", "telemetry", default=False,
+    "--telemetry/--no-telemetry",
+    "telemetry",
+    default=False,
     help="Enable telemetry collection during eval.",
 )
 @click.option(
-    "--gpu-metrics/--no-gpu-metrics", "gpu_metrics", default=False,
+    "--gpu-metrics/--no-gpu-metrics",
+    "gpu_metrics",
+    default=False,
     help="Enable GPU metrics collection.",
 )
 @click.option(
-    "--seed", "seed", type=int, default=42,
+    "--seed",
+    "seed",
+    type=int,
+    default=42,
     help="Random seed.",
 )
 @click.option(
-    "--temperature", "temperature", type=float, default=0.0,
+    "--temperature",
+    "temperature",
+    type=float,
+    default=0.0,
     help="Generation temperature.",
 )
 @click.option(
-    "--max-tokens", "max_tokens", type=int, default=2048,
+    "--max-tokens",
+    "max_tokens",
+    type=int,
+    default=2048,
     help="Max output tokens.",
 )
 @click.option(
-    "--model-filter", "model_filter", default=None,
+    "--model-filter",
+    "model_filter",
+    default=None,
     help="Filter models by name substring (for multi-model configs).",
 )
 @click.option(
-    "-o", "--output", "output_path", default=None, type=click.Path(),
+    "-o",
+    "--output",
+    "output_path",
+    default=None,
+    type=click.Path(),
     help="Output JSONL path.",
 )
 @click.option(
-    "--wandb-project", "wandb_project", default="",
+    "--wandb-project",
+    "wandb_project",
+    default="",
     help="W&B project name (enables W&B tracking).",
 )
 @click.option(
-    "--wandb-entity", "wandb_entity", default="",
+    "--wandb-entity",
+    "wandb_entity",
+    default="",
     help="W&B entity (team or user).",
 )
 @click.option(
-    "--wandb-tags", "wandb_tags", default="",
+    "--wandb-tags",
+    "wandb_tags",
+    default="",
     help="Comma-separated W&B tags.",
 )
 @click.option(
-    "--wandb-group", "wandb_group", default="",
+    "--wandb-group",
+    "wandb_group",
+    default="",
     help="W&B run group.",
 )
 @click.option(
-    "--sheets-id", "sheets_spreadsheet_id", default="",
+    "--sheets-id",
+    "sheets_spreadsheet_id",
+    default="",
     help="Google Sheets spreadsheet ID.",
 )
 @click.option(
-    "--sheets-worksheet", "sheets_worksheet", default="Results",
+    "--sheets-worksheet",
+    "sheets_worksheet",
+    default="Results",
     help="Google Sheets worksheet name.",
 )
 @click.option(
-    "--sheets-creds", "sheets_credentials_path", default="",
+    "--sheets-creds",
+    "sheets_credentials_path",
+    default="",
     help="Path to Google service account JSON.",
 )
 @click.option(
-    "-v", "--verbose", "verbose", is_flag=True, default=False,
+    "-v",
+    "--verbose",
+    "verbose",
+    is_flag=True,
+    default=False,
     help="Verbose logging.",
 )
 def eval_run(
@@ -237,13 +298,9 @@ def eval_run(
 
         # Filter by model name substring if requested
         if model_filter:
-            run_configs = [
-                rc for rc in run_configs if model_filter in rc.model
-            ]
+            run_configs = [rc for rc in run_configs if model_filter in rc.model]
             if not run_configs:
-                console.print(
-                    f"[red]No models match filter '{model_filter}'[/red]"
-                )
+                console.print(f"[red]No models match filter '{model_filter}'[/red]")
                 sys.exit(1)
 
         console.print(
@@ -257,9 +314,7 @@ def eval_run(
         try:
             from openjarvis.evals.cli import _run_single
         except ImportError:
-            console.print(
-                "[red]Eval CLI module not available.[/red]"
-            )
+            console.print("[red]Eval CLI module not available.[/red]")
             sys.exit(1)
 
         for i, rc in enumerate(run_configs, 1):
@@ -286,9 +341,7 @@ def eval_run(
         )
 
     if benchmark not in KNOWN_BENCHMARKS:
-        console.print(
-            f"[yellow]Warning: unknown benchmark '{benchmark}'[/yellow]"
-        )
+        console.print(f"[yellow]Warning: unknown benchmark '{benchmark}'[/yellow]")
 
     try:
         from openjarvis.evals.core.types import RunConfig
@@ -299,9 +352,7 @@ def eval_run(
         )
         sys.exit(1)
 
-    tool_list = (
-        [t.strip() for t in tools.split(",") if t.strip()] if tools else []
-    )
+    tool_list = [t.strip() for t in tools.split(",") if t.strip()] if tools else []
 
     config = RunConfig(
         benchmark=benchmark,
@@ -340,9 +391,7 @@ def eval_run(
             f"({summary.correct}/{summary.scored_samples})"
         )
     except ImportError:
-        console.print(
-            "[red]Eval CLI module not available.[/red]"
-        )
+        console.print("[red]Eval CLI module not available.[/red]")
         sys.exit(1)
     except Exception as exc:
         console.print(f"[red]Error: {exc}[/red]")
@@ -352,7 +401,9 @@ def eval_run(
 @eval_group.command("compare")
 @click.argument("result_files", nargs=-1, required=True)
 @click.option(
-    "--metric", "metric", default="accuracy",
+    "--metric",
+    "metric",
+    default="accuracy",
     help="Metric to compare across runs (default: accuracy).",
 )
 def eval_compare(result_files: tuple[str, ...], metric: str) -> None:
@@ -367,13 +418,15 @@ def eval_compare(result_files: tuple[str, ...], metric: str) -> None:
         if summary_path.exists():
             with open(summary_path) as f:
                 data = json.load(f)
-            rows.append({
-                "file": path.name,
-                "benchmark": data.get("benchmark", "?"),
-                "model": data.get("model", "?"),
-                "value": data.get(metric, "N/A"),
-                "samples": data.get("total_samples", 0),
-            })
+            rows.append(
+                {
+                    "file": path.name,
+                    "benchmark": data.get("benchmark", "?"),
+                    "model": data.get("model", "?"),
+                    "value": data.get(metric, "N/A"),
+                    "samples": data.get("total_samples", 0),
+                }
+            )
         elif path.exists() and path.suffix == ".jsonl":
             # Fall back to reading JSONL and computing metric on-the-fly
             records = []
@@ -384,29 +437,25 @@ def eval_compare(result_files: tuple[str, ...], metric: str) -> None:
                         records.append(json.loads(line))
             if records:
                 if metric == "accuracy":
-                    scored = [
-                        r for r in records
-                        if r.get("is_correct") is not None
-                    ]
+                    scored = [r for r in records if r.get("is_correct") is not None]
                     correct = [r for r in scored if r["is_correct"]]
-                    value = (
-                        len(correct) / len(scored) if scored else 0.0
-                    )
+                    value = len(correct) / len(scored) if scored else 0.0
                 else:
                     values = [
-                        r[metric] for r in records
+                        r[metric]
+                        for r in records
                         if metric in r and r[metric] is not None
                     ]
-                    value = (
-                        sum(values) / len(values) if values else "N/A"
-                    )
-                rows.append({
-                    "file": path.name,
-                    "benchmark": records[0].get("benchmark", "?"),
-                    "model": records[0].get("model", "?"),
-                    "value": value,
-                    "samples": len(records),
-                })
+                    value = sum(values) / len(values) if values else "N/A"
+                rows.append(
+                    {
+                        "file": path.name,
+                        "benchmark": records[0].get("benchmark", "?"),
+                        "model": records[0].get("model", "?"),
+                        "value": value,
+                        "samples": len(records),
+                    }
+                )
         else:
             console.print(f"[yellow]Skipping missing file: {path_str}[/yellow]")
 
@@ -429,8 +478,11 @@ def eval_compare(result_files: tuple[str, ...], metric: str) -> None:
         val = row["value"]
         val_str = f"{val:.4f}" if isinstance(val, float) else str(val)
         table.add_row(
-            row["file"], row["benchmark"], row["model"],
-            val_str, str(row["samples"]),
+            row["file"],
+            row["benchmark"],
+            row["model"],
+            val_str,
+            str(row["samples"]),
         )
 
     console.print(table)
@@ -454,8 +506,7 @@ def eval_report(result_file: str) -> None:
         console.print(f"  [cyan]Model:[/cyan]     {data.get('model', '?')}")
         console.print(f"  [cyan]Backend:[/cyan]   {data.get('backend', '?')}")
         console.print(
-            f"  [cyan]Accuracy:[/cyan]  "
-            f"[bold]{data.get('accuracy', 0.0):.4f}[/bold]"
+            f"  [cyan]Accuracy:[/cyan]  [bold]{data.get('accuracy', 0.0):.4f}[/bold]"
         )
         console.print(f"  [cyan]Samples:[/cyan]   {data.get('total_samples', 0)}")
         console.print(f"  [cyan]Scored:[/cyan]    {data.get('scored_samples', 0)}")
@@ -466,8 +517,7 @@ def eval_report(result_file: str) -> None:
             f"{data.get('mean_latency_seconds', 0.0):.4f}s (mean)"
         )
         console.print(
-            f"  [cyan]Cost:[/cyan]      "
-            f"${data.get('total_cost_usd', 0.0):.6f}"
+            f"  [cyan]Cost:[/cyan]      ${data.get('total_cost_usd', 0.0):.6f}"
         )
 
         # Per-subject breakdown
@@ -521,9 +571,7 @@ def eval_report(result_file: str) -> None:
     console.print(f"  [cyan]Total:[/cyan]     {len(records)}")
     console.print(f"  [cyan]Scored:[/cyan]    {len(scored)}")
     console.print(f"  [cyan]Correct:[/cyan]   {len(correct)}")
-    console.print(
-        f"  [cyan]Accuracy:[/cyan]  [bold]{accuracy:.4f}[/bold]"
-    )
+    console.print(f"  [cyan]Accuracy:[/cyan]  [bold]{accuracy:.4f}[/bold]")
     console.print(f"  [cyan]Errors:[/cyan]    {len(errors)}")
 
 

src/openjarvis/cli/feedback_cmd.py

@@ -18,7 +18,10 @@ def feedback_group() -> None:
 @feedback_group.command("score")
 @click.argument("trace_id")
 @click.option(
-    "-s", "--score", type=float, required=True,
+    "-s",
+    "--score",
+    type=float,
+    required=True,
     help="Feedback score (0.0-1.0).",
 )
 def feedback_score(trace_id: str, score: float) -> None:
@@ -43,13 +46,9 @@ def feedback_score(trace_id: str, score: float) -> None:
         store.close()
 
         if updated:
-            console.print(
-                f"[green]Recorded score {score} for trace {trace_id}[/green]"
-            )
+            console.print(f"[green]Recorded score {score} for trace {trace_id}[/green]")
         else:
-            console.print(
-                f"[yellow]Trace '{trace_id}' not found.[/yellow]"
-            )
+            console.print(f"[yellow]Trace '{trace_id}' not found.[/yellow]")
     except Exception as exc:
         console.print(f"[red]Error: {exc}[/red]")
         sys.exit(1)
@@ -57,16 +56,22 @@ def feedback_score(trace_id: str, score: float) -> None:
 
 @feedback_group.command("thumbs")
 @click.option(
-    "--last", is_flag=True, default=False,
+    "--last",
+    is_flag=True,
+    default=False,
     help="Rate the last interaction.",
 )
 @click.option(
-    "--up/--down", "thumbs_up", default=True,
+    "--up/--down",
+    "thumbs_up",
+    default=True,
     help="Thumbs up or down.",
 )
 @click.argument("trace_id", required=False)
 def feedback_thumbs(
-    last: bool, thumbs_up: bool, trace_id: Optional[str],
+    last: bool,
+    thumbs_up: bool,
+    trace_id: Optional[str],
 ) -> None:
     """Rate a trace with thumbs up/down."""
     console = Console()
@@ -97,13 +102,9 @@ def feedback_thumbs(
 
         label = "thumbs up" if thumbs_up else "thumbs down"
         if updated:
-            console.print(
-                f"[green]Recorded {label} for trace {trace_id}[/green]"
-            )
+            console.print(f"[green]Recorded {label} for trace {trace_id}[/green]")
         else:
-            console.print(
-                f"[yellow]Trace '{trace_id}' not found.[/yellow]"
-            )
+            console.print(f"[yellow]Trace '{trace_id}' not found.[/yellow]")
     except Exception as exc:
         console.print(f"[red]Error: {exc}[/red]")
         sys.exit(1)
@@ -111,7 +112,9 @@ def feedback_thumbs(
 
 @feedback_group.command("evaluate")
 @click.option(
-    "--since", type=str, default="7d",
+    "--since",
+    type=str,
+    default="7d",
     help="Evaluate traces since (e.g. 7d, 24h).",
 )
 def feedback_evaluate(since: str) -> None:
@@ -125,15 +128,11 @@ def feedback_evaluate(since: str) -> None:
         value = float(since[:-1])
         seconds = value * multipliers.get(unit, 86400)
     except (ValueError, IndexError):
-        console.print(
-            f"[red]Invalid duration '{since}'. Use e.g. 7d, 24h, 30m.[/red]"
-        )
+        console.print(f"[red]Invalid duration '{since}'. Use e.g. 7d, 24h, 30m.[/red]")
         sys.exit(1)
 
     since_ts = time.time() - seconds
-    console.print(
-        f"[cyan]Evaluating traces from the last {since}...[/cyan]"
-    )
+    console.print(f"[cyan]Evaluating traces from the last {since}...[/cyan]")
 
     try:
         from openjarvis.core.config import DEFAULT_CONFIG_DIR
@@ -153,8 +152,7 @@ def feedback_evaluate(since: str) -> None:
             return
 
         console.print(
-            "[yellow]LLM judge evaluation is not yet "
-            "fully implemented.[/yellow]"
+            "[yellow]LLM judge evaluation is not yet fully implemented.[/yellow]"
         )
     except Exception as exc:
         console.print(f"[red]Error: {exc}[/red]")
@@ -183,9 +181,7 @@ def feedback_stats() -> None:
         total = len(all_traces)
         scored_count = len(scored)
         mean_score = (
-            sum(t.feedback for t in scored) / scored_count
-            if scored_count > 0
-            else 0.0
+            sum(t.feedback for t in scored) / scored_count if scored_count > 0 else 0.0
         )
         positive = sum(1 for t in scored if t.feedback >= 0.5)
 

src/openjarvis/cli/gateway_cmd.py

@@ -31,27 +31,26 @@ def start(install: bool) -> None:
 
         if plat.system() == "Darwin":
             plist_path = (
-                Path.home()
-                / "Library/LaunchAgents/com.openjarvis.gateway.plist"
+                Path.home() / "Library/LaunchAgents/com.openjarvis.gateway.plist"
             )
             generate_launchd_plist(plist_path)
             click.echo(f"Wrote {plist_path}")
             subprocess.run(
-                ["launchctl", "load", str(plist_path)], check=False,
+                ["launchctl", "load", str(plist_path)],
+                check=False,
             )
         else:
             service_path = (
-                Path.home()
-                / ".config/systemd/user/openjarvis-gateway.service"
+                Path.home() / ".config/systemd/user/openjarvis-gateway.service"
             )
             generate_systemd_service(service_path)
             click.echo(f"Wrote {service_path}")
             subprocess.run(
-                ["systemctl", "--user", "daemon-reload"], check=False,
+                ["systemctl", "--user", "daemon-reload"],
+                check=False,
             )
             subprocess.run(
-                ["systemctl", "--user", "enable", "--now",
-                 "openjarvis-gateway"],
+                ["systemctl", "--user", "enable", "--now", "openjarvis-gateway"],
                 check=False,
             )
     else:

src/openjarvis/cli/host_cmd.py

@@ -136,9 +136,7 @@ def _install_backend(backend: str, console: Console) -> bool:
     display = info["display"]
 
     console.print()
-    console.print(
-        f"[yellow]Backend [bold]{display}[/bold] is not installed.[/yellow]"
-    )
+    console.print(f"[yellow]Backend [bold]{display}[/bold] is not installed.[/yellow]")
 
     uv_available = shutil.which("uv") is not None
     in_uv_project = os.path.exists("pyproject.toml") and os.path.exists("uv.lock")
@@ -168,9 +166,7 @@ def _install_backend(backend: str, console: Console) -> bool:
     console.print(f"[bold]Running:[/bold] {install_label}")
     result = subprocess.run(install_cmd)
     if result.returncode != 0:
-        console.print(
-            f"[red]Installation failed (exit {result.returncode}).[/red]"
-        )
+        console.print(f"[red]Installation failed (exit {result.returncode}).[/red]")
         return False
 
     console.print(f"[green]{display} installed successfully.[/green]\n")
@@ -208,11 +204,7 @@ def _install_binary_backend(backend: str, console: Console) -> bool:
             "  Or from source:\n"
             "    https://github.com/exo-explore/exo"
         ),
-        "uzu": (
-            "Install Uzu:\n"
-            "\n"
-            "  See https://uzu.ai for installation instructions."
-        ),
+        "uzu": ("Install Uzu:\n\n  See https://uzu.ai for installation instructions."),
     }
 
     console.print()
@@ -241,8 +233,7 @@ def _install_binary_backend(backend: str, console: Console) -> bool:
                     console.print("[green]Ollama installed successfully.[/green]\n")
                     return True
                 console.print(
-                    "[red]Installation may have failed. "
-                    "Check above for errors.[/red]"
+                    "[red]Installation may have failed. Check above for errors.[/red]"
                 )
                 return False
 
@@ -340,9 +331,7 @@ def host(
             raise SystemExit(1)
         backend = detected
         name = _BACKENDS[backend]["display"]
-        console.print(
-            f"Auto-detected backend: [bold cyan]{name}[/bold cyan]"
-        )
+        console.print(f"Auto-detected backend: [bold cyan]{name}[/bold cyan]")
 
     info = _BACKENDS[backend]
 
@@ -381,12 +370,9 @@ def host(
     console.print()
 
     if backend != "ollama":
+        console.print(f"[dim]The model server will be available at {host_url}[/dim]")
         console.print(
-            f"[dim]The model server will be available at {host_url}[/dim]"
-        )
-        console.print(
-            "[dim]OpenJarvis will auto-discover it. "
-            "Press Ctrl+C to stop.[/dim]\n"
+            "[dim]OpenJarvis will auto-discover it. Press Ctrl+C to stop.[/dim]\n"
         )
 
     try:

src/openjarvis/cli/log_config.py

@@ -58,12 +58,12 @@ def setup_logging(
             log_dir.mkdir(parents=True, exist_ok=True)
             log_file = log_dir / "cli.log"
         file_handler = RotatingFileHandler(
-            str(log_file), maxBytes=5 * 1024 * 1024, backupCount=3,
+            str(log_file),
+            maxBytes=5 * 1024 * 1024,
+            backupCount=3,
         )
         file_handler.setLevel(logging.DEBUG)
-        file_fmt = logging.Formatter(
-            "%(asctime)s %(levelname)s %(name)s: %(message)s"
-        )
+        file_fmt = logging.Formatter("%(asctime)s %(levelname)s %(name)s: %(message)s")
         file_handler.setFormatter(file_fmt)
         logger.addHandler(file_handler)
 

src/openjarvis/cli/memory_cmd.py

@@ -43,15 +43,21 @@ def memory() -> None:
 @memory.command()
 @click.argument("path")
 @click.option(
-    "--backend", "-b", default=None,
+    "--backend",
+    "-b",
+    default=None,
     help="Override the default memory backend.",
 )
 @click.option(
-    "--chunk-size", default=512, type=int,
+    "--chunk-size",
+    default=512,
+    type=int,
     help="Chunk size in tokens.",
 )
 @click.option(
-    "--chunk-overlap", default=64, type=int,
+    "--chunk-overlap",
+    default=64,
+    type=int,
     help="Overlap between chunks in tokens.",
 )
 def index(
@@ -108,11 +114,16 @@ def index(
 @memory.command()
 @click.argument("query", nargs=-1, required=True)
 @click.option(
-    "--top-k", "-k", default=5, type=int,
+    "--top-k",
+    "-k",
+    default=5,
+    type=int,
     help="Number of results to return.",
 )
 @click.option(
-    "--backend", "-b", default=None,
+    "--backend",
+    "-b",
+    default=None,
     help="Override the default memory backend.",
 )
 def search(
@@ -158,7 +169,9 @@ def search(
 
 @memory.command()
 @click.option(
-    "--backend", "-b", default=None,
+    "--backend",
+    "-b",
+    default=None,
     help="Override the default memory backend.",
 )
 def stats(backend: str | None) -> None:

src/openjarvis/cli/model.py

@@ -97,15 +97,11 @@ def info(model_name: str) -> None:
     spec = ModelRegistry.get(model_name)
     params = f"{spec.parameter_count_b}B" if spec.parameter_count_b else "unknown"
     active = (
-        f"{spec.active_parameter_count_b}B"
-        if spec.active_parameter_count_b
-        else "-"
+        f"{spec.active_parameter_count_b}B" if spec.active_parameter_count_b else "-"
     )
     ctx_len = f"{spec.context_length:,}" if spec.context_length else "unknown"
     vram = f"{spec.min_vram_gb}GB" if spec.min_vram_gb else "-"
-    engines_str = (
-        ", ".join(spec.supported_engines) if spec.supported_engines else "-"
-    )
+    engines_str = ", ".join(spec.supported_engines) if spec.supported_engines else "-"
     provider = spec.provider or "-"
     api_key = "required" if spec.requires_api_key else "not required"
     lines = [
@@ -163,6 +159,7 @@ def ollama_pull(host: str, model_name: str, console: Console) -> bool:
         ) as resp:
             resp.raise_for_status()
             import json
+
             for line in resp.iter_lines():
                 if not line.strip():
                     continue
@@ -219,9 +216,7 @@ def hf_download(repo: str, filename: str | None, console: Console) -> bool:
 
 @model.command()
 @click.argument("model_name")
-@click.option(
-    "--engine", default=None, help="Engine to download for."
-)
+@click.option("--engine", default=None, help="Engine to download for.")
 def pull(model_name: str, engine: str | None) -> None:
     """Download a model."""
     console = Console()

src/openjarvis/cli/operators_cmd.py

@@ -29,10 +29,10 @@ def list_operators() -> None:
         from openjarvis.operators.loader import load_operator
 
         config = load_config()
-        manifests_dir = Path(
-            config.operators.manifests_dir
-        ).expanduser() if hasattr(config, "operators") else (
-            DEFAULT_CONFIG_DIR / "operators"
+        manifests_dir = (
+            Path(config.operators.manifests_dir).expanduser()
+            if hasattr(config, "operators")
+            else (DEFAULT_CONFIG_DIR / "operators")
         )
 
         # Also check project-local operators/ directory
@@ -55,8 +55,7 @@ def list_operators() -> None:
         if not found:
             console.print("[dim]No operators discovered.[/dim]")
             console.print(
-                f"[dim]Place TOML manifests in {manifests_dir} "
-                f"or ./operators/[/dim]"
+                f"[dim]Place TOML manifests in {manifests_dir} or ./operators/[/dim]"
             )
             return
 
@@ -189,6 +188,7 @@ def logs(operator_id: str, lines: int) -> None:
         db_path = config.scheduler.db_path
         if not db_path:
             from openjarvis.core.config import DEFAULT_CONFIG_DIR
+
             db_path = str(DEFAULT_CONFIG_DIR / "scheduler.db")
 
         store = SchedulerStore(db_path=db_path)

src/openjarvis/cli/optimize_cmd.py

@@ -18,27 +18,43 @@ def optimize_group() -> None:
 
 @optimize_group.command("run")
 @click.option(
-    "-c", "--config", "config_path", type=str, default=None,
+    "-c",
+    "--config",
+    "config_path",
+    type=str,
+    default=None,
     help="TOML config file for the optimization run.",
 )
 @click.option(
-    "-b", "--benchmark", type=str, default=None,
+    "-b",
+    "--benchmark",
+    type=str,
+    default=None,
     help="Benchmark name (e.g. supergpqa, mmlu-pro).",
 )
 @click.option(
-    "-t", "--trials", type=int, default=20,
+    "-t",
+    "--trials",
+    type=int,
+    default=20,
     help="Maximum number of trials.",
 )
 @click.option(
-    "--optimizer-model", type=str, default="claude-sonnet-4-6",
+    "--optimizer-model",
+    type=str,
+    default="claude-sonnet-4-6",
     help="Model used by the LLM optimizer.",
 )
 @click.option(
-    "--max-samples", type=int, default=50,
+    "--max-samples",
+    type=int,
+    default=50,
     help="Maximum samples per trial evaluation.",
 )
 @click.option(
-    "--output-dir", type=str, default="results/optimize/",
+    "--output-dir",
+    type=str,
+    default="results/optimize/",
     help="Directory for trial output files.",
 )
 def optimize_run(
@@ -58,9 +74,7 @@ def optimize_run(
         try:
             from openjarvis.learning.optimize.config import load_optimize_config
         except ImportError:
-            console.print(
-                "[red]Optimization framework not available.[/red]"
-            )
+            console.print("[red]Optimization framework not available.[/red]")
             sys.exit(1)
 
         try:
@@ -167,7 +181,8 @@ def optimize_run(
         early_stop = 5
         if data is not None:
             early_stop = data.get("optimize", {}).get(
-                "early_stop_patience", early_stop,
+                "early_stop_patience",
+                early_stop,
             )
 
         engine = OptimizationEngine(
@@ -200,9 +215,7 @@ def optimize_run(
                 f"(accuracy={run.best_trial.accuracy:.4f})"
             )
     except ImportError as exc:
-        console.print(
-            f"[red]Missing dependency for optimization: {exc}[/red]"
-        )
+        console.print(f"[red]Missing dependency for optimization: {exc}[/red]")
         sys.exit(1)
     except Exception as exc:
         console.print(f"[red]Optimization failed: {exc}[/red]")
@@ -321,7 +334,10 @@ def optimize_results(run_id: str) -> None:
 @optimize_group.command("best")
 @click.argument("run_id")
 @click.option(
-    "-o", "--output", type=str, default=None,
+    "-o",
+    "--output",
+    type=str,
+    default=None,
     help="Output recipe path (TOML).",
 )
 def optimize_best(run_id: str, output: Optional[str]) -> None:
@@ -350,15 +366,11 @@ def optimize_best(run_id: str, output: Optional[str]) -> None:
             console.print("[yellow]No best trial found in this run.[/yellow]")
             return
 
-        output_path = Path(
-            output or f"results/optimize/best_{run_id}.toml"
-        )
+        output_path = Path(output or f"results/optimize/best_{run_id}.toml")
         engine = OptimizationEngine.__new__(OptimizationEngine)
         engine.export_best_recipe(run, output_path)
 
-        console.print(
-            f"[green]Best recipe exported to:[/green] {output_path}"
-        )
+        console.print(f"[green]Best recipe exported to:[/green] {output_path}")
         console.print(
             f"  Trial: {run.best_trial.trial_id} "
             f"(accuracy={run.best_trial.accuracy:.4f})"
@@ -370,11 +382,16 @@ def optimize_best(run_id: str, output: Optional[str]) -> None:
 @optimize_group.command("personal")
 @click.argument("action", type=click.Choice(["synthesize", "run"]))
 @click.option(
-    "--workflow", type=str, default="default",
+    "--workflow",
+    type=str,
+    default="default",
     help="Workflow ID for personal optimization.",
 )
 @click.option(
-    "-t", "--trials", type=int, default=10,
+    "-t",
+    "--trials",
+    type=int,
+    default=10,
     help="Maximum trials for personal optimization.",
 )
 def optimize_personal(action: str, workflow: str, trials: int) -> None:
@@ -396,8 +413,7 @@ def optimize_personal(action: str, workflow: str, trials: int) -> None:
             f"workflow '{workflow}' (max {trials} trials)...[/cyan]"
         )
         console.print(
-            "[yellow]Personal optimization is not yet "
-            "fully implemented.[/yellow]"
+            "[yellow]Personal optimization is not yet fully implemented.[/yellow]"
         )
 
 

src/openjarvis/cli/scheduler_cmd.py

@@ -17,9 +17,9 @@ def _get_store() -> "SchedulerStore":  # noqa: F821
     from openjarvis.scheduler.store import SchedulerStore
 
     config = load_config()
-    db_path = getattr(
-        getattr(config, "scheduler", None), "db_path", None
-    ) or str(DEFAULT_CONFIG_DIR / "scheduler.db")
+    db_path = getattr(getattr(config, "scheduler", None), "db_path", None) or str(
+        DEFAULT_CONFIG_DIR / "scheduler.db"
+    )
     return SchedulerStore(db_path)
 
 
@@ -38,13 +38,15 @@ def scheduler() -> None:
 @scheduler.command("create")
 @click.argument("prompt")
 @click.option(
-    "--type", "schedule_type",
+    "--type",
+    "schedule_type",
     required=True,
     type=click.Choice(["cron", "interval", "once"]),
     help="Schedule type.",
 )
 @click.option(
-    "--value", "schedule_value",
+    "--value",
+    "schedule_value",
     required=True,
     help="Schedule value (cron expr, seconds, or ISO datetime).",
 )
@@ -82,7 +84,8 @@ def scheduler_create(
 
 @scheduler.command("list")
 @click.option(
-    "--status", default=None,
+    "--status",
+    default=None,
     type=click.Choice(["active", "paused", "completed", "cancelled"]),
     help="Filter by status.",
 )
@@ -197,14 +200,10 @@ def scheduler_logs(task_id: str, limit: int) -> None:
         table.add_column("Error", max_width=30)
 
         for log in logs:
-            success_str = (
-                "[green]yes[/green]" if log["success"] else "[red]no[/red]"
-            )
+            success_str = "[green]yes[/green]" if log["success"] else "[red]no[/red]"
             result_text = log["result"]
             result_short = (
-                (result_text[:37] + "...")
-                if len(result_text) > 40
-                else result_text
+                (result_text[:37] + "...") if len(result_text) > 40 else result_text
             )
             table.add_row(
                 str(log["id"]),
@@ -221,7 +220,9 @@ def scheduler_logs(task_id: str, limit: int) -> None:
 
 @scheduler.command("start")
 @click.option(
-    "--poll-interval", default=60, type=int,
+    "--poll-interval",
+    default=60,
+    type=int,
     help="Seconds between poll cycles.",
 )
 def scheduler_start(poll_interval: int) -> None:

src/openjarvis/cli/serve.py

@@ -26,13 +26,18 @@ logger = logging.getLogger(__name__)
 @click.command()
 @click.option("--host", default=None, help="Bind address (default: config).")
 @click.option(
-    "--port", default=None, type=int,
+    "--port",
+    default=None,
+    type=int,
     help="Port number (default: config).",
 )
 @click.option("-e", "--engine", "engine_key", default=None, help="Engine backend.")
 @click.option("-m", "--model", "model_name", default=None, help="Default model.")
 @click.option(
-    "-a", "--agent", "agent_name", default=None,
+    "-a",
+    "--agent",
+    "agent_name",
+    default=None,
     help="Agent for non-streaming requests (simple, orchestrator, react, openhands).",
 )
 def serve(
@@ -94,12 +99,14 @@ def serve(
 
     # Apply security guardrails
     from openjarvis.security import setup_security
+
     sec = setup_security(config, engine, bus)
     engine = sec.engine
 
     # If cloud API keys are set, wrap with MultiEngine so both local
     # and cloud models appear in the model list and can be used.
     import os
+
     _has_cloud = (
         os.environ.get("OPENAI_API_KEY")
         or os.environ.get("ANTHROPIC_API_KEY")
@@ -183,13 +190,13 @@ def serve(
                     if configured:
                         if isinstance(configured, list):
                             allowed = {
-                                t.strip() for t in configured
+                                t.strip()
+                                for t in configured
                                 if isinstance(t, str) and t.strip()
                             }
                         else:
                             allowed = {
-                                t.strip() for t in configured.split(",")
-                                if t.strip()
+                                t.strip() for t in configured.split(",") if t.strip()
                             }
                     else:
                         allowed = _DEFAULT_TOOLS
@@ -214,6 +221,7 @@ def serve(
                 agent = agent_cls(engine, model_name, **agent_kwargs)
         except Exception as exc:
             import traceback
+
             console.print(f"[yellow]Agent '{agent_key}' failed to load: {exc}[/yellow]")
             traceback.print_exc()
 
@@ -254,6 +262,7 @@ def serve(
     speech_backend = None
     try:
         from openjarvis.speech._discovery import get_speech_backend
+
         speech_backend = get_speech_backend(config)
         if speech_backend:
             console.print(f"  Speech: [cyan]{speech_backend.backend_id}[/cyan]")
@@ -287,6 +296,7 @@ def serve(
 
             executor = AgentExecutor(manager=agent_manager, event_bus=bus)
             from openjarvis.system import SystemBuilder
+
             system = SystemBuilder(config).build()
             executor.set_system(system)
 
@@ -298,7 +308,8 @@ def serve(
             for ag in agent_manager.list_agents():
                 sched_type = ag.get("config", {}).get("schedule_type", "manual")
                 if sched_type in ("cron", "interval") and ag["status"] not in (
-                    "archived", "error",
+                    "archived",
+                    "error",
                 ):
                     agent_scheduler.register_agent(ag["id"])
             agent_scheduler.start()
@@ -316,7 +327,8 @@ def serve(
             mem_key = config.memory.default_backend
             if MemoryRegistry.contains(mem_key):
                 memory_backend = MemoryRegistry.create(
-                    mem_key, db_path=config.memory.db_path,
+                    mem_key,
+                    db_path=config.memory.db_path,
                 )
                 console.print("  Memory:    [cyan]active[/cyan]")
         except Exception as exc:
@@ -329,33 +341,21 @@ def serve(
     if not api_key:
         try:
             import tomllib
+
             _cfg_path = str(
-                __import__("pathlib").Path.home()
-                / ".openjarvis" / "config.toml"
+                __import__("pathlib").Path.home() / ".openjarvis" / "config.toml"
             )
             with open(_cfg_path, "rb") as _f:
                 _raw = tomllib.load(_f)
-            api_key = (
-                _raw.get("server", {})
-                .get("auth", {})
-                .get("api_key", "")
-            )
+            api_key = _raw.get("server", {}).get("auth", {}).get("api_key", "")
         except (FileNotFoundError, ImportError):
             pass
 
     webhook_config = {
-        "twilio_auth_token": _os.environ.get(
-            "TWILIO_AUTH_TOKEN", ""
-        ),
-        "bluebubbles_password": _os.environ.get(
-            "BLUEBUBBLES_PASSWORD", ""
-        ),
-        "whatsapp_verify_token": _os.environ.get(
-            "WHATSAPP_VERIFY_TOKEN", ""
-        ),
-        "whatsapp_app_secret": _os.environ.get(
-            "WHATSAPP_APP_SECRET", ""
-        ),
+        "twilio_auth_token": _os.environ.get("TWILIO_AUTH_TOKEN", ""),
+        "bluebubbles_password": _os.environ.get("BLUEBUBBLES_PASSWORD", ""),
+        "whatsapp_verify_token": _os.environ.get("WHATSAPP_VERIFY_TOKEN", ""),
+        "whatsapp_app_secret": _os.environ.get("WHATSAPP_APP_SECRET", ""),
     }
 
     # Wrap existing channel in ChannelBridge orchestrator
@@ -369,9 +369,7 @@ def serve(
             )
 
             session_store = SessionStore()
-            channels = {
-                channel_bridge.channel_id: channel_bridge
-            }
+            channels = {channel_bridge.channel_id: channel_bridge}
             channel_bridge = ChannelBridge(
                 channels=channels,
                 session_store=session_store,
@@ -380,14 +378,17 @@ def serve(
                 agent_manager=agent_manager,
             )
         except Exception as exc:
-            logger.debug(
-                "ChannelBridge init skipped: %s", exc
-            )
+            logger.debug("ChannelBridge init skipped: %s", exc)
 
     app = create_app(
-        engine, model_name, agent=agent, bus=bus,
-        engine_name=engine_name, agent_name=agent_key or "",
-        channel_bridge=channel_bridge, config=config,
+        engine,
+        model_name,
+        agent=agent,
+        bus=bus,
+        engine_name=engine_name,
+        agent_name=agent_key or "",
+        channel_bridge=channel_bridge,
+        config=config,
         memory_backend=memory_backend,
         speech_backend=speech_backend,
         agent_manager=agent_manager,
@@ -405,4 +406,5 @@ def serve(
     )
 
     import uvicorn
+
     uvicorn.run(app, host=bind_host, port=bind_port, log_level="info")

src/openjarvis/cli/telemetry_cmd.py

@@ -27,7 +27,11 @@ def telemetry() -> None:
 
 @telemetry.command()
 @click.option(
-    "-n", "--top", "top_n", default=10, type=int,
+    "-n",
+    "--top",
+    "top_n",
+    default=10,
+    type=int,
     help="Number of top models to show.",
 )
 def stats(top_n: int) -> None:
@@ -76,13 +80,9 @@ def stats(top_n: int) -> None:
         # Per-model table
         if summary.per_model:
             has_energy = any(
-                ms.total_energy_joules > 0
-                for ms in summary.per_model[:top_n]
-            )
-            has_itl = any(
-                ms.avg_mean_itl_ms > 0
-                for ms in summary.per_model[:top_n]
+                ms.total_energy_joules > 0 for ms in summary.per_model[:top_n]
             )
+            has_itl = any(ms.avg_mean_itl_ms > 0 for ms in summary.per_model[:top_n])
             model_table = Table(title=f"Top {top_n} Models")
             model_table.add_column("Model", style="cyan")
             model_table.add_column("Calls", justify="right")
@@ -121,13 +121,9 @@ def stats(top_n: int) -> None:
         # Per-engine table
         if summary.per_engine:
             has_engine_energy = any(
-                es.total_energy_joules > 0
-                for es in summary.per_engine
-            )
-            has_engine_itl = any(
-                es.avg_mean_itl_ms > 0
-                for es in summary.per_engine
+                es.total_energy_joules > 0 for es in summary.per_engine
             )
+            has_engine_itl = any(es.avg_mean_itl_ms > 0 for es in summary.per_engine)
             engine_table = Table(title="Engines")
             engine_table.add_column("Engine", style="cyan")
             engine_table.add_column("Calls", justify="right")
@@ -171,11 +167,19 @@ def stats(top_n: int) -> None:
 
 @telemetry.command()
 @click.option(
-    "-f", "--format", "fmt", default="json", type=click.Choice(["json", "csv"]),
+    "-f",
+    "--format",
+    "fmt",
+    default="json",
+    type=click.Choice(["json", "csv"]),
     help="Output format.",
 )
 @click.option(
-    "-o", "--output", "output_path", default=None, type=click.Path(),
+    "-o",
+    "--output",
+    "output_path",
+    default=None,
+    type=click.Path(),
     help="Output file path (default: stdout).",
 )
 def export(fmt: str, output_path: str | None) -> None:
@@ -207,7 +211,10 @@ def export(fmt: str, output_path: str | None) -> None:
 
 @telemetry.command()
 @click.option(
-    "-y", "--yes", "confirmed", is_flag=True,
+    "-y",
+    "--yes",
+    "confirmed",
+    is_flag=True,
     help="Skip confirmation prompt.",
 )
 def clear(confirmed: bool) -> None:

src/openjarvis/cli/tunnel_cmd.py

@@ -12,9 +12,7 @@ from openjarvis.core.config import DEFAULT_CONFIG_PATH
 
 
 @click.group("tunnel", invoke_without_command=True)
-@click.option(
-    "--port", default=8000, help="Local port to tunnel."
-)
+@click.option("--port", default=8000, help="Local port to tunnel.")
 @click.pass_context
 def tunnel(ctx: click.Context, port: int) -> None:
     """Start a Cloudflare tunnel or manage config."""
@@ -31,10 +29,7 @@ def tunnel(ctx: click.Context, port: int) -> None:
         )
         sys.exit(1)
 
-    click.echo(
-        f"Starting Cloudflare tunnel "
-        f"to localhost:{port}..."
-    )
+    click.echo(f"Starting Cloudflare tunnel to localhost:{port}...")
     click.echo("Press Ctrl+C to stop.\n")
 
     try:
@@ -66,10 +61,7 @@ def status() -> None:
     if "public_url" in content:
         for line in content.splitlines():
             if "public_url" in line:
-                click.echo(
-                    "Configured tunnel URL: "
-                    f"{line.split('=', 1)[1].strip()}"
-                )
+                click.echo(f"Configured tunnel URL: {line.split('=', 1)[1].strip()}")
                 return
     click.echo("No tunnel URL configured.")
 

src/openjarvis/cli/vault_cmd.py

@@ -21,8 +21,7 @@ def _get_or_create_key() -> bytes:
         from cryptography.fernet import Fernet
     except ImportError:
         raise ImportError(
-            "cryptography not installed. Install with: "
-            "uv sync --extra security-signing"
+            "cryptography not installed. Install with: uv sync --extra security-signing"
         )
 
     if _VAULT_KEY_FILE.exists():
@@ -41,6 +40,7 @@ def _load_vault() -> dict:
         return {}
     try:
         from cryptography.fernet import Fernet
+
         key = _get_or_create_key()
         f = Fernet(key)
         encrypted = _VAULT_FILE.read_bytes()
@@ -53,6 +53,7 @@ def _load_vault() -> dict:
 def _save_vault(data: dict) -> None:
     """Encrypt and save vault contents."""
     from cryptography.fernet import Fernet
+
     key = _get_or_create_key()
     f = Fernet(key)
     plaintext = json.dumps(data).encode()

src/openjarvis/cli/workflow_cmd.py

@@ -52,8 +52,7 @@ def run(workflow_name: str, input_text: str | None) -> None:
         console.print(f"[green]Workflow '{workflow_name}' started.[/green]")
         # Full execution would need a JarvisSystem — just report for now
         console.print(
-            "[dim]Note: Full workflow execution"
-            " requires a running system.[/dim]"
+            "[dim]Note: Full workflow execution requires a running system.[/dim]"
         )
     except ImportError:
         console.print("[red]Workflow system not available.[/red]")

src/openjarvis/connectors/dropbox.py

@@ -26,9 +26,7 @@ _DROPBOX_API_BASE = "https://api.dropboxapi.com/2"
 _DROPBOX_CONTENT_BASE = "https://content.dropboxapi.com/2"
 _DROPBOX_AUTH_URL = "https://www.dropbox.com/oauth2/authorize"
 _DROPBOX_SCOPES = ["files.metadata.read", "files.content.read"]
-_DEFAULT_CREDENTIALS_PATH = str(
-    DEFAULT_CONFIG_DIR / "connectors" / "dropbox.json"
-)
+_DEFAULT_CREDENTIALS_PATH = str(DEFAULT_CONFIG_DIR / "connectors" / "dropbox.json")
 
 # File extensions whose content can be downloaded and stored as text
 _TEXT_EXTENSIONS = {
@@ -231,9 +229,7 @@ class DropboxConnector(BaseConnector):
         entries_seen: int = 0
 
         while True:
-            list_resp = _dropbox_api_list_folder(
-                token, path="", cursor=list_cursor
-            )
+            list_resp = _dropbox_api_list_folder(token, path="", cursor=list_cursor)
             entries: List[Dict[str, Any]] = list_resp.get("entries", [])
             entries_seen += len(entries)
 

src/openjarvis/connectors/granola.py

@@ -26,9 +26,7 @@ from openjarvis.tools._stubs import ToolSpec
 # ---------------------------------------------------------------------------
 
 _GRANOLA_API_BASE = "https://public-api.granola.ai"
-_DEFAULT_CREDENTIALS_PATH = str(
-    DEFAULT_CONFIG_DIR / "connectors" / "granola.json"
-)
+_DEFAULT_CREDENTIALS_PATH = str(DEFAULT_CONFIG_DIR / "connectors" / "granola.json")
 
 # ---------------------------------------------------------------------------
 # Module-level API functions (easy to patch in tests)
@@ -122,9 +120,7 @@ def _format_note_content(note: Dict[str, Any]) -> str:
     parts: List[str] = []
 
     # Summary section
-    summary_markdown: str = (
-        note.get("summary", {}) or {}
-    ).get("markdown", "")
+    summary_markdown: str = (note.get("summary", {}) or {}).get("markdown", "")
     parts.append("## Summary")
     parts.append(summary_markdown)
 

src/openjarvis/connectors/notion.py

@@ -27,9 +27,7 @@ from openjarvis.tools._stubs import ToolSpec
 
 _NOTION_API_BASE = "https://api.notion.com/v1"
 _NOTION_VERSION = "2022-06-28"
-_DEFAULT_CREDENTIALS_PATH = str(
-    DEFAULT_CONFIG_DIR / "connectors" / "notion.json"
-)
+_DEFAULT_CREDENTIALS_PATH = str(DEFAULT_CONFIG_DIR / "connectors" / "notion.json")
 
 # ---------------------------------------------------------------------------
 # Module-level API functions (easy to patch in tests)

src/openjarvis/connectors/outlook.py

@@ -17,9 +17,7 @@ from openjarvis.connectors.gmail_imap import GmailIMAPConnector
 from openjarvis.core.config import DEFAULT_CONFIG_DIR
 from openjarvis.core.registry import ConnectorRegistry
 
-_DEFAULT_CREDENTIALS_PATH = str(
-    DEFAULT_CONFIG_DIR / "connectors" / "outlook.json"
-)
+_DEFAULT_CREDENTIALS_PATH = str(DEFAULT_CONFIG_DIR / "connectors" / "outlook.json")
 
 
 @ConnectorRegistry.register("outlook")

src/openjarvis/connectors/slack_connector.py

@@ -26,9 +26,7 @@ from openjarvis.tools._stubs import ToolSpec
 _SLACK_API_BASE = "https://slack.com/api"
 _SLACK_AUTH_ENDPOINT = "https://slack.com/oauth/v2/authorize"
 _SLACK_SCOPES = "channels:history,channels:read,users:read"
-_DEFAULT_CREDENTIALS_PATH = str(
-    DEFAULT_CONFIG_DIR / "connectors" / "slack.json"
-)
+_DEFAULT_CREDENTIALS_PATH = str(DEFAULT_CONFIG_DIR / "connectors" / "slack.json")
 
 # ---------------------------------------------------------------------------
 # Module-level API functions (easy to patch in tests)
@@ -263,9 +261,7 @@ class SlackConnector(BaseConnector):
 
         # Step 2: paginate through channels
         while True:
-            channels_resp = _slack_api_conversations_list(
-                token, cursor=channels_cursor
-            )
+            channels_resp = _slack_api_conversations_list(token, cursor=channels_cursor)
             channels: List[Dict[str, Any]] = channels_resp.get("channels", [])
 
             for channel in channels:
@@ -280,9 +276,7 @@ class SlackConnector(BaseConnector):
                     history_resp = _slack_api_conversations_history(
                         token, chan_id, cursor=history_cursor
                     )
-                    messages: List[Dict[str, Any]] = history_resp.get(
-                        "messages", []
-                    )
+                    messages: List[Dict[str, Any]] = history_resp.get("messages", [])
 
                     for msg in messages:
                         # Skip bot messages and non-content subtypes
@@ -327,9 +321,7 @@ class SlackConnector(BaseConnector):
                         yield doc
 
                     next_history_cursor: str = (
-                        history_resp.get("response_metadata", {}).get(
-                            "next_cursor", ""
-                        )
+                        history_resp.get("response_metadata", {}).get("next_cursor", "")
                         or ""
                     )
                     if not history_resp.get("has_more") or not next_history_cursor:
@@ -337,8 +329,7 @@ class SlackConnector(BaseConnector):
                     history_cursor = next_history_cursor
 
             next_channels_cursor: str = (
-                channels_resp.get("response_metadata", {}).get("next_cursor", "")
-                or ""
+                channels_resp.get("response_metadata", {}).get("next_cursor", "") or ""
             )
             if not next_channels_cursor:
                 self._last_cursor = None

src/openjarvis/core/credentials.py

@@ -3,6 +3,7 @@
 Stores credentials in ~/.openjarvis/credentials.toml with 0o600 permissions.
 Thread-safe writes via lock. Sets os.environ on save for immediate effect.
 """
+
 from __future__ import annotations
 
 import os
@@ -33,8 +34,10 @@ TOOL_CREDENTIALS: dict[str, list[str]] = {
     "viber": ["VIBER_AUTH_TOKEN"],
     "messenger": ["MESSENGER_PAGE_ACCESS_TOKEN", "MESSENGER_VERIFY_TOKEN"],
     "reddit": [
-        "REDDIT_CLIENT_ID", "REDDIT_CLIENT_SECRET",
-        "REDDIT_USERNAME", "REDDIT_PASSWORD",
+        "REDDIT_CLIENT_ID",
+        "REDDIT_CLIENT_SECRET",
+        "REDDIT_USERNAME",
+        "REDDIT_PASSWORD",
     ],
     "mastodon": ["MASTODON_ACCESS_TOKEN", "MASTODON_API_BASE_URL"],
     "twitch": ["TWITCH_TOKEN", "TWITCH_CHANNEL"],

src/openjarvis/daemon/session_expiry.py

@@ -26,8 +26,7 @@ class SessionExpiryHook:
         self._executor.run_ephemeral(
             agent_type="simple",
             system_prompt=(
-                "You are a memory management agent. "
-                "Save important information."
+                "You are a memory management agent. Save important information."
             ),
             input_text=input_text,
             tools=["memory_manage", "skill_manage"],

src/openjarvis/engine/apple_fm_shim.py

@@ -80,12 +80,14 @@ def health() -> JSONResponse:
 
 @app.get("/v1/models")
 def list_models() -> JSONResponse:
-    return JSONResponse({
-        "object": "list",
-        "data": [
-            {"id": MODEL_ID, "object": "model", "owned_by": "apple"},
-        ],
-    })
+    return JSONResponse(
+        {
+            "object": "list",
+            "data": [
+                {"id": MODEL_ID, "object": "model", "owned_by": "apple"},
+            ],
+        }
+    )
 
 
 @app.post("/v1/chat/completions")
@@ -96,21 +98,25 @@ async def chat_completions(
     session = apple_fm.LanguageModelSession()
 
     if req.stream:
+
         async def generate():
             cid = f"chatcmpl-{uuid.uuid4().hex[:12]}"
             async for token in session.stream_response(
-                prompt, max_tokens=req.max_tokens,
+                prompt,
+                max_tokens=req.max_tokens,
             ):
                 chunk = {
                     "id": cid,
                     "object": "chat.completion.chunk",
                     "created": int(time.time()),
                     "model": MODEL_ID,
-                    "choices": [{
-                        "index": 0,
-                        "delta": {"content": token},
-                        "finish_reason": None,
-                    }],
+                    "choices": [
+                        {
+                            "index": 0,
+                            "delta": {"content": token},
+                            "finish_reason": None,
+                        }
+                    ],
                 }
                 yield f"data: {json.dumps(chunk)}\n\n"
             final = {
@@ -118,34 +124,41 @@ async def chat_completions(
                 "object": "chat.completion.chunk",
                 "created": int(time.time()),
                 "model": MODEL_ID,
-                "choices": [{
-                    "index": 0,
-                    "delta": {},
-                    "finish_reason": "stop",
-                }],
+                "choices": [
+                    {
+                        "index": 0,
+                        "delta": {},
+                        "finish_reason": "stop",
+                    }
+                ],
             }
             yield f"data: {json.dumps(final)}\n\n"
             yield "data: [DONE]\n\n"
 
         return StreamingResponse(
-            generate(), media_type="text/event-stream",
+            generate(),
+            media_type="text/event-stream",
         )
 
     text = await session.respond(prompt, max_tokens=req.max_tokens)
     cid = f"chatcmpl-{uuid.uuid4().hex[:12]}"
-    return JSONResponse({
-        "id": cid,
-        "object": "chat.completion",
-        "created": int(time.time()),
-        "model": MODEL_ID,
-        "choices": [{
-            "index": 0,
-            "message": {"role": "assistant", "content": text},
-            "finish_reason": "stop",
-        }],
-        "usage": {
-            "prompt_tokens": 0,
-            "completion_tokens": 0,
-            "total_tokens": 0,
-        },
-    })
+    return JSONResponse(
+        {
+            "id": cid,
+            "object": "chat.completion",
+            "created": int(time.time()),
+            "model": MODEL_ID,
+            "choices": [
+                {
+                    "index": 0,
+                    "message": {"role": "assistant", "content": text},
+                    "finish_reason": "stop",
+                }
+            ],
+            "usage": {
+                "prompt_tokens": 0,
+                "completion_tokens": 0,
+                "total_tokens": 0,
+            },
+        }
+    )

src/openjarvis/engine/nexa_shim.py

@@ -81,12 +81,14 @@ def health() -> JSONResponse:
 
 @app.get("/v1/models")
 def list_models() -> JSONResponse:
-    return JSONResponse({
-        "object": "list",
-        "data": [
-            {"id": MODEL_ID, "object": "model", "owned_by": "nexa"},
-        ],
-    })
+    return JSONResponse(
+        {
+            "object": "list",
+            "data": [
+                {"id": MODEL_ID, "object": "model", "owned_by": "nexa"},
+            ],
+        }
+    )
 
 
 @app.post("/v1/chat/completions")
@@ -97,6 +99,7 @@ async def chat_completions(
     llm = _get_llm()
 
     if req.stream:
+
         async def generate():
             cid = f"chatcmpl-{uuid.uuid4().hex[:12]}"
             for token in llm.generate(prompt, max_tokens=req.max_tokens):
@@ -105,11 +108,13 @@ async def chat_completions(
                     "object": "chat.completion.chunk",
                     "created": int(time.time()),
                     "model": MODEL_ID,
-                    "choices": [{
-                        "index": 0,
-                        "delta": {"content": token},
-                        "finish_reason": None,
-                    }],
+                    "choices": [
+                        {
+                            "index": 0,
+                            "delta": {"content": token},
+                            "finish_reason": None,
+                        }
+                    ],
                 }
                 yield f"data: {json.dumps(chunk)}\n\n"
             final = {
@@ -117,36 +122,43 @@ async def chat_completions(
                 "object": "chat.completion.chunk",
                 "created": int(time.time()),
                 "model": MODEL_ID,
-                "choices": [{
-                    "index": 0,
-                    "delta": {},
-                    "finish_reason": "stop",
-                }],
+                "choices": [
+                    {
+                        "index": 0,
+                        "delta": {},
+                        "finish_reason": "stop",
+                    }
+                ],
             }
             yield f"data: {json.dumps(final)}\n\n"
             yield "data: [DONE]\n\n"
 
         return StreamingResponse(
-            generate(), media_type="text/event-stream",
+            generate(),
+            media_type="text/event-stream",
         )
 
     text = llm.generate(prompt, max_tokens=req.max_tokens)
     if isinstance(text, list):
         text = "".join(text)
     cid = f"chatcmpl-{uuid.uuid4().hex[:12]}"
-    return JSONResponse({
-        "id": cid,
-        "object": "chat.completion",
-        "created": int(time.time()),
-        "model": MODEL_ID,
-        "choices": [{
-            "index": 0,
-            "message": {"role": "assistant", "content": text},
-            "finish_reason": "stop",
-        }],
-        "usage": {
-            "prompt_tokens": 0,
-            "completion_tokens": 0,
-            "total_tokens": 0,
-        },
-    })
+    return JSONResponse(
+        {
+            "id": cid,
+            "object": "chat.completion",
+            "created": int(time.time()),
+            "model": MODEL_ID,
+            "choices": [
+                {
+                    "index": 0,
+                    "message": {"role": "assistant", "content": text},
+                    "finish_reason": "stop",
+                }
+            ],
+            "usage": {
+                "prompt_tokens": 0,
+                "completion_tokens": 0,
+                "total_tokens": 0,
+            },
+        }
+    )

src/openjarvis/engine/ollama.py

@@ -139,26 +139,36 @@ class OllamaEngine(InferenceEngine):
         }
         # Extract timing from Ollama response (nanoseconds → seconds)
         result["ttft"] = data.get("prompt_eval_duration", 0) / 1e9
-        result["engine_timing"] = {k: data[k] for k in
-            ("total_duration", "load_duration", "prompt_eval_duration", "eval_duration")
-            if k in data}
+        result["engine_timing"] = {
+            k: data[k]
+            for k in (
+                "total_duration",
+                "load_duration",
+                "prompt_eval_duration",
+                "eval_duration",
+            )
+            if k in data
+        }
         # Extract tool calls if present
         raw_tool_calls = data.get("message", {}).get("tool_calls", [])
         if raw_tool_calls:
             tool_calls = []
             for i, tc in enumerate(raw_tool_calls):
                 raw_args = tc.get("function", {}).get(
-                    "arguments", "{}",
+                    "arguments",
+                    "{}",
+                )
+                tool_calls.append(
+                    {
+                        "id": tc.get("id", f"call_{i}"),
+                        "name": tc.get("function", {}).get("name", ""),
+                        "arguments": (
+                            json.dumps(raw_args)
+                            if isinstance(raw_args, dict)
+                            else raw_args
+                        ),
+                    }
                 )
-                tool_calls.append({
-                    "id": tc.get("id", f"call_{i}"),
-                    "name": tc.get("function", {}).get("name", ""),
-                    "arguments": (
-                        json.dumps(raw_args)
-                        if isinstance(raw_args, dict)
-                        else raw_args
-                    ),
-                })
             result["tool_calls"] = tool_calls
         return result
 
@@ -199,8 +209,7 @@ class OllamaEngine(InferenceEngine):
                         est_prompt = estimate_prompt_tokens(messages)
                         full_prompt = max(reported_prompt, est_prompt)
                         evaluated = (
-                            reported_prompt if reported_prompt > 0
-                            else full_prompt
+                            reported_prompt if reported_prompt > 0 else full_prompt
                         )
                         comp = chunk.get("eval_count", 0)
                         self._last_stream_usage = {
@@ -220,11 +229,14 @@ class OllamaEngine(InferenceEngine):
             resp = self._client.get("/api/tags")
             resp.raise_for_status()
         except (
-            httpx.ConnectError, httpx.TimeoutException, httpx.HTTPStatusError,
+            httpx.ConnectError,
+            httpx.TimeoutException,
+            httpx.HTTPStatusError,
         ) as exc:
             logger.warning(
                 "Failed to list models from Ollama at %s: %s",
-                self._host, exc,
+                self._host,
+                exc,
             )
             return []
         data = resp.json()

src/openjarvis/evals/backends/jarvis_agent.py

@@ -57,8 +57,11 @@ class JarvisAgentBackend(InferenceBackend):
         max_tokens: int = 2048,
     ) -> str:
         result = self.generate_full(
-            prompt, model=model, system=system,
-            temperature=temperature, max_tokens=max_tokens,
+            prompt,
+            model=model,
+            system=system,
+            temperature=temperature,
+            max_tokens=max_tokens,
         )
         return result["content"]
 

src/openjarvis/evals/backends/jarvis_direct.py

@@ -43,8 +43,11 @@ class JarvisDirectBackend(InferenceBackend):
         max_tokens: int = 2048,
     ) -> str:
         result = self.generate_full(
-            prompt, model=model, system=system,
-            temperature=temperature, max_tokens=max_tokens,
+            prompt,
+            model=model,
+            system=system,
+            temperature=temperature,
+            max_tokens=max_tokens,
         )
         return result["content"]
 
@@ -66,8 +69,10 @@ class JarvisDirectBackend(InferenceBackend):
 
         t0 = time.monotonic()
         result = self._system.engine.generate(
-            messages, model=model,
-            temperature=temperature, max_tokens=max_tokens,
+            messages,
+            model=model,
+            temperature=temperature,
+            max_tokens=max_tokens,
         )
         elapsed = time.monotonic() - t0
 

src/openjarvis/evals/backends/terminalbench_native.py

@@ -79,6 +79,7 @@ class TerminalBenchNativeBackend(InferenceBackend):
 
         # Use built-in agent (naive uses LiteLLM)
         from terminal_bench.agents.agent_name import AgentName
+
         harness_kwargs["agent_name"] = AgentName(self._agent_name)
         harness_kwargs["agent_kwargs"] = {
             "llm": LiteLLM(
@@ -95,13 +96,25 @@ class TerminalBenchNativeBackend(InferenceBackend):
         self._results = harness.run()
         return self._results
 
-    def generate(self, prompt: str, *, model: str, system: str = "",
-                 temperature: float = 0.0, max_tokens: int = 2048) -> str:
+    def generate(
+        self,
+        prompt: str,
+        *,
+        model: str,
+        system: str = "",
+        temperature: float = 0.0,
+        max_tokens: int = 2048,
+    ) -> str:
         return ""
 
     def generate_full(
-        self, prompt: str, *, model: str, system: str = "",
-        temperature: float = 0.0, max_tokens: int = 2048,
+        self,
+        prompt: str,
+        *,
+        model: str,
+        system: str = "",
+        temperature: float = 0.0,
+        max_tokens: int = 2048,
     ) -> Dict[str, Any]:
         return {"content": "", "usage": {}, "model": model, "latency_seconds": 0.0}
 

src/openjarvis/evals/cli.py

@@ -45,7 +45,8 @@ BENCHMARKS = {
     "swebench": {"category": "agentic", "description": "SWE-bench code patches"},
     "swefficiency": {"category": "agentic", "description": "SWEfficiency optimization"},
     "terminalbench": {
-        "category": "agentic", "description": "TerminalBench terminal tasks",
+        "category": "agentic",
+        "description": "TerminalBench terminal tasks",
     },
     "terminalbench-native": {
         "category": "agentic",
@@ -140,13 +141,19 @@ def _setup_logging(verbose: bool) -> None:
     )
 
 
-def _build_backend(backend_name: str, engine_key: Optional[str],
-                    agent_name: str, tools: list[str],
-                    telemetry: bool = False, gpu_metrics: bool = False,
-                    model: Optional[str] = None):
+def _build_backend(
+    backend_name: str,
+    engine_key: Optional[str],
+    agent_name: str,
+    tools: list[str],
+    telemetry: bool = False,
+    gpu_metrics: bool = False,
+    model: Optional[str] = None,
+):
     """Construct the appropriate backend."""
     if backend_name == "jarvis-agent":
         from openjarvis.evals.backends.jarvis_agent import JarvisAgentBackend
+
         return JarvisAgentBackend(
             engine_key=engine_key,
             agent_name=agent_name,
@@ -157,6 +164,7 @@ def _build_backend(backend_name: str, engine_key: Optional[str],
         )
     else:
         from openjarvis.evals.backends.jarvis_direct import JarvisDirectBackend
+
         return JarvisDirectBackend(
             engine_key=engine_key,
             telemetry=telemetry,
@@ -168,104 +176,137 @@ def _build_dataset(benchmark: str, subset: str | None = None):
     """Construct the dataset provider for a benchmark."""
     if benchmark == "supergpqa":
         from openjarvis.evals.datasets.supergpqa import SuperGPQADataset
+
         return SuperGPQADataset()
     elif benchmark == "gpqa":
         from openjarvis.evals.datasets.gpqa import GPQADataset
+
         return GPQADataset()
     elif benchmark == "mmlu-pro":
         from openjarvis.evals.datasets.mmlu_pro import MMLUProDataset
+
         return MMLUProDataset()
     elif benchmark == "math500":
         from openjarvis.evals.datasets.math500 import MATH500Dataset
+
         return MATH500Dataset()
     elif benchmark == "natural-reasoning":
         from openjarvis.evals.datasets.natural_reasoning import NaturalReasoningDataset
+
         return NaturalReasoningDataset()
     elif benchmark == "hle":
         from openjarvis.evals.datasets.hle import HLEDataset
+
         return HLEDataset()
     elif benchmark == "simpleqa":
         from openjarvis.evals.datasets.simpleqa import SimpleQADataset
+
         return SimpleQADataset()
     elif benchmark == "wildchat":
         from openjarvis.evals.datasets.wildchat import WildChatDataset
+
         return WildChatDataset()
     elif benchmark == "ipw":
         from openjarvis.evals.datasets.ipw_mixed import IPWDataset
+
         return IPWDataset()
     elif benchmark == "gaia":
         from openjarvis.evals.datasets.gaia import GAIADataset
+
         return GAIADataset()
     elif benchmark == "frames":
         from openjarvis.evals.datasets.frames import FRAMESDataset
+
         return FRAMESDataset()
     elif benchmark == "swebench":
         from openjarvis.evals.datasets.swebench import SWEBenchDataset
+
         return SWEBenchDataset()
     elif benchmark == "swefficiency":
         from openjarvis.evals.datasets.swefficiency import SWEfficiencyDataset
+
         return SWEfficiencyDataset()
     elif benchmark == "terminalbench":
         from openjarvis.evals.datasets.terminalbench import TerminalBenchDataset
+
         return TerminalBenchDataset()
     elif benchmark == "terminalbench-native":
         from openjarvis.evals.datasets.terminalbench_native import (
             TerminalBenchNativeDataset,
         )
+
         return TerminalBenchNativeDataset()
     elif benchmark == "email_triage":
         from openjarvis.evals.datasets.email_triage import EmailTriageDataset
+
         return EmailTriageDataset()
     elif benchmark == "morning_brief":
         from openjarvis.evals.datasets.morning_brief import MorningBriefDataset
+
         return MorningBriefDataset()
     elif benchmark == "research_mining":
         from openjarvis.evals.datasets.research_mining import ResearchMiningDataset
+
         return ResearchMiningDataset()
     elif benchmark == "knowledge_base":
         from openjarvis.evals.datasets.knowledge_base import KnowledgeBaseDataset
+
         return KnowledgeBaseDataset()
     elif benchmark == "coding_task":
         from openjarvis.evals.datasets.coding_task import CodingTaskDataset
+
         return CodingTaskDataset()
     elif benchmark == "loghub":
         from openjarvis.evals.datasets.loghub import LogHubDataset
+
         return LogHubDataset()
     elif benchmark == "ama-bench":
         from openjarvis.evals.datasets.ama_bench import AMABenchDataset
+
         return AMABenchDataset()
     elif benchmark == "lifelong-agent":
         from openjarvis.evals.datasets.lifelong_agent import LifelongAgentDataset
+
         return LifelongAgentDataset(subset=subset or "db_bench")
     elif benchmark == "deepplanning":
         from openjarvis.evals.datasets.deepplanning import DeepPlanningDataset
+
         return DeepPlanningDataset()
     elif benchmark == "paperarena":
         from openjarvis.evals.datasets.paperarena import PaperArenaDataset
+
         return PaperArenaDataset()
     elif benchmark == "webchorearena":
         from openjarvis.evals.datasets.webchorearena import WebChoreArenaDataset
+
         return WebChoreArenaDataset()
     elif benchmark == "workarena":
         from openjarvis.evals.datasets.workarena import WorkArenaDataset
+
         return WorkArenaDataset()
     elif benchmark == "coding_assistant":
         from openjarvis.evals.datasets.coding_assistant import CodingAssistantDataset
+
         return CodingAssistantDataset()
     elif benchmark == "security_scanner":
         from openjarvis.evals.datasets.security_scanner import SecurityScannerDataset
+
         return SecurityScannerDataset()
     elif benchmark == "daily_digest":
         from openjarvis.evals.datasets.daily_digest import DailyDigestDataset
+
         return DailyDigestDataset()
     elif benchmark == "doc_qa":
         from openjarvis.evals.datasets.doc_qa import DocQADataset
+
         return DocQADataset()
     elif benchmark == "browser_assistant":
         from openjarvis.evals.datasets.browser_assistant import BrowserAssistantDataset
+
         return BrowserAssistantDataset()
     elif benchmark == "pinchbench":
         from openjarvis.evals.datasets.pinchbench import PinchBenchDataset
+
         return PinchBenchDataset(path=subset)
     else:
         raise click.ClickException(f"Unknown benchmark: {benchmark}")
@@ -275,101 +316,133 @@ def _build_scorer(benchmark: str, judge_backend, judge_model: str):
     """Construct the scorer for a benchmark."""
     if benchmark == "supergpqa":
         from openjarvis.evals.scorers.supergpqa_mcq import SuperGPQAScorer
+
         return SuperGPQAScorer(judge_backend, judge_model)
     elif benchmark == "gpqa":
         from openjarvis.evals.scorers.gpqa_mcq import GPQAScorer
+
         return GPQAScorer(judge_backend, judge_model)
     elif benchmark == "mmlu-pro":
         from openjarvis.evals.scorers.mmlu_pro_mcq import MMLUProScorer
+
         return MMLUProScorer(judge_backend, judge_model)
     elif benchmark == "math500" or benchmark == "natural-reasoning":
         from openjarvis.evals.scorers.reasoning_judge import ReasoningJudgeScorer
+
         return ReasoningJudgeScorer(judge_backend, judge_model)
     elif benchmark == "hle":
         from openjarvis.evals.scorers.hle_judge import HLEScorer
+
         return HLEScorer(judge_backend, judge_model)
     elif benchmark == "simpleqa":
         from openjarvis.evals.scorers.simpleqa_judge import SimpleQAScorer
+
         return SimpleQAScorer(judge_backend, judge_model)
     elif benchmark == "wildchat":
         from openjarvis.evals.scorers.wildchat_judge import WildChatScorer
+
         return WildChatScorer(judge_backend, judge_model)
     elif benchmark == "ipw":
         from openjarvis.evals.scorers.ipw_mixed import IPWMixedScorer
+
         return IPWMixedScorer(judge_backend, judge_model)
     elif benchmark == "gaia":
         from openjarvis.evals.scorers.gaia_exact import GAIAScorer
+
         return GAIAScorer(judge_backend, judge_model)
     elif benchmark == "frames":
         from openjarvis.evals.scorers.frames_judge import FRAMESScorer
+
         return FRAMESScorer(judge_backend, judge_model)
     elif benchmark == "swebench":
         from openjarvis.evals.scorers.swebench_structural import SWEBenchScorer
+
         return SWEBenchScorer(judge_backend, judge_model)
     elif benchmark == "swefficiency":
         from openjarvis.evals.scorers.swefficiency_structural import SWEfficiencyScorer
+
         return SWEfficiencyScorer(judge_backend, judge_model)
     elif benchmark == "terminalbench":
         from openjarvis.evals.scorers.terminalbench_judge import TerminalBenchScorer
+
         return TerminalBenchScorer(judge_backend, judge_model)
     elif benchmark == "terminalbench-native":
         from openjarvis.evals.scorers.terminalbench_native_structural import (
             TerminalBenchNativeScorer,
         )
+
         return TerminalBenchNativeScorer(judge_backend, judge_model)
     elif benchmark == "email_triage":
         from openjarvis.evals.scorers.email_triage import EmailTriageScorer
+
         return EmailTriageScorer(judge_backend, judge_model)
     elif benchmark == "morning_brief":
         from openjarvis.evals.scorers.morning_brief import MorningBriefScorer
+
         return MorningBriefScorer(judge_backend, judge_model)
     elif benchmark == "research_mining":
         from openjarvis.evals.scorers.research_mining import ResearchMiningScorer
+
         return ResearchMiningScorer(judge_backend, judge_model)
     elif benchmark == "knowledge_base":
         from openjarvis.evals.scorers.knowledge_base import KnowledgeBaseScorer
+
         return KnowledgeBaseScorer(judge_backend, judge_model)
     elif benchmark == "coding_task":
         from openjarvis.evals.scorers.coding_task import CodingTaskScorer
+
         return CodingTaskScorer(judge_backend, judge_model)
     elif benchmark == "loghub":
         from openjarvis.evals.scorers.loghub_scorer import LogHubScorer
+
         return LogHubScorer(judge_backend, judge_model)
     elif benchmark == "ama-bench":
         from openjarvis.evals.scorers.ama_bench_judge import AMABenchScorer
+
         return AMABenchScorer(judge_backend, judge_model)
     elif benchmark == "lifelong-agent":
         from openjarvis.evals.scorers.lifelong_agent_scorer import LifelongAgentScorer
+
         return LifelongAgentScorer(judge_backend, judge_model)
     elif benchmark == "deepplanning":
         from openjarvis.evals.scorers.deepplanning_scorer import DeepPlanningScorer
+
         return DeepPlanningScorer(judge_backend, judge_model)
     elif benchmark == "paperarena":
         from openjarvis.evals.scorers.paperarena_judge import PaperArenaScorer
+
         return PaperArenaScorer(judge_backend, judge_model)
     elif benchmark == "webchorearena":
         from openjarvis.evals.scorers.webchorearena_scorer import WebChoreArenaScorer
+
         return WebChoreArenaScorer(judge_backend, judge_model)
     elif benchmark == "workarena":
         from openjarvis.evals.scorers.workarena_scorer import WorkArenaScorer
+
         return WorkArenaScorer(judge_backend, judge_model)
     elif benchmark == "coding_assistant":
         from openjarvis.evals.scorers.coding_assistant import CodingAssistantScorer
+
         return CodingAssistantScorer(judge_backend, judge_model)
     elif benchmark == "security_scanner":
         from openjarvis.evals.scorers.security_scanner import SecurityScannerScorer
+
         return SecurityScannerScorer(judge_backend, judge_model)
     elif benchmark == "daily_digest":
         from openjarvis.evals.scorers.daily_digest import DailyDigestScorer
+
         return DailyDigestScorer(judge_backend, judge_model)
     elif benchmark == "doc_qa":
         from openjarvis.evals.scorers.doc_qa import DocQAScorer
+
         return DocQAScorer(judge_backend, judge_model)
     elif benchmark == "browser_assistant":
         from openjarvis.evals.scorers.browser_assistant import BrowserAssistantScorer
+
         return BrowserAssistantScorer(judge_backend, judge_model)
     elif benchmark == "pinchbench":
         from openjarvis.evals.scorers.pinchbench import PinchBenchScorer
+
         return PinchBenchScorer(judge_backend, judge_model)
     else:
         raise click.ClickException(f"Unknown benchmark: {benchmark}")
@@ -384,6 +457,7 @@ def _build_judge_backend(judge_model: str, engine_key: str = "cloud"):
     to use the backend rather than failing at startup.
     """
     from openjarvis.evals.backends.jarvis_direct import JarvisDirectBackend
+
     try:
         return JarvisDirectBackend(engine_key=engine_key)
     except RuntimeError as exc:
@@ -391,7 +465,8 @@ def _build_judge_backend(judge_model: str, engine_key: str = "cloud"):
             "Judge backend (%s) unavailable: %s — "
             "deterministic scorers will still work; "
             "LLM-judge scorers will fail when scoring.",
-            engine_key, exc,
+            engine_key,
+            exc,
         )
         return None
 
@@ -421,25 +496,30 @@ def _build_trackers(config) -> list:
     if getattr(config, "wandb_project", ""):
         try:
             from openjarvis.evals.trackers.wandb_tracker import WandbTracker
-            trackers.append(WandbTracker(
-                project=config.wandb_project,
-                entity=getattr(config, "wandb_entity", ""),
-                tags=getattr(config, "wandb_tags", ""),
-                group=getattr(config, "wandb_group", ""),
-            ))
+
+            trackers.append(
+                WandbTracker(
+                    project=config.wandb_project,
+                    entity=getattr(config, "wandb_entity", ""),
+                    tags=getattr(config, "wandb_tags", ""),
+                    group=getattr(config, "wandb_group", ""),
+                )
+            )
         except ImportError as exc:
             raise click.ClickException(
-                f"wandb not installed: {exc}\n"
-                "Install with: uv sync --extra eval-wandb"
+                f"wandb not installed: {exc}\nInstall with: uv sync --extra eval-wandb"
             ) from exc
     if getattr(config, "sheets_spreadsheet_id", ""):
         try:
             from openjarvis.evals.trackers.sheets_tracker import SheetsTracker
-            trackers.append(SheetsTracker(
-                spreadsheet_id=config.sheets_spreadsheet_id,
-                worksheet=getattr(config, "sheets_worksheet", "Results"),
-                credentials_path=getattr(config, "sheets_credentials_path", ""),
-            ))
+
+            trackers.append(
+                SheetsTracker(
+                    spreadsheet_id=config.sheets_spreadsheet_id,
+                    worksheet=getattr(config, "sheets_worksheet", "Results"),
+                    credentials_path=getattr(config, "sheets_credentials_path", ""),
+                )
+            )
         except ImportError as exc:
             raise click.ClickException(
                 f"gspread not installed: {exc}\n"
@@ -486,7 +566,8 @@ def _run_single(config, console: Optional[Console] = None) -> object:
                 task = progress.add_task("Evaluating samples...", total=num_samples)
                 summary = runner.run(
                     progress_callback=lambda done, total: progress.update(
-                        task, completed=done,
+                        task,
+                        completed=done,
                     ),
                 )
         else:
@@ -533,8 +614,7 @@ def _run_agentic(
     if config.benchmark == "pinchbench" and hasattr(dataset, "set_judge"):
         judge_engine = getattr(config, "judge_engine", "cloud") or "cloud"
         judge_model = (
-            getattr(config, "judge_model", None)
-            or "anthropic/claude-opus-4-5"
+            getattr(config, "judge_model", None) or "anthropic/claude-opus-4-5"
         )
         judge_backend = _build_judge_backend(judge_model, engine_key=judge_engine)
         dataset.set_judge(judge_backend, judge_model)
@@ -576,7 +656,8 @@ def _run_agentic(
         monitor = create_energy_monitor()
         if monitor is not None:
             telemetry_session = TelemetrySession(
-                monitor=monitor, interval_ms=100,
+                monitor=monitor,
+                interval_ms=100,
             )
     except ImportError:
         pass
@@ -650,6 +731,7 @@ def _run_agentic(
     # Try HF dataset export (optional)
     try:
         from openjarvis.evals.core.export import export_hf_dataset
+
         hf_path = run_dir / "hf_dataset"
         export_hf_dataset(traces, hf_path)
         console.print(f"  [green]HF Arrow:[/green]  {hf_path}")
@@ -664,6 +746,7 @@ def _run_agentic(
 def _nullctx():
     """Return a no-op context manager."""
     from contextlib import nullcontext
+
     return nullcontext()
 
 
@@ -681,7 +764,8 @@ def _print_agentic_summary(console: Console, traces, config) -> None:
     total_wall = sum(t.total_wall_clock_s for t in traces)
 
     gpu_energies = [
-        t.total_gpu_energy_joules for t in traces
+        t.total_gpu_energy_joules
+        for t in traces
         if t.total_gpu_energy_joules is not None
     ]
     total_gpu_energy = sum(gpu_energies) if gpu_energies else None
@@ -710,7 +794,7 @@ def _print_agentic_summary(console: Console, traces, config) -> None:
     table.add_row("Wall clock", f"{total_wall:.1f}s")
     table.add_row(
         "Avg query time",
-        f"{total_wall/len(traces):.1f}s" if traces else "0s",
+        f"{total_wall / len(traces):.1f}s" if traces else "0s",
     )
 
     if total_gpu_energy is not None:
@@ -722,7 +806,7 @@ def _print_agentic_summary(console: Console, traces, config) -> None:
     if total_out_tok > 0 and total_wall > 0:
         table.add_row(
             "Throughput",
-            f"{total_out_tok/total_wall:.1f} tok/s",
+            f"{total_out_tok / total_wall:.1f} tok/s",
         )
 
     console.print(table)
@@ -746,18 +830,14 @@ def _run_from_config(
     if model_filter:
         run_configs = [rc for rc in run_configs if model_filter in rc.model]
         if not run_configs:
-            raise click.ClickException(
-                f"No models match filter '{model_filter}'"
-            )
+            raise click.ClickException(f"No models match filter '{model_filter}'")
 
     suite_name = suite.meta.name or Path(config_path).stem
 
     # Banner + configuration
     print_banner(console)
     print_section(console, "Suite Configuration")
-    console.print(
-        f"  [cyan]Suite:[/cyan]       {suite_name}"
-    )
+    console.print(f"  [cyan]Suite:[/cyan]       {suite_name}")
     if suite.meta.description:
         console.print(f"  [cyan]Description:[/cyan] {suite.meta.description}")
     console.print(
@@ -802,86 +882,166 @@ def main():
 
 
 @main.command()
-@click.option("-c", "--config", "config_path", default=None,
-              type=click.Path(), help="TOML config file for suite runs")
-@click.option("-b", "--benchmark", default=None,
-              type=click.Choice(list(BENCHMARKS.keys())),
-              help="Benchmark to run")
-@click.option("--backend", default="jarvis-direct",
-              type=click.Choice(list(BACKENDS.keys())),
-              help="Inference backend")
-@click.option("-m", "--model", default=None, help="Model identifier")
-@click.option("-e", "--engine", "engine_key", default=None,
-              help="Engine key (ollama, vllm, cloud, ...)")
-@click.option("--agent", "agent_name", default="orchestrator",
-              help="Agent name for jarvis-agent backend")
-@click.option("--tools", default="", help="Comma-separated tool names")
-@click.option("-n", "--max-samples", type=int, default=None,
-              help="Maximum samples to evaluate")
-@click.option("-w", "--max-workers", type=int, default=4,
-              help="Parallel workers")
-@click.option("--judge-model", default="gpt-5-mini-2025-08-07",
-              help="LLM judge model")
-@click.option("-o", "--output", "output_path", default=None,
-              help="Output JSONL path")
-@click.option("--seed", type=int, default=42, help="Random seed")
-@click.option("--split", "dataset_split", default=None,
-              help="Dataset split override")
-@click.option("--temperature", type=float, default=0.0,
-              help="Generation temperature")
-@click.option("--max-tokens", type=int, default=2048,
-              help="Max output tokens")
-@click.option("--telemetry/--no-telemetry", default=False,
-              help="Enable telemetry collection during eval")
-@click.option("--gpu-metrics/--no-gpu-metrics", default=False,
-              help="Enable GPU metrics collection")
 @click.option(
-    "--compact", is_flag=True, default=False,
+    "-c",
+    "--config",
+    "config_path",
+    default=None,
+    type=click.Path(),
+    help="TOML config file for suite runs",
+)
+@click.option(
+    "-b",
+    "--benchmark",
+    default=None,
+    type=click.Choice(list(BENCHMARKS.keys())),
+    help="Benchmark to run",
+)
+@click.option(
+    "--backend",
+    default="jarvis-direct",
+    type=click.Choice(list(BACKENDS.keys())),
+    help="Inference backend",
+)
+@click.option("-m", "--model", default=None, help="Model identifier")
+@click.option(
+    "-e",
+    "--engine",
+    "engine_key",
+    default=None,
+    help="Engine key (ollama, vllm, cloud, ...)",
+)
+@click.option(
+    "--agent",
+    "agent_name",
+    default="orchestrator",
+    help="Agent name for jarvis-agent backend",
+)
+@click.option("--tools", default="", help="Comma-separated tool names")
+@click.option(
+    "-n", "--max-samples", type=int, default=None, help="Maximum samples to evaluate"
+)
+@click.option("-w", "--max-workers", type=int, default=4, help="Parallel workers")
+@click.option("--judge-model", default="gpt-5-mini-2025-08-07", help="LLM judge model")
+@click.option("-o", "--output", "output_path", default=None, help="Output JSONL path")
+@click.option("--seed", type=int, default=42, help="Random seed")
+@click.option("--split", "dataset_split", default=None, help="Dataset split override")
+@click.option("--temperature", type=float, default=0.0, help="Generation temperature")
+@click.option("--max-tokens", type=int, default=2048, help="Max output tokens")
+@click.option(
+    "--telemetry/--no-telemetry",
+    default=False,
+    help="Enable telemetry collection during eval",
+)
+@click.option(
+    "--gpu-metrics/--no-gpu-metrics",
+    default=False,
+    help="Enable GPU metrics collection",
+)
+@click.option(
+    "--compact",
+    is_flag=True,
+    default=False,
     help="Dense single-table output",
 )
 @click.option(
-    "--trace-detail", is_flag=True, default=False,
+    "--trace-detail",
+    is_flag=True,
+    default=False,
     help="Full per-step trace listing",
 )
-@click.option("--wandb-project", default="",
-              help="W&B project name (enables tracking)")
-@click.option("--wandb-entity", default="",
-              help="W&B entity (team or user)")
-@click.option("--wandb-tags", default="",
-              help="Comma-separated W&B tags")
-@click.option("--wandb-group", default="",
-              help="W&B run group")
-@click.option("--sheets-id", "sheets_spreadsheet_id", default="",
-              help="Google Sheets spreadsheet ID")
-@click.option("--sheets-worksheet", default="Results",
-              help="Google Sheets worksheet name")
-@click.option("--sheets-creds", "sheets_credentials_path",
-              default="",
-              help="Service account JSON path")
-@click.option("--model-filter", default=None,
-              help="Filter models by name substring (for multi-model configs)")
-@click.option("--judge-engine", default="cloud",
-              help="Engine key for LLM judge (default: cloud). "
-              "Use 'vllm' to judge locally.")
-@click.option("--agentic", is_flag=True, default=False,
-              help="Use AgenticRunner for multi-turn agent execution")
-@click.option("--episode-mode", is_flag=True, default=False,
-              help="Sequential episode processing with lifelong learning "
-                   "(required for lifelong-agent and similar benchmarks)")
-@click.option("--concurrency", type=int, default=1,
-              help="Parallel query execution (AgenticRunner only)")
-@click.option("--query-timeout", type=float, default=None,
-              help="Per-query wall-clock timeout in seconds (AgenticRunner only)")
+@click.option("--wandb-project", default="", help="W&B project name (enables tracking)")
+@click.option("--wandb-entity", default="", help="W&B entity (team or user)")
+@click.option("--wandb-tags", default="", help="Comma-separated W&B tags")
+@click.option("--wandb-group", default="", help="W&B run group")
+@click.option(
+    "--sheets-id",
+    "sheets_spreadsheet_id",
+    default="",
+    help="Google Sheets spreadsheet ID",
+)
+@click.option(
+    "--sheets-worksheet", default="Results", help="Google Sheets worksheet name"
+)
+@click.option(
+    "--sheets-creds",
+    "sheets_credentials_path",
+    default="",
+    help="Service account JSON path",
+)
+@click.option(
+    "--model-filter",
+    default=None,
+    help="Filter models by name substring (for multi-model configs)",
+)
+@click.option(
+    "--judge-engine",
+    default="cloud",
+    help="Engine key for LLM judge (default: cloud). Use 'vllm' to judge locally.",
+)
+@click.option(
+    "--agentic",
+    is_flag=True,
+    default=False,
+    help="Use AgenticRunner for multi-turn agent execution",
+)
+@click.option(
+    "--episode-mode",
+    is_flag=True,
+    default=False,
+    help="Sequential episode processing with lifelong learning "
+    "(required for lifelong-agent and similar benchmarks)",
+)
+@click.option(
+    "--concurrency",
+    type=int,
+    default=1,
+    help="Parallel query execution (AgenticRunner only)",
+)
+@click.option(
+    "--query-timeout",
+    type=float,
+    default=None,
+    help="Per-query wall-clock timeout in seconds (AgenticRunner only)",
+)
 @click.option("-v", "--verbose", is_flag=True, help="Verbose logging")
 @click.pass_context
-def run(ctx, config_path, benchmark, backend, model, engine_key, agent_name,
-        tools, max_samples, max_workers, judge_model, output_path, seed,
-        dataset_split, temperature, max_tokens, telemetry, gpu_metrics,
-        compact, trace_detail,
-        wandb_project, wandb_entity, wandb_tags, wandb_group,
-        sheets_spreadsheet_id, sheets_worksheet, sheets_credentials_path,
-        model_filter, judge_engine, agentic, episode_mode,
-        concurrency, query_timeout, verbose):
+def run(
+    ctx,
+    config_path,
+    benchmark,
+    backend,
+    model,
+    engine_key,
+    agent_name,
+    tools,
+    max_samples,
+    max_workers,
+    judge_model,
+    output_path,
+    seed,
+    dataset_split,
+    temperature,
+    max_tokens,
+    telemetry,
+    gpu_metrics,
+    compact,
+    trace_detail,
+    wandb_project,
+    wandb_entity,
+    wandb_tags,
+    wandb_group,
+    sheets_spreadsheet_id,
+    sheets_worksheet,
+    sheets_credentials_path,
+    model_filter,
+    judge_engine,
+    agentic,
+    episode_mode,
+    concurrency,
+    query_timeout,
+    verbose,
+):
     """Run a single benchmark evaluation, or a full suite from a TOML config."""
     _setup_logging(verbose)
 
@@ -900,8 +1060,7 @@ def run(ctx, config_path, benchmark, backend, model, engine_key, agent_name,
         )
     if model is None:
         raise click.UsageError(
-            "Missing option '-m' / '--model' "
-            "(required when --config is not provided)"
+            "Missing option '-m' / '--model' (required when --config is not provided)"
         )
 
     from openjarvis.evals.core.types import RunConfig
@@ -960,22 +1119,18 @@ def run(ctx, config_path, benchmark, backend, model, engine_key, agent_name,
     )
     if episode_mode:
         console.print(
-            "  [cyan]Mode:[/cyan]       episode "
-            "(sequential + lifelong learning)"
+            "  [cyan]Mode:[/cyan]       episode (sequential + lifelong learning)"
         )
 
     if agentic:
         # --- Agentic runner path ---
         print_section(console, "Agentic Evaluation")
-        console.print(
-            f"  [cyan]Concurrency:[/cyan] {concurrency}"
-        )
+        console.print(f"  [cyan]Concurrency:[/cyan] {concurrency}")
         if query_timeout:
-            console.print(
-                f"  [cyan]Timeout:[/cyan]     {query_timeout}s per query"
-            )
+            console.print(f"  [cyan]Timeout:[/cyan]     {query_timeout}s per query")
         _run_agentic(
-            config, console=console,
+            config,
+            console=console,
             concurrency=concurrency,
             query_timeout=query_timeout,
         )
@@ -1000,19 +1155,18 @@ def run(ctx, config_path, benchmark, backend, model, engine_key, agent_name,
 
 @main.command("run-all")
 @click.option("-m", "--model", required=True, help="Model identifier")
-@click.option("-e", "--engine", "engine_key", default=None,
-              help="Engine key")
-@click.option("-n", "--max-samples", type=int, default=None,
-              help="Max samples per benchmark")
-@click.option("-w", "--max-workers", type=int, default=4,
-              help="Parallel workers")
+@click.option("-e", "--engine", "engine_key", default=None, help="Engine key")
+@click.option(
+    "-n", "--max-samples", type=int, default=None, help="Max samples per benchmark"
+)
+@click.option("-w", "--max-workers", type=int, default=4, help="Parallel workers")
 @click.option("--judge-model", default="gpt-5-mini-2025-08-07", help="LLM judge model")
-@click.option("--output-dir", default="results/",
-              help="Output directory for results")
+@click.option("--output-dir", default="results/", help="Output directory for results")
 @click.option("--seed", type=int, default=42, help="Random seed")
 @click.option("-v", "--verbose", is_flag=True, help="Verbose logging")
-def run_all(model, engine_key, max_samples, max_workers, judge_model,
-            output_dir, seed, verbose):
+def run_all(
+    model, engine_key, max_samples, max_workers, judge_model, output_dir, seed, verbose
+):
     """Run all benchmarks."""
     _setup_logging(verbose)
 
@@ -1069,11 +1223,13 @@ def run_all(model, engine_key, max_samples, max_workers, judge_model,
                     console=console,
                 ) as progress:
                     task = progress.add_task(
-                        f"Evaluating {bench_name}...", total=max_samples,
+                        f"Evaluating {bench_name}...",
+                        total=max_samples,
                     )
                     summary = runner.run(
                         progress_callback=lambda done, total: progress.update(
-                            task, completed=done,
+                            task,
+                            completed=done,
                         ),
                     )
             else:

src/openjarvis/evals/core/agentic_runner.py

@@ -36,10 +36,7 @@ def _compute_energy_delta(
     gpu_field: str = "gpu_energy_j",
 ) -> Optional[float]:
     """Compute energy delta from first to last reading for a field."""
-    values = [
-        getattr(s, gpu_field, None)
-        for s in readings
-    ]
+    values = [getattr(s, gpu_field, None) for s in readings]
     values = [v for v in values if v is not None and math.isfinite(v)]
     if len(values) >= 2:
         delta = values[-1] - values[0]
@@ -52,10 +49,7 @@ def _compute_power_avg(
     power_field: str = "gpu_power_w",
 ) -> Optional[float]:
     """Compute average power across readings for a field."""
-    values = [
-        getattr(s, power_field, None)
-        for s in readings
-    ]
+    values = [getattr(s, power_field, None) for s in readings]
     values = [v for v in values if v is not None and math.isfinite(v)]
     return statistics.mean(values) if values else None
 
@@ -64,9 +58,7 @@ def _compute_power_avg(
 # Patch extraction helpers
 # ---------------------------------------------------------------------------
 
-_FENCED_DIFF_RE = re.compile(
-    r"```(?:diff|patch)\s*\n(.*?)```", re.DOTALL
-)
+_FENCED_DIFF_RE = re.compile(r"```(?:diff|patch)\s*\n(.*?)```", re.DOTALL)
 _UNIFIED_DIFF_MARKERS = ("diff --git", "--- a/", "+++ b/", "@@ ")
 
 
@@ -160,16 +152,16 @@ class AgenticRunner:
                     index, record, model, self._agent, self._event_recorder
                 )
                 if self._query_timeout:
-                    trace = await asyncio.wait_for(
-                        fut, timeout=self._query_timeout
-                    )
+                    trace = await asyncio.wait_for(fut, timeout=self._query_timeout)
                 else:
                     trace = await fut
             except asyncio.TimeoutError:
                 elapsed = time.time() - start_time
                 LOGGER.warning(
                     "Query %s timed out after %.0fs (limit=%ss)",
-                    query_id, elapsed, self._query_timeout,
+                    query_id,
+                    elapsed,
+                    self._query_timeout,
                 )
                 workload_type = getattr(record, "category", "agentic")
                 trace = QueryTrace(
@@ -185,12 +177,13 @@ class AgenticRunner:
             self._traces.append(trace)
 
             status = (
-                "TIMEOUT" if trace.timed_out
-                else ("OK" if trace.completed else "FAIL")
+                "TIMEOUT" if trace.timed_out else ("OK" if trace.completed else "FAIL")
             )
             LOGGER.info(
                 "Task %s: %s in %.1fs",
-                query_id, status, trace.total_wall_clock_s,
+                query_id,
+                status,
+                trace.total_wall_clock_s,
             )
 
             if self._run_dir:
@@ -199,7 +192,8 @@ class AgenticRunner:
             if len(self._traces) % self._FLUSH_INTERVAL == 0:
                 LOGGER.debug(
                     "Processed %d/%d queries",
-                    len(self._traces), len(work_items),
+                    len(self._traces),
+                    len(work_items),
                 )
 
         return self._traces
@@ -213,7 +207,8 @@ class AgenticRunner:
         total = len(work_items)
         LOGGER.info(
             "Running %d queries with concurrency=%d",
-            total, self._concurrency,
+            total,
+            self._concurrency,
         )
 
         result_slots: list[Optional[QueryTrace]] = [None] * total
@@ -235,19 +230,23 @@ class AgenticRunner:
                     fut = loop.run_in_executor(
                         None,
                         self._run_single_query_sync,
-                        index, record, model, agent, recorder,
+                        index,
+                        record,
+                        model,
+                        agent,
+                        recorder,
                     )
                     if self._query_timeout:
-                        trace = await asyncio.wait_for(
-                            fut, timeout=self._query_timeout
-                        )
+                        trace = await asyncio.wait_for(fut, timeout=self._query_timeout)
                     else:
                         trace = await fut
                 except asyncio.TimeoutError:
                     elapsed = time.time() - start_time
                     LOGGER.warning(
                         "Query %s timed out after %.0fs (limit=%ss)",
-                        query_id, elapsed, self._query_timeout,
+                        query_id,
+                        elapsed,
+                        self._query_timeout,
                     )
                     workload_type = getattr(record, "category", "agentic")
                     trace = QueryTrace(
@@ -262,12 +261,15 @@ class AgenticRunner:
                     )
 
                 status = (
-                    "TIMEOUT" if trace.timed_out
+                    "TIMEOUT"
+                    if trace.timed_out
                     else ("OK" if trace.completed else "FAIL")
                 )
                 LOGGER.info(
                     "Task %s: %s in %.1fs",
-                    query_id, status, trace.total_wall_clock_s,
+                    query_id,
+                    status,
+                    trace.total_wall_clock_s,
                 )
 
                 if self._run_dir:
@@ -328,9 +330,11 @@ class AgenticRunner:
         agent_bus = getattr(agent, "bus", None)
         if agent_bus is not None:
             for etype in (EventType.TOOL_CALL_START, EventType.TOOL_CALL_END):
+
                 def _relay(event, _etype=etype):
                     data = event.data if hasattr(event, "data") else {}
                     event_recorder.record(_etype, **data)
+
                 agent_bus.subscribe(etype, _relay)
                 _bus_unsubs.append((etype, _relay))
 
@@ -364,6 +368,7 @@ class AgenticRunner:
                 # Envs with reset/step/evaluate use run_agent_loop
                 # for multi-turn interaction with conversation history.
                 if task_env is not None and hasattr(task_env, "run_agent_loop"):
+
                     def _generate(prompt: str) -> str:
                         if hasattr(agent, "ask"):
                             r = agent.ask(prompt)
@@ -402,10 +407,8 @@ class AgenticRunner:
                         result = agent.run(record.problem)
                         response_text = getattr(result, "content", str(result))
                         result_tokens = {
-                            "input_tokens": getattr(result, "input_tokens", 0)
-                            or 0,
-                            "output_tokens": getattr(result, "output_tokens", 0)
-                            or 0,
+                            "input_tokens": getattr(result, "input_tokens", 0) or 0,
+                            "output_tokens": getattr(result, "output_tokens", 0) or 0,
                             "cost_usd": getattr(result, "cost_usd", 0.0) or 0.0,
                         }
                     else:
@@ -499,13 +502,15 @@ class AgenticRunner:
         out_tok = result_tokens.get("output_tokens", 0)
         cost = result_tokens.get("cost_usd", 0.0)
         if not turns and (in_tok > 0 or out_tok > 0):
-            turns = [TurnTrace(
-                turn_index=0,
-                input_tokens=in_tok,
-                output_tokens=out_tok,
-                wall_clock_s=end_time - start_time,
-                cost_usd=cost if cost else None,
-            )]
+            turns = [
+                TurnTrace(
+                    turn_index=0,
+                    input_tokens=in_tok,
+                    output_tokens=out_tok,
+                    wall_clock_s=end_time - start_time,
+                    cost_usd=cost if cost else None,
+                )
+            ]
 
         # Backfill tokens from result when turns have zero tokens
         if turns and in_tok > 0 and out_tok > 0:
@@ -514,9 +519,7 @@ class AgenticRunner:
             if total_turn_in == 0 and total_turn_out == 0:
                 turns[0].input_tokens = in_tok
                 turns[0].output_tokens = out_tok
-                turns[0].wall_clock_s = (
-                    turns[0].wall_clock_s or (end_time - start_time)
-                )
+                turns[0].wall_clock_s = turns[0].wall_clock_s or (end_time - start_time)
                 if cost and turns[0].cost_usd is None:
                     turns[0].cost_usd = cost
 
@@ -526,6 +529,7 @@ class AgenticRunner:
                 turn.input_tokens > 0 or turn.output_tokens > 0
             ):
                 from openjarvis.evals.core.pricing import compute_turn_cost
+
                 turn.cost_usd = compute_turn_cost(
                     model, turn.input_tokens, turn.output_tokens
                 )
@@ -538,16 +542,10 @@ class AgenticRunner:
 
         # Extract MBU from telemetry readings
         mbu_values = [
-            getattr(s, "gpu_memory_bandwidth_utilization_pct", None)
-            for s in readings
+            getattr(s, "gpu_memory_bandwidth_utilization_pct", None) for s in readings
         ]
-        mbu_values = [
-            v for v in mbu_values
-            if v is not None and v >= 0
-        ]
-        query_mbu_avg = (
-            statistics.mean(mbu_values) if mbu_values else None
-        )
+        mbu_values = [v for v in mbu_values if v is not None and v >= 0]
+        query_mbu_avg = statistics.mean(mbu_values) if mbu_values else None
         query_mbu_max = max(mbu_values) if mbu_values else None
 
         trace = QueryTrace(
@@ -585,10 +583,7 @@ class AgenticRunner:
         """
         start_ns = int(start_s * 1e9)
         end_ns = int(end_s * 1e9)
-        window = [
-            r for r in readings
-            if start_ns <= r.timestamp_ns <= end_ns
-        ]
+        window = [r for r in readings if start_ns <= r.timestamp_ns <= end_ns]
         gpu_energy = _compute_energy_delta(window, "gpu_energy_j")
         cpu_energy = _compute_energy_delta(window, "cpu_energy_j")
         avg_gpu_power = _compute_power_avg(window, "gpu_power_w")
@@ -629,12 +624,14 @@ class AgenticRunner:
                 wall_clock = 0.0
                 if current_turn_start is not None:
                     wall_clock = event.timestamp - current_turn_start
-                    current_action_spans.append({
-                        "action_type": "lm_inference",
-                        "start_s": current_turn_start,
-                        "end_s": event.timestamp,
-                        "duration_s": wall_clock,
-                    })
+                    current_action_spans.append(
+                        {
+                            "action_type": "lm_inference",
+                            "start_s": current_turn_start,
+                            "end_s": event.timestamp,
+                            "duration_s": wall_clock,
+                        }
+                    )
 
                 input_tokens = event.metadata.get("prompt_tokens", 0)
                 output_tokens = event.metadata.get("completion_tokens", 0)
@@ -645,13 +642,17 @@ class AgenticRunner:
                     action_breakdown = []
                     for span in current_action_spans:
                         energy = self._action_energy_from_readings(
-                            readings, span["start_s"], span["end_s"],
+                            readings,
+                            span["start_s"],
+                            span["end_s"],
+                        )
+                        action_breakdown.append(
+                            {
+                                "action_type": span["action_type"],
+                                "duration_s": span["duration_s"],
+                                **energy,
+                            }
                         )
-                        action_breakdown.append({
-                            "action_type": span["action_type"],
-                            "duration_s": span["duration_s"],
-                            **energy,
-                        })
 
                 turn = TurnTrace(
                     turn_index=current_turn_index,
@@ -683,21 +684,25 @@ class AgenticRunner:
             elif etype == EventType.TOOL_CALL_END:
                 tool_name = event.metadata.get("tool", "unknown")
                 current_tools.append(tool_name)
-                current_tool_calls.append({
-                    "name": tool_name,
-                    "arguments": current_tool_args.pop(tool_name, {}),
-                    "result": event.metadata.get("result", ""),
-                })
+                current_tool_calls.append(
+                    {
+                        "name": tool_name,
+                        "arguments": current_tool_args.pop(tool_name, {}),
+                        "result": event.metadata.get("result", ""),
+                    }
+                )
                 start_ts = tool_start_times.pop(tool_name, None)
                 if start_ts is not None:
                     duration = event.timestamp - start_ts
                     current_tool_latencies[tool_name] = duration
-                    current_action_spans.append({
-                        "action_type": f"tool_call:{tool_name}",
-                        "start_s": start_ts,
-                        "end_s": event.timestamp,
-                        "duration_s": duration,
-                    })
+                    current_action_spans.append(
+                        {
+                            "action_type": f"tool_call:{tool_name}",
+                            "start_s": start_ts,
+                            "end_s": event.timestamp,
+                            "duration_s": duration,
+                        }
+                    )
 
         # Synthetic turn if events but no complete LM_START/END pair
         if not turns and events:
@@ -724,9 +729,7 @@ class AgenticRunner:
         if not readings or not trace.turns:
             return trace
 
-        has_turn_energy = any(
-            t.gpu_energy_joules is not None for t in trace.turns
-        )
+        has_turn_energy = any(t.gpu_energy_joules is not None for t in trace.turns)
         if has_turn_energy:
             return trace
 
@@ -770,8 +773,11 @@ class AgenticRunner:
             "num_turns": trace.num_turns,
         }
         for key in (
-            "repo", "base_commit", "dataset_name",
-            "is_resolved", "test_results",
+            "repo",
+            "base_commit",
+            "dataset_name",
+            "is_resolved",
+            "test_results",
         ):
             val = record.metadata.get(key)
             if val is not None:

src/openjarvis/evals/core/config.py

@@ -35,14 +35,31 @@ VALID_BACKENDS = {"jarvis-direct", "jarvis-agent"}
 
 # Known benchmark names (used for warnings, not hard validation)
 KNOWN_BENCHMARKS = {
-    "supergpqa", "gpqa", "mmlu-pro", "math500", "natural-reasoning", "hle",
-    "simpleqa", "wildchat", "ipw",
-    "gaia", "frames", "swebench", "swefficiency",
-    "terminalbench", "terminalbench-native",
-    "email_triage", "morning_brief", "research_mining",
-    "knowledge_base", "coding_task",
-    "coding_assistant", "security_scanner", "daily_digest",
-    "doc_qa", "browser_assistant",
+    "supergpqa",
+    "gpqa",
+    "mmlu-pro",
+    "math500",
+    "natural-reasoning",
+    "hle",
+    "simpleqa",
+    "wildchat",
+    "ipw",
+    "gaia",
+    "frames",
+    "swebench",
+    "swefficiency",
+    "terminalbench",
+    "terminalbench-native",
+    "email_triage",
+    "morning_brief",
+    "research_mining",
+    "knowledge_base",
+    "coding_task",
+    "coding_assistant",
+    "security_scanner",
+    "daily_digest",
+    "doc_qa",
+    "browser_assistant",
     "pinchbench",
 }
 
@@ -123,36 +140,32 @@ def load_eval_config(path: str | Path) -> EvalSuiteConfig:
     for m in models_raw:
         if not m.get("name"):
             raise EvalConfigError("Each [[models]] entry must have a 'name' field")
-        models.append(ModelConfig(
-            name=m["name"],
-            engine=m.get("engine"),
-            provider=m.get("provider"),
-            temperature=float(m["temperature"]) if "temperature" in m else None,
-            max_tokens=int(m["max_tokens"]) if "max_tokens" in m else None,
-            param_count_b=float(m.get("param_count_b", 0.0)),
-            active_params_b=(
-                float(m["active_params_b"])
-                if "active_params_b" in m
-                else None
-            ),
-            gpu_peak_tflops=float(m.get("gpu_peak_tflops", 0.0)),
-            gpu_peak_bandwidth_gb_s=float(m.get("gpu_peak_bandwidth_gb_s", 0.0)),
-            num_gpus=int(m.get("num_gpus", 1)),
-        ))
+        models.append(
+            ModelConfig(
+                name=m["name"],
+                engine=m.get("engine"),
+                provider=m.get("provider"),
+                temperature=float(m["temperature"]) if "temperature" in m else None,
+                max_tokens=int(m["max_tokens"]) if "max_tokens" in m else None,
+                param_count_b=float(m.get("param_count_b", 0.0)),
+                active_params_b=(
+                    float(m["active_params_b"]) if "active_params_b" in m else None
+                ),
+                gpu_peak_tflops=float(m.get("gpu_peak_tflops", 0.0)),
+                gpu_peak_bandwidth_gb_s=float(m.get("gpu_peak_bandwidth_gb_s", 0.0)),
+                num_gpus=int(m.get("num_gpus", 1)),
+            )
+        )
 
     # Parse [[benchmarks]]
     benchmarks_raw = raw.get("benchmarks", [])
     if not benchmarks_raw:
-        raise EvalConfigError(
-            "Config must define at least one [[benchmarks]] entry"
-        )
+        raise EvalConfigError("Config must define at least one [[benchmarks]] entry")
 
     benchmarks: List[BenchmarkConfig] = []
     for b in benchmarks_raw:
         if not b.get("name"):
-            raise EvalConfigError(
-                "Each [[benchmarks]] entry must have a 'name' field"
-            )
+            raise EvalConfigError("Each [[benchmarks]] entry must have a 'name' field")
 
         backend = b.get("backend", "jarvis-direct")
         if backend not in VALID_BACKENDS:
@@ -166,18 +179,20 @@ def load_eval_config(path: str | Path) -> EvalSuiteConfig:
             logger.warning("Unknown benchmark name: '%s'", bench_name)
 
         tools_raw = b.get("tools", [])
-        benchmarks.append(BenchmarkConfig(
-            name=bench_name,
-            backend=backend,
-            max_samples=int(b["max_samples"]) if "max_samples" in b else None,
-            split=b.get("split"),
-            agent=b.get("agent"),
-            tools=list(tools_raw),
-            judge_model=b.get("judge_model"),
-            temperature=float(b["temperature"]) if "temperature" in b else None,
-            max_tokens=int(b["max_tokens"]) if "max_tokens" in b else None,
-            subset=b.get("subset"),
-        ))
+        benchmarks.append(
+            BenchmarkConfig(
+                name=bench_name,
+                backend=backend,
+                max_samples=int(b["max_samples"]) if "max_samples" in b else None,
+                split=b.get("split"),
+                agent=b.get("agent"),
+                tools=list(tools_raw),
+                judge_model=b.get("judge_model"),
+                temperature=float(b["temperature"]) if "temperature" in b else None,
+                max_tokens=int(b["max_tokens"]) if "max_tokens" in b else None,
+                subset=b.get("subset"),
+            )
+        )
 
     return EvalSuiteConfig(
         meta=meta,
@@ -245,35 +260,37 @@ def expand_suite(suite: EvalSuiteConfig) -> List[RunConfig]:
             # Judge engine: suite.judge.engine > "cloud"
             judge_engine = suite.judge.engine or "cloud"
 
-            configs.append(RunConfig(
-                benchmark=bench.name,
-                backend=bench.backend,
-                model=model.name,
-                max_samples=bench.max_samples,
-                max_workers=suite.run.max_workers,
-                temperature=temperature,
-                max_tokens=max_tokens,
-                judge_model=judge_model,
-                judge_engine=judge_engine,
-                engine_key=model.engine,
-                agent_name=bench.agent,
-                tools=list(bench.tools),
-                output_path=output_path,
-                seed=suite.run.seed,
-                dataset_split=bench.split,
-                dataset_subset=bench.subset,
-                telemetry=suite.run.telemetry,
-                gpu_metrics=suite.run.gpu_metrics,
-                metadata=model_meta,
-                warmup_samples=suite.run.warmup_samples,
-                wandb_project=suite.run.wandb_project,
-                wandb_entity=suite.run.wandb_entity,
-                wandb_tags=suite.run.wandb_tags,
-                wandb_group=suite.run.wandb_group,
-                sheets_spreadsheet_id=suite.run.sheets_spreadsheet_id,
-                sheets_worksheet=suite.run.sheets_worksheet,
-                sheets_credentials_path=suite.run.sheets_credentials_path,
-            ))
+            configs.append(
+                RunConfig(
+                    benchmark=bench.name,
+                    backend=bench.backend,
+                    model=model.name,
+                    max_samples=bench.max_samples,
+                    max_workers=suite.run.max_workers,
+                    temperature=temperature,
+                    max_tokens=max_tokens,
+                    judge_model=judge_model,
+                    judge_engine=judge_engine,
+                    engine_key=model.engine,
+                    agent_name=bench.agent,
+                    tools=list(bench.tools),
+                    output_path=output_path,
+                    seed=suite.run.seed,
+                    dataset_split=bench.split,
+                    dataset_subset=bench.subset,
+                    telemetry=suite.run.telemetry,
+                    gpu_metrics=suite.run.gpu_metrics,
+                    metadata=model_meta,
+                    warmup_samples=suite.run.warmup_samples,
+                    wandb_project=suite.run.wandb_project,
+                    wandb_entity=suite.run.wandb_entity,
+                    wandb_tags=suite.run.wandb_tags,
+                    wandb_group=suite.run.wandb_group,
+                    sheets_spreadsheet_id=suite.run.sheets_spreadsheet_id,
+                    sheets_worksheet=suite.run.sheets_worksheet,
+                    sheets_credentials_path=suite.run.sheets_credentials_path,
+                )
+            )
 
     return configs
 

src/openjarvis/evals/core/dataset.py

@@ -34,7 +34,8 @@ class DatasetProvider(ABC):
         """Return the number of loaded records."""
 
     def create_task_env(
-        self, record: EvalRecord,
+        self,
+        record: EvalRecord,
     ) -> Optional[AbstractContextManager]:
         """Return a task environment context manager, or None."""
         return None

src/openjarvis/evals/core/display.py

@@ -125,8 +125,10 @@ def print_metrics_table(console: Console, summary: RunSummary) -> None:
     _add_metric_row(table, "Power (W)", summary.power_stats)
     _add_metric_row(table, "GPU Util (%)", summary.gpu_utilization_stats, decimals=1)
     _add_metric_row(
-        table, "Energy/OutTok (J)",
-        summary.energy_per_output_token_stats, decimals=6,
+        table,
+        "Energy/OutTok (J)",
+        summary.energy_per_output_token_stats,
+        decimals=6,
     )
     _add_metric_row(table, "Throughput/Watt", summary.throughput_per_watt_stats)
     _add_metric_row(table, "MFU (%)", summary.mfu_stats, decimals=2)
@@ -203,35 +205,43 @@ def print_accuracy_panel(console: Console, summary: RunSummary) -> None:
         lines.append(f"  {subj:<20s} {acc:.1%}  ({correct}/{scored})")
     body = "\n".join(lines)
     panel = Panel(
-        body, title="[bold]Accuracy[/bold]",
-        border_style="green", expand=False,
+        body,
+        title="[bold]Accuracy[/bold]",
+        border_style="green",
+        expand=False,
     )
     console.print(panel)
 
 
 def print_latency_table(console: Console, summary: RunSummary) -> None:
     """Print latency, throughput, and token stats table."""
-    table = _stats_table("Latency & Throughput", [
-        ("Latency (s)", summary.latency_stats, 2),
-        ("TTFT (s)", summary.ttft_stats, 3),
-        ("Throughput (tok/s)", summary.throughput_stats, 1),
-        ("Avg Input Tokens", summary.input_token_stats, 1),
-        ("Avg Output Tokens", summary.output_token_stats, 1),
-    ])
+    table = _stats_table(
+        "Latency & Throughput",
+        [
+            ("Latency (s)", summary.latency_stats, 2),
+            ("TTFT (s)", summary.ttft_stats, 3),
+            ("Throughput (tok/s)", summary.throughput_stats, 1),
+            ("Avg Input Tokens", summary.input_token_stats, 1),
+            ("Avg Output Tokens", summary.output_token_stats, 1),
+        ],
+    )
     if table.row_count > 0:
         console.print(table)
 
 
 def print_energy_table(console: Console, summary: RunSummary) -> None:
     """Print energy, efficiency, and IPJ/IPW table."""
-    table = _stats_table("Energy & Efficiency", [
-        ("Energy (J)", summary.energy_stats, 1),
-        ("Power (W)", summary.power_stats, 1),
-        ("GPU Util (%)", summary.gpu_utilization_stats, 1),
-        ("Energy/OutTok (J)", summary.energy_per_output_token_stats, 6),
-        ("MFU (%)", summary.mfu_stats, 3),
-        ("MBU (%)", summary.mbu_stats, 3),
-    ])
+    table = _stats_table(
+        "Energy & Efficiency",
+        [
+            ("Energy (J)", summary.energy_stats, 1),
+            ("Power (W)", summary.power_stats, 1),
+            ("GPU Util (%)", summary.gpu_utilization_stats, 1),
+            ("Energy/OutTok (J)", summary.energy_per_output_token_stats, 6),
+            ("MFU (%)", summary.mfu_stats, 3),
+            ("MBU (%)", summary.mbu_stats, 3),
+        ],
+    )
     if table.row_count > 0:
         console.print(table)
     # Headline: IPW, IPJ, Total Energy
@@ -258,9 +268,7 @@ def print_trace_summary(console: Console, summary: RunSummary) -> None:
         return
     total_steps = sum(s.get("count", 0) for s in sts.values())
     avg_per_sample = (
-        total_steps / summary.scored_samples
-        if summary.scored_samples > 0
-        else 0
+        total_steps / summary.scored_samples if summary.scored_samples > 0 else 0
     )
 
     table = Table(
@@ -270,8 +278,7 @@ def print_trace_summary(console: Console, summary: RunSummary) -> None:
         border_style="bright_blue",
         title_style="bold cyan",
         caption=(
-            f"Total Steps: {total_steps}"
-            f"  |  Avg Steps/Sample: {avg_per_sample:.1f}"
+            f"Total Steps: {total_steps}  |  Avg Steps/Sample: {avg_per_sample:.1f}"
         ),
     )
     table.add_column("Step Type", style="cyan", no_wrap=True)

src/openjarvis/evals/core/environment.py

@@ -34,7 +34,8 @@ class EnvironmentProvider(ABC):
 
     @abstractmethod
     def validate(
-        self, record: EvalRecord,
+        self,
+        record: EvalRecord,
     ) -> Tuple[bool, Dict[str, Any]]:
         """Check environment state against expected outcome.
 

src/openjarvis/evals/core/export.py

@@ -36,12 +36,10 @@ def _compute_efficiency(
     resolved = sum(1 for t in scored if t.is_resolved is True)
     accuracy = resolved / len(scored) if scored else None
     gpu_powers = [
-        t.avg_gpu_power_watts for t in traces
-        if t.avg_gpu_power_watts is not None
+        t.avg_gpu_power_watts for t in traces if t.avg_gpu_power_watts is not None
     ]
     cpu_powers = [
-        t.avg_cpu_power_watts for t in traces
-        if t.avg_cpu_power_watts is not None
+        t.avg_cpu_power_watts for t in traces if t.avg_cpu_power_watts is not None
     ]
     avg_gpu_power = statistics.mean(gpu_powers) if gpu_powers else None
     avg_cpu_power = statistics.mean(cpu_powers) if cpu_powers else None
@@ -51,16 +49,8 @@ def _compute_efficiency(
         "total_cpu_energy_joules": total_cpu_energy,
         "avg_gpu_power_watts": avg_gpu_power,
         "avg_cpu_power_watts": avg_cpu_power,
-        "ipj": (
-            accuracy / total_gpu_energy
-            if accuracy and total_gpu_energy
-            else None
-        ),
-        "ipw": (
-            accuracy / avg_gpu_power
-            if accuracy and avg_gpu_power
-            else None
-        ),
+        "ipj": (accuracy / total_gpu_energy if accuracy and total_gpu_energy else None),
+        "ipw": (accuracy / avg_gpu_power if accuracy and avg_gpu_power else None),
     }
 
 
@@ -77,14 +67,15 @@ def _compute_normalized(
 
     trim_count = max(1, math.floor(n * 0.05))
     sorted_traces = sorted(traces, key=lambda t: t.total_wall_clock_s)
-    trimmed = sorted_traces[trim_count: n - trim_count]
+    trimmed = sorted_traces[trim_count : n - trim_count]
 
     if not trimmed:
         return None
 
     # Recompute aggregate energy on trimmed set
     gpu_energy_values = [
-        t.total_gpu_energy_joules for t in trimmed
+        t.total_gpu_energy_joules
+        for t in trimmed
         if t.total_gpu_energy_joules is not None
     ]
     total_gpu_energy = sum(gpu_energy_values) if gpu_energy_values else None
@@ -92,7 +83,8 @@ def _compute_normalized(
     cpu_energy_values: list[float] = []
     for trace in trimmed:
         cpu_vals = [
-            turn.cpu_energy_joules for turn in trace.turns
+            turn.cpu_energy_joules
+            for turn in trace.turns
             if turn.cpu_energy_joules is not None
         ]
         if cpu_vals:
@@ -188,6 +180,7 @@ def _hardware_info_dict() -> dict[str, Any]:
     """Detect hardware and return a JSON-serializable dict."""
     try:
         from openjarvis.core.config import detect_hardware
+
         hw = detect_hardware()
         info: dict[str, Any] = {
             "platform": hw.platform,
@@ -237,7 +230,8 @@ def export_summary_json(
     total_wall_clock_s = sum(t.total_wall_clock_s for t in traces)
 
     gpu_energy_values = [
-        t.total_gpu_energy_joules for t in traces
+        t.total_gpu_energy_joules
+        for t in traces
         if t.total_gpu_energy_joules is not None
     ]
     total_gpu_energy = sum(gpu_energy_values) if gpu_energy_values else None
@@ -245,7 +239,8 @@ def export_summary_json(
     cpu_energy_values: list[float] = []
     for trace in traces:
         cpu_vals = [
-            turn.cpu_energy_joules for turn in trace.turns
+            turn.cpu_energy_joules
+            for turn in trace.turns
             if turn.cpu_energy_joules is not None
         ]
         if cpu_vals:
@@ -255,10 +250,7 @@ def export_summary_json(
     resolved = sum(1 for t in traces if t.is_resolved is True)
     unresolved = sum(1 for t in traces if t.is_resolved is False)
 
-    cost_values = [
-        t.total_cost_usd for t in traces
-        if t.total_cost_usd is not None
-    ]
+    cost_values = [t.total_cost_usd for t in traces if t.total_cost_usd is not None]
     total_cost = sum(cost_values) if cost_values else None
 
     avg_turns = total_turns / total_queries if total_queries > 0 else 0
@@ -309,9 +301,7 @@ def export_summary_json(
     }
 
     accuracy = (
-        resolved / (resolved + unresolved)
-        if (resolved + unresolved) > 0
-        else None
+        resolved / (resolved + unresolved) if (resolved + unresolved) > 0 else None
     )
 
     efficiency = _compute_efficiency(traces, total_gpu_energy, total_cpu_energy)
@@ -336,7 +326,8 @@ def export_summary_json(
                 entry = action_totals[atype]
                 entry["count"] += 1
                 entry["total_duration_s"] += action.get(
-                    "duration_s", 0.0,
+                    "duration_s",
+                    0.0,
                 )
                 gpu_e = action.get("gpu_energy_joules")
                 if gpu_e is not None:

src/openjarvis/evals/core/runner.py

@@ -102,6 +102,7 @@ class EvalRunner:
         # default iter_episodes() that wraps each record in its own episode,
         # so hasattr() is always True — we must check for a real override.
         from openjarvis.evals.core.dataset import DatasetProvider as _DP
+
         try:
             _overrides_episodes = (
                 type(self._dataset).iter_episodes is not _DP.iter_episodes
@@ -120,18 +121,20 @@ class EvalRunner:
         # Detect if dataset provides task environments (e.g. PinchBench)
         try:
             self._has_task_env = (
-                type(self._dataset).create_task_env
-                is not _DP.create_task_env
+                type(self._dataset).create_task_env is not _DP.create_task_env
             )
         except AttributeError:
             self._has_task_env = False
 
         records = list(self._dataset.iter_records())
         LOGGER.info(
-            "Running %s: %d samples, backend=%s, model=%s, workers=%d, "
-            "episode_mode=%s",
-            cfg.benchmark, len(records), cfg.backend, cfg.model,
-            cfg.max_workers, cfg.episode_mode,
+            "Running %s: %d samples, backend=%s, model=%s, workers=%d, episode_mode=%s",
+            cfg.benchmark,
+            len(records),
+            cfg.backend,
+            cfg.model,
+            cfg.max_workers,
+            cfg.episode_mode,
         )
 
         # --- Warmup phase (discard results) ---
@@ -155,7 +158,8 @@ class EvalRunner:
             except Exception as exc:
                 LOGGER.warning(
                     "Tracker %s.on_run_start failed: %s",
-                    type(tracker).__name__, exc,
+                    type(tracker).__name__,
+                    exc,
                 )
 
         total = len(records)
@@ -173,9 +177,7 @@ class EvalRunner:
                         progress_callback(len(self._results), total)
             else:
                 with ThreadPoolExecutor(max_workers=cfg.max_workers) as pool:
-                    futures = {
-                        pool.submit(self._process_one, r): r for r in records
-                    }
+                    futures = {pool.submit(self._process_one, r): r for r in records}
                     for future in as_completed(futures):
                         result = future.result()
                         self._results.append(result)
@@ -197,14 +199,16 @@ class EvalRunner:
             except Exception as exc:
                 LOGGER.warning(
                     "Tracker %s.on_summary failed: %s",
-                    type(tracker).__name__, exc,
+                    type(tracker).__name__,
+                    exc,
                 )
             try:
                 tracker.on_run_end()
             except Exception as exc:
                 LOGGER.warning(
                     "Tracker %s.on_run_end failed: %s",
-                    type(tracker).__name__, exc,
+                    type(tracker).__name__,
+                    exc,
                 )
 
         # Write summary JSON alongside JSONL
@@ -253,6 +257,7 @@ class EvalRunner:
 
             if getattr(self, "_has_task_env", False):
                 from contextlib import nullcontext
+
                 task_env = self._dataset.create_task_env(record)
                 ctx = task_env if task_env is not None else nullcontext()
                 with ctx:
@@ -261,22 +266,23 @@ class EvalRunner:
                         **gen_kwargs,
                     )
                     full = full or {}
-                    all_tool_results = list(full.get(
-                        "tool_results", [],
-                    ))
+                    all_tool_results = list(
+                        full.get(
+                            "tool_results",
+                            [],
+                        )
+                    )
 
                     # Multi-session: execute remaining sessions
                     sessions = record.metadata.get("sessions", [])
-                    if (
-                        record.metadata.get("multi_session")
-                        and len(sessions) > 1
-                    ):
+                    if record.metadata.get("multi_session") and len(sessions) > 1:
                         for session in sessions[1:]:
                             prompt = session.get("prompt", "")
                             if not prompt:
                                 continue
                             sfull = self._backend.generate_full(
-                                prompt, **gen_kwargs,
+                                prompt,
+                                **gen_kwargs,
                             )
                             sfull = sfull or {}
                             all_tool_results.extend(
@@ -287,7 +293,8 @@ class EvalRunner:
                     # Score INSIDE context so workspace files still exist
                     content = full.get("content", "")
                     is_correct, scoring_meta = self._scorer.score(
-                        record, content,
+                        record,
+                        content,
                     )
             else:
                 full = self._backend.generate_full(
@@ -297,7 +304,8 @@ class EvalRunner:
                 full = full or {}
                 content = full.get("content", "")
                 is_correct, scoring_meta = self._scorer.score(
-                    record, content,
+                    record,
+                    content,
                 )
 
             usage = full.get("usage", {})
@@ -340,9 +348,7 @@ class EvalRunner:
 
             # Extract derived and ITL metrics from _telemetry dict
             _telem = full.get("_telemetry", {})
-            energy_per_out_tok = _telem.get(
-                "energy_per_output_token_joules", 0.0
-            )
+            energy_per_out_tok = _telem.get("energy_per_output_token_joules", 0.0)
             throughput_per_w = _telem.get("throughput_per_watt", 0.0)
             mean_itl = _telem.get("mean_itl_ms", 0.0)
 
@@ -406,9 +412,9 @@ class EvalRunner:
         # default implementation that returns None, so hasattr() is always True —
         # we must check for a real override to avoid calling env.reset() on None.
         from openjarvis.evals.core.dataset import DatasetProvider
+
         has_task_env = (
-            type(self._dataset).create_task_env
-            is not DatasetProvider.create_task_env
+            type(self._dataset).create_task_env is not DatasetProvider.create_task_env
         )
 
         for episode in self._dataset.iter_episodes():
@@ -417,12 +423,14 @@ class EvalRunner:
             for record in episode:
                 if has_task_env:
                     result = self._process_interactive(
-                        record, successful_examples,
+                        record,
+                        successful_examples,
                     )
                 else:
                     # Inject prior examples into prompt, then single-shot
                     augmented = self._inject_examples(
-                        record, successful_examples,
+                        record,
+                        successful_examples,
                     )
                     result = self._process_one(augmented)
 
@@ -437,9 +445,13 @@ class EvalRunner:
                         "answer": result.model_answer,
                     }
                     # Attach full interaction history if recorded
-                    interaction = result.scoring_metadata.get(
-                        "_interaction_history",
-                    ) if result.scoring_metadata else None
+                    interaction = (
+                        result.scoring_metadata.get(
+                            "_interaction_history",
+                        )
+                        if result.scoring_metadata
+                        else None
+                    )
                     if interaction:
                         example["interaction_history"] = interaction
                     successful_examples.append(example)
@@ -482,8 +494,7 @@ class EvalRunner:
             else:
                 # Fallback: problem + answer summary
                 example_text += (
-                    f"Task: {ex['problem'][:800]}\n"
-                    f"Solution: {ex['answer'][:800]}\n\n"
+                    f"Task: {ex['problem'][:800]}\nSolution: {ex['answer'][:800]}\n\n"
                 )
         example_text += "## Current Task\n\n"
 
@@ -549,9 +560,7 @@ class EvalRunner:
             # PreviousSampleUtilizationCallback which replays the complete
             # chat history from prior successful sessions.
             if prior_examples:
-                examples_text = (
-                    "Here are examples of previously completed tasks:\n\n"
-                )
+                examples_text = "Here are examples of previously completed tasks:\n\n"
                 for i, ex in enumerate(prior_examples, 1):
                     history = ex.get("interaction_history")
                     if history and isinstance(history, list):
@@ -573,10 +582,12 @@ class EvalRunner:
                             f"Solution: {ex['answer'][:800]}\n\n"
                         )
                 messages.append({"role": "user", "content": examples_text})
-                messages.append({
-                    "role": "assistant",
-                    "content": "I've reviewed the examples. Ready.",
-                })
+                messages.append(
+                    {
+                        "role": "assistant",
+                        "content": "I've reviewed the examples. Ready.",
+                    }
+                )
 
             # Initial task message — always use the full problem text which
             # contains the system prompt, schema, AND task instruction.
@@ -648,7 +659,8 @@ class EvalRunner:
         except Exception as exc:
             LOGGER.error(
                 "Interactive processing failed for %s: %s",
-                record.record_id, exc,
+                record.record_id,
+                exc,
             )
             return EvalResult(
                 record_id=record.record_id,
@@ -720,15 +732,18 @@ class EvalRunner:
         except Exception as exc:
             LOGGER.error(
                 "Failed to serialize result %s to JSON: %s — writing error record",
-                result.record_id, exc,
+                result.record_id,
+                exc,
+            )
+            line = json.dumps(
+                {
+                    "record_id": result.record_id,
+                    "benchmark": self._config.benchmark,
+                    "model": self._config.model,
+                    "is_correct": result.is_correct,
+                    "error": f"serialization_error: {exc}",
+                }
             )
-            line = json.dumps({
-                "record_id": result.record_id,
-                "benchmark": self._config.benchmark,
-                "model": self._config.model,
-                "is_correct": result.is_correct,
-                "error": f"serialization_error: {exc}",
-            })
         self._output_file.write(line + "\n")
         self._output_file.flush()
 
@@ -739,7 +754,8 @@ class EvalRunner:
             except Exception as exc:
                 LOGGER.warning(
                     "Tracker %s.on_result failed: %s",
-                    type(tracker).__name__, exc,
+                    type(tracker).__name__,
+                    exc,
                 )
 
     def _resolve_output_path(self) -> Optional[Path]:
@@ -802,12 +818,10 @@ class EvalRunner:
         energy_vals = [r.energy_joules for r in results if r.energy_joules > 0]
         power_vals = [r.power_watts for r in results if r.power_watts > 0]
         gpu_util_vals = [
-            r.gpu_utilization_pct for r in results
-            if r.gpu_utilization_pct > 0
+            r.gpu_utilization_pct for r in results if r.gpu_utilization_pct > 0
         ]
         throughput_vals = [
-            r.throughput_tok_per_sec for r in results
-            if r.throughput_tok_per_sec > 0
+            r.throughput_tok_per_sec for r in results if r.throughput_tok_per_sec > 0
         ]
         mfu_vals = [r.mfu_pct for r in results if r.mfu_pct > 0]
         mbu_vals = [r.mbu_pct for r in results if r.mbu_pct > 0]
@@ -818,15 +832,11 @@ class EvalRunner:
             for r in results
             if r.energy_per_output_token_joules > 0
         ]
-        tpw_vals = [
-            r.throughput_per_watt
-            for r in results if r.throughput_per_watt > 0
-        ]
+        tpw_vals = [r.throughput_per_watt for r in results if r.throughput_per_watt > 0]
         itl_vals = [r.mean_itl_ms for r in results if r.mean_itl_ms > 0]
         input_tok_vals = [r.prompt_tokens for r in results if r.prompt_tokens > 0]
         output_tok_vals = [
-            r.completion_tokens for r in results
-            if r.completion_tokens > 0
+            r.completion_tokens for r in results if r.completion_tokens > 0
         ]
 
         total_energy = sum(r.energy_joules for r in results)
@@ -839,19 +849,14 @@ class EvalRunner:
             "accuracy": round(accuracy, 4),
             "total_energy_joules": round(total_energy, 6),
             "avg_power_watts": round(avg_power, 4),
-            "ipj": (
-                round(accuracy / total_energy, 6)
-                if total_energy > 0 else None
-            ),
-            "ipw": (
-                round(accuracy / avg_power, 6)
-                if avg_power > 0 else None
-            ),
+            "ipj": (round(accuracy / total_energy, 6) if total_energy > 0 else None),
+            "ipw": (round(accuracy / avg_power, 6) if avg_power > 0 else None),
         }
 
         # Compute normalized statistics (trim 5% outliers by latency)
         normalized_stats, normalized_eff = _compute_normalized_stats(
-            results, accuracy,
+            results,
+            accuracy,
         )
 
         return RunSummary(
@@ -911,7 +916,7 @@ def _compute_normalized_stats(
 
     trim_count = max(1, math.floor(n * 0.05))
     sorted_results = sorted(results, key=lambda r: r.latency_seconds)
-    trimmed = sorted_results[trim_count: n - trim_count]
+    trimmed = sorted_results[trim_count : n - trim_count]
 
     if not trimmed:
         return None, None
@@ -924,8 +929,7 @@ def _compute_normalized_stats(
     t_energy_vals = [r.energy_joules for r in trimmed if r.energy_joules > 0]
     t_power_vals = [r.power_watts for r in trimmed if r.power_watts > 0]
     t_throughput_vals = [
-        r.throughput_tok_per_sec for r in trimmed
-        if r.throughput_tok_per_sec > 0
+        r.throughput_tok_per_sec for r in trimmed if r.throughput_tok_per_sec > 0
     ]
     t_mbu_vals = [r.mbu_pct for r in trimmed if r.mbu_pct > 0]
 
@@ -951,14 +955,8 @@ def _compute_normalized_stats(
         "accuracy": round(t_accuracy, 4),
         "total_energy_joules": round(t_total_energy, 6),
         "avg_power_watts": round(t_avg_power, 4),
-        "ipj": (
-            round(t_accuracy / t_total_energy, 6)
-            if t_total_energy > 0 else None
-        ),
-        "ipw": (
-            round(t_accuracy / t_avg_power, 6)
-            if t_avg_power > 0 else None
-        ),
+        "ipj": (round(t_accuracy / t_total_energy, 6) if t_total_energy > 0 else None),
+        "ipw": (round(t_accuracy / t_avg_power, 6) if t_avg_power > 0 else None),
     }
 
     return norm_stats, norm_eff

src/openjarvis/evals/core/scorer.py

@@ -16,7 +16,9 @@ class Scorer(ABC):
 
     @abstractmethod
     def score(
-        self, record: EvalRecord, model_answer: str,
+        self,
+        record: EvalRecord,
+        model_answer: str,
     ) -> Tuple[Optional[bool], Dict[str, Any]]:
         """Score a model answer against the reference.
 

src/openjarvis/evals/core/trace.py

@@ -115,8 +115,7 @@ class QueryTrace:
     @property
     def total_gpu_energy_joules(self) -> Optional[float]:
         values = [
-            t.gpu_energy_joules for t in self.turns
-            if t.gpu_energy_joules is not None
+            t.gpu_energy_joules for t in self.turns if t.gpu_energy_joules is not None
         ]
         if values:
             return sum(values)
@@ -125,8 +124,7 @@ class QueryTrace:
     @property
     def total_cpu_energy_joules(self) -> Optional[float]:
         values = [
-            t.cpu_energy_joules for t in self.turns
-            if t.cpu_energy_joules is not None
+            t.cpu_energy_joules for t in self.turns if t.cpu_energy_joules is not None
         ]
         if values:
             return sum(values)
@@ -146,7 +144,8 @@ class QueryTrace:
     def avg_gpu_power_watts(self) -> Optional[float]:
         """Mean GPU power across turns; falls back to query-level power."""
         values = [
-            t.gpu_power_avg_watts for t in self.turns
+            t.gpu_power_avg_watts
+            for t in self.turns
             if t.gpu_power_avg_watts is not None
         ]
         if values:
@@ -157,7 +156,8 @@ class QueryTrace:
     def avg_cpu_power_watts(self) -> Optional[float]:
         """Mean CPU power across turns; falls back to query-level power."""
         values = [
-            t.cpu_power_avg_watts for t in self.turns
+            t.cpu_power_avg_watts
+            for t in self.turns
             if t.cpu_power_avg_watts is not None
         ]
         if values:
@@ -246,31 +246,33 @@ class QueryTrace:
 
         rows = []
         for trace in traces:
-            rows.append({
-                "query_id": trace.query_id,
-                "workload_type": trace.workload_type,
-                "query_text": trace.query_text,
-                "response_text": trace.response_text,
-                "num_turns": trace.num_turns,
-                "total_input_tokens": trace.total_input_tokens,
-                "total_output_tokens": trace.total_output_tokens,
-                "total_tool_calls": trace.total_tool_calls,
-                "total_wall_clock_s": trace.total_wall_clock_s,
-                "total_gpu_energy_joules": trace.total_gpu_energy_joules,
-                "total_cpu_energy_joules": trace.total_cpu_energy_joules,
-                "total_tokens": trace.total_tokens,
-                "total_cost_usd": trace.total_cost_usd,
-                "avg_gpu_power_watts": trace.avg_gpu_power_watts,
-                "avg_cpu_power_watts": trace.avg_cpu_power_watts,
-                "throughput_tokens_per_sec": trace.throughput_tokens_per_sec,
-                "energy_per_token_joules": trace.energy_per_token_joules,
-                "completed": trace.completed,
-                "timed_out": trace.timed_out,
-                "is_resolved": trace.is_resolved,
-                "query_mbu_avg_pct": trace.query_mbu_avg_pct,
-                "query_mbu_max_pct": trace.query_mbu_max_pct,
-                "trace_json": json.dumps(trace.to_dict()),
-            })
+            rows.append(
+                {
+                    "query_id": trace.query_id,
+                    "workload_type": trace.workload_type,
+                    "query_text": trace.query_text,
+                    "response_text": trace.response_text,
+                    "num_turns": trace.num_turns,
+                    "total_input_tokens": trace.total_input_tokens,
+                    "total_output_tokens": trace.total_output_tokens,
+                    "total_tool_calls": trace.total_tool_calls,
+                    "total_wall_clock_s": trace.total_wall_clock_s,
+                    "total_gpu_energy_joules": trace.total_gpu_energy_joules,
+                    "total_cpu_energy_joules": trace.total_cpu_energy_joules,
+                    "total_tokens": trace.total_tokens,
+                    "total_cost_usd": trace.total_cost_usd,
+                    "avg_gpu_power_watts": trace.avg_gpu_power_watts,
+                    "avg_cpu_power_watts": trace.avg_cpu_power_watts,
+                    "throughput_tokens_per_sec": trace.throughput_tokens_per_sec,
+                    "energy_per_token_joules": trace.energy_per_token_joules,
+                    "completed": trace.completed,
+                    "timed_out": trace.timed_out,
+                    "is_resolved": trace.is_resolved,
+                    "query_mbu_avg_pct": trace.query_mbu_avg_pct,
+                    "query_mbu_max_pct": trace.query_mbu_max_pct,
+                    "trace_json": json.dumps(trace.to_dict()),
+                }
+            )
         return Dataset.from_list(rows)
 
 

src/openjarvis/evals/datasets/ama_bench.py

@@ -130,7 +130,8 @@ class AMABenchDataset(DatasetProvider):
         return [dict(row) for row in rows]
 
     def _row_to_episode(
-        self, row: Dict[str, Any],
+        self,
+        row: Dict[str, Any],
     ) -> List[EvalRecord]:
         """Convert one AMA-Bench episode row to EvalRecord(s)."""
         episode_id = str(row.get("episode_id", "")).strip()
@@ -139,11 +140,15 @@ class AMABenchDataset(DatasetProvider):
 
         trajectory = row.get("trajectory")
         if not isinstance(trajectory, list):
-            raise ValueError(f"AMA-Bench episode {episode_id}: trajectory must be a list")
+            raise ValueError(
+                f"AMA-Bench episode {episode_id}: trajectory must be a list"
+            )
 
         qa_pairs = row.get("qa_pairs")
         if not isinstance(qa_pairs, list) or not qa_pairs:
-            raise ValueError(f"AMA-Bench episode {episode_id}: qa_pairs must be a non-empty list")
+            raise ValueError(
+                f"AMA-Bench episode {episode_id}: qa_pairs must be a non-empty list"
+            )
 
         task = str(row.get("task", "")).strip()
         domain = str(row.get("domain", "")).strip() or "general"
@@ -159,12 +164,15 @@ class AMABenchDataset(DatasetProvider):
         if len(trajectory_text) > max_chars:
             original_len = len(trajectory_text)
             trajectory_text = self._truncate_trajectory_text(
-                trajectory_text, max_chars,
+                trajectory_text,
+                max_chars,
             )
             LOGGER.info(
                 "AMA-Bench episode %s: trajectory truncated from %d to %d chars "
                 "(first 50%% + last 50%% of budget kept per Appendix B)",
-                episode_id, original_len, len(trajectory_text),
+                episode_id,
+                original_len,
+                len(trajectory_text),
             )
 
         records: List[EvalRecord] = []
@@ -194,31 +202,33 @@ class AMABenchDataset(DatasetProvider):
                 f"## Question\n{question}"
             )
 
-            records.append(EvalRecord(
-                record_id=(
-                    f"ama-{episode_id}-{q_uuid}"
-                    if q_uuid
-                    else f"ama-{episode_id}-q{question_index}"
-                ),
-                problem=problem,
-                reference=answer,
-                category="agentic",
-                subject=subject,
-                metadata={
-                    "episode_id": episode_id,
-                    "task": task,
-                    "task_type": task_type,
-                    "source": source,
-                    "domain": domain,
-                    "success": success,
-                    "num_turns": num_turns,
-                    "total_tokens": total_tokens,
-                    "question_index": question_index,
-                    "question_uuid": q_uuid,
-                    "question_type": q_type,
-                    "capability": subject,
-                },
-            ))
+            records.append(
+                EvalRecord(
+                    record_id=(
+                        f"ama-{episode_id}-{q_uuid}"
+                        if q_uuid
+                        else f"ama-{episode_id}-q{question_index}"
+                    ),
+                    problem=problem,
+                    reference=answer,
+                    category="agentic",
+                    subject=subject,
+                    metadata={
+                        "episode_id": episode_id,
+                        "task": task,
+                        "task_type": task_type,
+                        "source": source,
+                        "domain": domain,
+                        "success": success,
+                        "num_turns": num_turns,
+                        "total_tokens": total_tokens,
+                        "question_index": question_index,
+                        "question_uuid": q_uuid,
+                        "question_type": q_type,
+                        "capability": subject,
+                    },
+                )
+            )
 
         return records
 
@@ -240,7 +250,8 @@ class AMABenchDataset(DatasetProvider):
 
     @staticmethod
     def _truncate_trajectory_text(
-        trajectory_text: str, max_chars: int,
+        trajectory_text: str,
+        max_chars: int,
     ) -> str:
         """Truncate formatted trajectory text by keeping first 50% + last 50%
         of the character budget, discarding the middle.
@@ -254,9 +265,7 @@ class AMABenchDataset(DatasetProvider):
         if budget_each <= 0:
             return trajectory_text[:max_chars]
         return (
-            trajectory_text[:budget_each]
-            + separator
-            + trajectory_text[-budget_each:]
+            trajectory_text[:budget_each] + separator + trajectory_text[-budget_each:]
         )
 
 

src/openjarvis/evals/datasets/browser_assistant.py

@@ -81,7 +81,10 @@ _EASY_TASKS: List[Dict[str, Any]] = [
     {
         "question": "How many attention heads does GPT-4 use (as reported in public documentation)?",
         "expected_facts": [
-            {"fact": "architecture details not publicly disclosed by OpenAI", "type": "semantic"},
+            {
+                "fact": "architecture details not publicly disclosed by OpenAI",
+                "type": "semantic",
+            },
         ],
     },
     {
@@ -116,9 +119,18 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
     {
         "question": "Compare vLLM and TensorRT-LLM for serving large language models.",
         "expected_facts": [
-            {"fact": "vLLM uses PagedAttention for memory efficiency", "type": "semantic"},
-            {"fact": "TensorRT-LLM optimizes for NVIDIA GPUs specifically", "type": "semantic"},
-            {"fact": "vLLM is easier to set up, TensorRT-LLM has higher throughput on supported hardware", "type": "semantic"},
+            {
+                "fact": "vLLM uses PagedAttention for memory efficiency",
+                "type": "semantic",
+            },
+            {
+                "fact": "TensorRT-LLM optimizes for NVIDIA GPUs specifically",
+                "type": "semantic",
+            },
+            {
+                "fact": "vLLM is easier to set up, TensorRT-LLM has higher throughput on supported hardware",
+                "type": "semantic",
+            },
         ],
     },
     {
@@ -133,8 +145,14 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
         "question": "Compare PostgreSQL and MySQL for JSON document storage.",
         "expected_facts": [
             {"fact": "PostgreSQL has JSONB with GIN indexes", "type": "semantic"},
-            {"fact": "MySQL has JSON type with generated columns for indexing", "type": "semantic"},
-            {"fact": "PostgreSQL JSONB is generally more feature-rich for JSON operations", "type": "semantic"},
+            {
+                "fact": "MySQL has JSON type with generated columns for indexing",
+                "type": "semantic",
+            },
+            {
+                "fact": "PostgreSQL JSONB is generally more feature-rich for JSON operations",
+                "type": "semantic",
+            },
         ],
     },
     {
@@ -142,15 +160,24 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
         "expected_facts": [
             {"fact": "Podman is daemonless", "type": "semantic"},
             {"fact": "Podman runs rootless by default", "type": "semantic"},
-            {"fact": "Docker uses a client-server architecture with dockerd", "type": "semantic"},
+            {
+                "fact": "Docker uses a client-server architecture with dockerd",
+                "type": "semantic",
+            },
         ],
     },
     {
         "question": "Compare Terraform and Pulumi for infrastructure as code.",
         "expected_facts": [
-            {"fact": "Terraform uses HCL, Pulumi uses general-purpose languages", "type": "semantic"},
+            {
+                "fact": "Terraform uses HCL, Pulumi uses general-purpose languages",
+                "type": "semantic",
+            },
             {"fact": "both support multiple cloud providers", "type": "semantic"},
-            {"fact": "Pulumi has native support for Python, TypeScript, Go, C#", "type": "semantic"},
+            {
+                "fact": "Pulumi has native support for Python, TypeScript, Go, C#",
+                "type": "semantic",
+            },
         ],
     },
     {
@@ -164,9 +191,15 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
     {
         "question": "Compare FastAPI, Flask, and Django for building REST APIs.",
         "expected_facts": [
-            {"fact": "FastAPI is async-first with automatic OpenAPI docs", "type": "semantic"},
+            {
+                "fact": "FastAPI is async-first with automatic OpenAPI docs",
+                "type": "semantic",
+            },
             {"fact": "Flask is lightweight and flexible", "type": "semantic"},
-            {"fact": "Django includes ORM, admin, and batteries-included approach", "type": "semantic"},
+            {
+                "fact": "Django includes ORM, admin, and batteries-included approach",
+                "type": "semantic",
+            },
         ],
     },
     {
@@ -187,33 +220,63 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "question": "What is the current state of the art for code generation benchmarks (HumanEval, MBPP)? Which models lead and what are their scores?",
         "expected_facts": [
             {"fact": "recent top models score 90%+ on HumanEval", "type": "semantic"},
-            {"fact": "MBPP scores are generally lower than HumanEval", "type": "semantic"},
+            {
+                "fact": "MBPP scores are generally lower than HumanEval",
+                "type": "semantic",
+            },
             {"fact": "mentions specific model names and scores", "type": "semantic"},
         ],
     },
     {
         "question": "Explain the trade-offs between different attention mechanisms: multi-head attention, grouped-query attention, and multi-query attention.",
         "expected_facts": [
-            {"fact": "MHA uses separate K,V heads per attention head", "type": "semantic"},
-            {"fact": "GQA groups multiple query heads to share K,V heads", "type": "semantic"},
-            {"fact": "MQA uses single K,V head for all query heads", "type": "semantic"},
+            {
+                "fact": "MHA uses separate K,V heads per attention head",
+                "type": "semantic",
+            },
+            {
+                "fact": "GQA groups multiple query heads to share K,V heads",
+                "type": "semantic",
+            },
+            {
+                "fact": "MQA uses single K,V head for all query heads",
+                "type": "semantic",
+            },
             {"fact": "GQA balances quality and inference speed", "type": "semantic"},
         ],
     },
     {
         "question": "What are the latest developments in mixture-of-experts (MoE) architectures for LLMs? Compare Mixtral, DeepSeek-V2, and Grok-1.",
         "expected_facts": [
-            {"fact": "Mixtral 8x7B routes to 2 of 8 experts per token", "type": "semantic"},
-            {"fact": "DeepSeek-V2 uses fine-grained expert segmentation", "type": "semantic"},
-            {"fact": "MoE reduces compute cost per token vs dense models", "type": "semantic"},
+            {
+                "fact": "Mixtral 8x7B routes to 2 of 8 experts per token",
+                "type": "semantic",
+            },
+            {
+                "fact": "DeepSeek-V2 uses fine-grained expert segmentation",
+                "type": "semantic",
+            },
+            {
+                "fact": "MoE reduces compute cost per token vs dense models",
+                "type": "semantic",
+            },
         ],
     },
     {
         "question": "How do different quantization methods (GPTQ, AWQ, GGUF/GGML, bitsandbytes) compare for LLM inference?",
         "expected_facts": [
-            {"fact": "GPTQ uses post-training quantization with calibration data", "type": "semantic"},
-            {"fact": "AWQ preserves salient weights for better quality", "type": "semantic"},
-            {"fact": "GGUF is the llama.cpp format for CPU and mixed inference", "type": "semantic"},
+            {
+                "fact": "GPTQ uses post-training quantization with calibration data",
+                "type": "semantic",
+            },
+            {
+                "fact": "AWQ preserves salient weights for better quality",
+                "type": "semantic",
+            },
+            {
+                "fact": "GGUF is the llama.cpp format for CPU and mixed inference",
+                "type": "semantic",
+            },
             {"fact": "bitsandbytes supports QLoRA for fine-tuning", "type": "semantic"},
         ],
     },
@@ -221,17 +284,35 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "question": "What are the security implications of running LLMs in production? Cover prompt injection, data exfiltration, and model poisoning.",
         "expected_facts": [
             {"fact": "prompt injection can bypass system prompts", "type": "semantic"},
-            {"fact": "data exfiltration via tool use or function calling", "type": "semantic"},
-            {"fact": "model poisoning through training data contamination", "type": "semantic"},
-            {"fact": "mitigations include input filtering and output scanning", "type": "semantic"},
+            {
+                "fact": "data exfiltration via tool use or function calling",
+                "type": "semantic",
+            },
+            {
+                "fact": "model poisoning through training data contamination",
+                "type": "semantic",
+            },
+            {
+                "fact": "mitigations include input filtering and output scanning",
+                "type": "semantic",
+            },
         ],
     },
     {
         "question": "Compare the architectures and capabilities of major embedding models: OpenAI ada-002/3, Cohere embed-v3, and open-source alternatives like BGE and E5.",
         "expected_facts": [
-            {"fact": "OpenAI text-embedding-3 supports Matryoshka dimensions", "type": "semantic"},
-            {"fact": "Cohere embed-v3 supports multiple input types", "type": "semantic"},
-            {"fact": "BGE and E5 are open-source alternatives with competitive performance", "type": "semantic"},
+            {
+                "fact": "OpenAI text-embedding-3 supports Matryoshka dimensions",
+                "type": "semantic",
+            },
+            {
+                "fact": "Cohere embed-v3 supports multiple input types",
+                "type": "semantic",
+            },
+            {
+                "fact": "BGE and E5 are open-source alternatives with competitive performance",
+                "type": "semantic",
+            },
         ],
     },
     {
@@ -246,10 +327,22 @@ _HARD_TASKS: List[Dict[str, Any]] = [
     {
         "question": "How do different RAG (Retrieval-Augmented Generation) strategies compare? Cover naive RAG, advanced RAG with re-ranking, and GraphRAG.",
         "expected_facts": [
-            {"fact": "naive RAG does simple similarity search then generate", "type": "semantic"},
-            {"fact": "re-ranking improves retrieval precision with cross-encoder", "type": "semantic"},
-            {"fact": "GraphRAG uses knowledge graphs for structured retrieval", "type": "semantic"},
-            {"fact": "hybrid search combines dense and sparse retrieval", "type": "semantic"},
+            {
+                "fact": "naive RAG does simple similarity search then generate",
+                "type": "semantic",
+            },
+            {
+                "fact": "re-ranking improves retrieval precision with cross-encoder",
+                "type": "semantic",
+            },
+            {
+                "fact": "GraphRAG uses knowledge graphs for structured retrieval",
+                "type": "semantic",
+            },
+            {
+                "fact": "hybrid search combines dense and sparse retrieval",
+                "type": "semantic",
+            },
         ],
     },
     {
@@ -257,17 +350,32 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "expected_facts": [
             {"fact": "LoRA adds low-rank adapter matrices", "type": "semantic"},
             {"fact": "QLoRA combines quantization with LoRA", "type": "semantic"},
-            {"fact": "DoRA decomposes weights into magnitude and direction", "type": "semantic"},
-            {"fact": "full fine-tuning updates all parameters but needs more memory", "type": "semantic"},
+            {
+                "fact": "DoRA decomposes weights into magnitude and direction",
+                "type": "semantic",
+            },
+            {
+                "fact": "full fine-tuning updates all parameters but needs more memory",
+                "type": "semantic",
+            },
         ],
     },
     {
         "question": "Explain the evolution of position encoding in transformers: absolute, RoPE, ALiBi, and YaRN. What are the trade-offs for long-context extension?",
         "expected_facts": [
-            {"fact": "absolute position embeddings are fixed length", "type": "semantic"},
-            {"fact": "RoPE encodes relative position through rotation", "type": "semantic"},
+            {
+                "fact": "absolute position embeddings are fixed length",
+                "type": "semantic",
+            },
+            {
+                "fact": "RoPE encodes relative position through rotation",
+                "type": "semantic",
+            },
             {"fact": "ALiBi adds linear bias to attention scores", "type": "semantic"},
-            {"fact": "YaRN extends context through interpolation of RoPE", "type": "semantic"},
+            {
+                "fact": "YaRN extends context through interpolation of RoPE",
+                "type": "semantic",
+            },
         ],
     },
 ]
@@ -305,29 +413,27 @@ class BrowserAssistantDataset(DatasetProvider):
             )
 
             exact_facts = [
-                f["fact"] for f in task["expected_facts"]
-                if f["type"] == "exact"
+                f["fact"] for f in task["expected_facts"] if f["type"] == "exact"
             ]
             semantic_facts = [
-                f["fact"] for f in task["expected_facts"]
-                if f["type"] == "semantic"
+                f["fact"] for f in task["expected_facts"] if f["type"] == "semantic"
             ]
 
-            self._records.append(EvalRecord(
-                record_id=f"browser-assistant-{idx:03d}",
-                problem=prompt,
-                reference="; ".join(
-                    f["fact"] for f in task["expected_facts"]
-                ),
-                category="agentic",
-                subject=diff,
-                metadata={
-                    "question": task["question"],
-                    "expected_facts": task["expected_facts"],
-                    "exact_facts": exact_facts,
-                    "semantic_facts": semantic_facts,
-                },
-            ))
+            self._records.append(
+                EvalRecord(
+                    record_id=f"browser-assistant-{idx:03d}",
+                    problem=prompt,
+                    reference="; ".join(f["fact"] for f in task["expected_facts"]),
+                    category="agentic",
+                    subject=diff,
+                    metadata={
+                        "question": task["question"],
+                        "expected_facts": task["expected_facts"],
+                        "exact_facts": exact_facts,
+                        "semantic_facts": semantic_facts,
+                    },
+                )
+            )
 
     def iter_records(self) -> Iterable[EvalRecord]:
         return iter(self._records)

src/openjarvis/evals/datasets/coding_assistant.py

@@ -64,7 +64,13 @@ _EASY_TASKS: List[Dict[str, Any]] = [
             "def test_empty_page():\n"
             "    assert paginate(list(range(10)), 5, 3) == []\n"
         ),
-        "bugs": [{"description": "Off-by-one: end = start + per_page - 1 should be start + per_page", "file": "solution.py", "line": 3}],
+        "bugs": [
+            {
+                "description": "Off-by-one: end = start + per_page - 1 should be start + per_page",
+                "file": "solution.py",
+                "line": 3,
+            }
+        ],
         "originally_failing_tests": ["test_first_page", "test_second_page"],
         "originally_passing_tests": ["test_last_page", "test_empty_page"],
     },
@@ -91,20 +97,20 @@ _EASY_TASKS: List[Dict[str, Any]] = [
             "def test_empty():\n"
             "    assert is_palindrome('') is True\n"
         ),
-        "bugs": [{"description": "Unnecessary len(s) > 1 check rejects single chars and empty strings", "file": "solution.py", "line": 3}],
+        "bugs": [
+            {
+                "description": "Unnecessary len(s) > 1 check rejects single chars and empty strings",
+                "file": "solution.py",
+                "line": 3,
+            }
+        ],
         "originally_failing_tests": ["test_single_char", "test_empty"],
         "originally_passing_tests": ["test_racecar", "test_hello"],
     },
     {
         "bug_report": "The celsius_to_fahrenheit function returns wrong values.",
-        "buggy_code": (
-            "def celsius_to_fahrenheit(c):\n"
-            "    return c * 9 / 5 + 23\n"
-        ),
-        "fixed_code": (
-            "def celsius_to_fahrenheit(c):\n"
-            "    return c * 9 / 5 + 32\n"
-        ),
+        "buggy_code": ("def celsius_to_fahrenheit(c):\n    return c * 9 / 5 + 23\n"),
+        "fixed_code": ("def celsius_to_fahrenheit(c):\n    return c * 9 / 5 + 32\n"),
         "test_code": (
             "from solution import celsius_to_fahrenheit\n\n"
             "def test_freezing():\n"
@@ -114,7 +120,13 @@ _EASY_TASKS: List[Dict[str, Any]] = [
             "def test_body_temp():\n"
             "    assert abs(celsius_to_fahrenheit(37) - 98.6) < 0.01\n"
         ),
-        "bugs": [{"description": "Wrong constant: +23 should be +32", "file": "solution.py", "line": 2}],
+        "bugs": [
+            {
+                "description": "Wrong constant: +23 should be +32",
+                "file": "solution.py",
+                "line": 2,
+            }
+        ],
         "originally_failing_tests": ["test_freezing", "test_boiling", "test_body_temp"],
         "originally_passing_tests": [],
     },
@@ -151,7 +163,13 @@ _EASY_TASKS: List[Dict[str, Any]] = [
             "def test_deeply_nested():\n"
             "    assert flatten([[[1]], [[2]], [[3]]]) == [1, 2, 3]\n"
         ),
-        "bugs": [{"description": "append should be extend for recursive flattening", "file": "solution.py", "line": 5}],
+        "bugs": [
+            {
+                "description": "append should be extend for recursive flattening",
+                "file": "solution.py",
+                "line": 5,
+            }
+        ],
         "originally_failing_tests": ["test_nested", "test_deeply_nested"],
         "originally_passing_tests": ["test_flat", "test_empty"],
     },
@@ -194,9 +212,19 @@ _EASY_TASKS: List[Dict[str, Any]] = [
             "def test_not_found():\n"
             "    assert binary_search([1, 3, 5, 7, 9], 4) == -1\n"
         ),
-        "bugs": [{"description": "lo starts at 1 instead of 0, skipping first element", "file": "solution.py", "line": 2}],
+        "bugs": [
+            {
+                "description": "lo starts at 1 instead of 0, skipping first element",
+                "file": "solution.py",
+                "line": 2,
+            }
+        ],
         "originally_failing_tests": ["test_find_first"],
-        "originally_passing_tests": ["test_find_middle", "test_find_last", "test_not_found"],
+        "originally_passing_tests": [
+            "test_find_middle",
+            "test_find_last",
+            "test_not_found",
+        ],
     },
     {
         "bug_report": "The clamp function doesn't work when value equals min_val.",
@@ -231,9 +259,21 @@ _EASY_TASKS: List[Dict[str, Any]] = [
             "def test_at_max():\n"
             "    assert clamp(10, 0, 10) == 10\n"
         ),
-        "bugs": [{"description": "Actually no bug — this is a control task to test false positive rate", "file": "solution.py", "line": 0}],
+        "bugs": [
+            {
+                "description": "Actually no bug — this is a control task to test false positive rate",
+                "file": "solution.py",
+                "line": 0,
+            }
+        ],
         "originally_failing_tests": [],
-        "originally_passing_tests": ["test_below", "test_above", "test_within", "test_at_min", "test_at_max"],
+        "originally_passing_tests": [
+            "test_below",
+            "test_above",
+            "test_within",
+            "test_at_min",
+            "test_at_max",
+        ],
     },
     {
         "bug_report": "The count_vowels function misses uppercase vowels.",
@@ -264,7 +304,13 @@ _EASY_TASKS: List[Dict[str, Any]] = [
             "def test_empty():\n"
             "    assert count_vowels('') == 0\n"
         ),
-        "bugs": [{"description": "Does not handle uppercase — should lowercase first", "file": "solution.py", "line": 3}],
+        "bugs": [
+            {
+                "description": "Does not handle uppercase — should lowercase first",
+                "file": "solution.py",
+                "line": 3,
+            }
+        ],
         "originally_failing_tests": ["test_uppercase", "test_mixed"],
         "originally_passing_tests": ["test_lowercase", "test_empty"],
     },
@@ -303,7 +349,13 @@ _EASY_TASKS: List[Dict[str, Any]] = [
             "def test_two_elements():\n"
             "    assert max_profit([1, 5]) == 4\n"
         ),
-        "bugs": [{"description": "Subtraction order reversed: min_price - price should be price - min_price", "file": "solution.py", "line": 7}],
+        "bugs": [
+            {
+                "description": "Subtraction order reversed: min_price - price should be price - min_price",
+                "file": "solution.py",
+                "line": 7,
+            }
+        ],
         "originally_failing_tests": ["test_basic", "test_two_elements"],
         "originally_passing_tests": ["test_declining", "test_single"],
     },
@@ -333,7 +385,13 @@ _EASY_TASKS: List[Dict[str, Any]] = [
             "def test_already_title():\n"
             "    assert title_case('Hello') == 'Hello'\n"
         ),
-        "bugs": [{"description": "Does not handle hyphenated words", "file": "solution.py", "line": 2}],
+        "bugs": [
+            {
+                "description": "Does not handle hyphenated words",
+                "file": "solution.py",
+                "line": 2,
+            }
+        ],
         "originally_failing_tests": ["test_hyphenated"],
         "originally_passing_tests": ["test_simple", "test_already_title"],
     },
@@ -364,7 +422,13 @@ _EASY_TASKS: List[Dict[str, Any]] = [
             "def test_type_error():\n"
             "    assert safe_divide(10, 'a') == 0\n"
         ),
-        "bugs": [{"description": "Catches TypeError but not ZeroDivisionError", "file": "solution.py", "line": 4}],
+        "bugs": [
+            {
+                "description": "Catches TypeError but not ZeroDivisionError",
+                "file": "solution.py",
+                "line": 4,
+            }
+        ],
         "originally_failing_tests": ["test_zero_div", "test_zero_div_custom"],
         "originally_passing_tests": ["test_normal", "test_type_error"],
     },
@@ -438,8 +502,16 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
             "    assert c.get(1) == 10\n"
         ),
         "bugs": [
-            {"description": "order.pop() removes last (MRU) instead of order.pop(0) for LRU", "file": "solution.py", "line": 17},
-            {"description": "get/put don't remove old position before re-appending", "file": "solution.py", "line": 9},
+            {
+                "description": "order.pop() removes last (MRU) instead of order.pop(0) for LRU",
+                "file": "solution.py",
+                "line": 17,
+            },
+            {
+                "description": "get/put don't remove old position before re-appending",
+                "file": "solution.py",
+                "line": 9,
+            },
         ],
         "originally_failing_tests": ["test_basic", "test_update"],
         "originally_passing_tests": [],
@@ -488,7 +560,13 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
             "def test_duplicates():\n"
             "    assert merge_sorted([1, 2], [2, 3]) == [1, 2, 2, 3]\n"
         ),
-        "bugs": [{"description": "Duplicate result.extend(a[i:]) on line 13 causes extra elements", "file": "solution.py", "line": 13}],
+        "bugs": [
+            {
+                "description": "Duplicate result.extend(a[i:]) on line 13 causes extra elements",
+                "file": "solution.py",
+                "line": 13,
+            }
+        ],
         "originally_failing_tests": ["test_basic", "test_duplicates"],
         "originally_passing_tests": ["test_one_empty", "test_both_empty"],
     },
@@ -535,7 +613,13 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
             "    b = [[4], [5], [6]]\n"
             "    assert matrix_multiply(a, b) == [[32]]\n"
         ),
-        "bugs": [{"description": "Wrong index: b[j][k] should be b[k][j]", "file": "solution.py", "line": 10}],
+        "bugs": [
+            {
+                "description": "Wrong index: b[j][k] should be b[k][j]",
+                "file": "solution.py",
+                "line": 10,
+            }
+        ],
         "originally_failing_tests": ["test_basic", "test_non_square"],
         "originally_passing_tests": ["test_identity"],
     },
@@ -582,7 +666,13 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
             "def test_no_repeats():\n"
             "    assert run_length_encode('abc') == 'a1b1c1'\n"
         ),
-        "bugs": [{"description": "In else branch, appends s[i] (next char) instead of s[i-1] (current char)", "file": "solution.py", "line": 10}],
+        "bugs": [
+            {
+                "description": "In else branch, appends s[i] (next char) instead of s[i-1] (current char)",
+                "file": "solution.py",
+                "line": 10,
+            }
+        ],
         "originally_failing_tests": ["test_basic", "test_no_repeats"],
         "originally_passing_tests": ["test_single", "test_empty"],
     },
@@ -627,9 +717,20 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
             "def test_extra_close():\n"
             "    assert validate_brackets(')') is False\n"
         ),
-        "bugs": [{"description": "Does not check that closing bracket matches the top of stack", "file": "solution.py", "line": 10}],
+        "bugs": [
+            {
+                "description": "Does not check that closing bracket matches the top of stack",
+                "file": "solution.py",
+                "line": 10,
+            }
+        ],
         "originally_failing_tests": ["test_mismatched"],
-        "originally_passing_tests": ["test_valid", "test_unclosed", "test_empty", "test_extra_close"],
+        "originally_passing_tests": [
+            "test_valid",
+            "test_unclosed",
+            "test_empty",
+            "test_extra_close",
+        ],
     },
     {
         "bug_report": "The group_by function loses entries when multiple items have the same key.",
@@ -660,7 +761,13 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
             "def test_empty():\n"
             "    assert group_by([], lambda x: x) == {}\n"
         ),
-        "bugs": [{"description": "Overwrites group with [item] instead of appending to list", "file": "solution.py", "line": 5}],
+        "bugs": [
+            {
+                "description": "Overwrites group with [item] instead of appending to list",
+                "file": "solution.py",
+                "line": 5,
+            }
+        ],
         "originally_failing_tests": ["test_basic", "test_strings"],
         "originally_passing_tests": ["test_empty"],
     },
@@ -697,8 +804,18 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
             "def test_window_too_large():\n"
             "    assert moving_average([1], 5) == []\n"
         ),
-        "bugs": [{"description": "Off-by-one in range: should be len(data) - window + 1", "file": "solution.py", "line": 5}],
-        "originally_failing_tests": ["test_basic", "test_window_equals_length", "test_window_one"],
+        "bugs": [
+            {
+                "description": "Off-by-one in range: should be len(data) - window + 1",
+                "file": "solution.py",
+                "line": 5,
+            }
+        ],
+        "originally_failing_tests": [
+            "test_basic",
+            "test_window_equals_length",
+            "test_window_one",
+        ],
         "originally_passing_tests": ["test_window_too_large"],
     },
     {
@@ -763,7 +880,13 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
             "    t = Trie()\n"
             "    assert t.search('hello') is False\n"
         ),
-        "bugs": [{"description": "search returns False instead of node.is_end", "file": "solution.py", "line": 24}],
+        "bugs": [
+            {
+                "description": "search returns False instead of node.is_end",
+                "file": "solution.py",
+                "line": 24,
+            }
+        ],
         "originally_failing_tests": ["test_insert_search"],
         "originally_passing_tests": ["test_search_missing", "test_search_not_inserted"],
     },
@@ -803,7 +926,13 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
             "    expected = {'a': {'b': {'c': 3, 'd': 2}}}\n"
             "    assert deep_merge(base, over) == expected\n"
         ),
-        "bugs": [{"description": "Shallow merge: overwrites nested dicts instead of recursively merging", "file": "solution.py", "line": 4}],
+        "bugs": [
+            {
+                "description": "Shallow merge: overwrites nested dicts instead of recursively merging",
+                "file": "solution.py",
+                "line": 4,
+            }
+        ],
         "originally_failing_tests": ["test_nested", "test_deeply_nested"],
         "originally_passing_tests": ["test_flat", "test_override"],
     },
@@ -864,9 +993,18 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
             "    debounced(2)  # fires after wait\n"
             "    assert len(calls) == 2\n"
         ),
-        "bugs": [{"description": "Missing time check: calls func every time instead of only after wait_seconds", "file": "solution.py", "line": 9}],
+        "bugs": [
+            {
+                "description": "Missing time check: calls func every time instead of only after wait_seconds",
+                "file": "solution.py",
+                "line": 9,
+            }
+        ],
         "originally_failing_tests": ["test_debounce_suppresses"],
-        "originally_passing_tests": ["test_debounce_fires_first", "test_debounce_fires_after_wait"],
+        "originally_passing_tests": [
+            "test_debounce_fires_first",
+            "test_debounce_fires_after_wait",
+        ],
     },
 ]
 
@@ -908,16 +1046,19 @@ _HARD_TASKS: List[Dict[str, Any]] = [
             "    # 19.99 * 1.0875 * 0.95 = 20.6496...\n"
             "    assert financial_round(19.99, 0.0875, 0.05) == 20.65\n"
         ),
-        "bugs": [{"description": "Float arithmetic causes precision errors — should use Decimal", "file": "solution.py", "line": 2}],
+        "bugs": [
+            {
+                "description": "Float arithmetic causes precision errors — should use Decimal",
+                "file": "solution.py",
+                "line": 2,
+            }
+        ],
         "originally_failing_tests": ["test_precision", "test_rounding_boundary"],
         "originally_passing_tests": ["test_basic", "test_no_discount"],
     },
     {
         "bug_report": "The csv_parser doesn't handle quoted fields with commas inside.",
-        "buggy_code": (
-            "def parse_csv_line(line):\n"
-            "    return line.split(',')\n"
-        ),
+        "buggy_code": ("def parse_csv_line(line):\n    return line.split(',')\n"),
         "fixed_code": (
             "import csv\nimport io\n\n"
             "def parse_csv_line(line):\n"
@@ -935,7 +1076,13 @@ _HARD_TASKS: List[Dict[str, Any]] = [
             "def test_empty_fields():\n"
             "    assert parse_csv_line('a,,c') == ['a', '', 'c']\n"
         ),
-        "bugs": [{"description": "Naive split(',') doesn't handle quoted fields", "file": "solution.py", "line": 2}],
+        "bugs": [
+            {
+                "description": "Naive split(',') doesn't handle quoted fields",
+                "file": "solution.py",
+                "line": 2,
+            }
+        ],
         "originally_failing_tests": ["test_quoted_comma"],
         "originally_passing_tests": ["test_simple", "test_empty_fields"],
     },
@@ -1003,7 +1150,13 @@ _HARD_TASKS: List[Dict[str, Any]] = [
             "    except RuntimeError:\n"
             "        pass\n"
         ),
-        "bugs": [{"description": "Success path doesn't return immediately and sleeps unnecessarily; runs all attempts", "file": "solution.py", "line": 8}],
+        "bugs": [
+            {
+                "description": "Success path doesn't return immediately and sleeps unnecessarily; runs all attempts",
+                "file": "solution.py",
+                "line": 8,
+            }
+        ],
         "originally_failing_tests": ["test_succeeds_first_try"],
         "originally_passing_tests": ["test_exhausts_retries"],
     },
@@ -1040,7 +1193,13 @@ _HARD_TASKS: List[Dict[str, Any]] = [
             "    result = parse_url_params('http://example.com?data=a=b')\n"
             "    assert result['data'] == 'a=b'\n"
         ),
-        "bugs": [{"description": "split('=') breaks on values containing '='; doesn't decode URL encoding", "file": "solution.py", "line": 7}],
+        "bugs": [
+            {
+                "description": "split('=') breaks on values containing '='; doesn't decode URL encoding",
+                "file": "solution.py",
+                "line": 7,
+            }
+        ],
         "originally_failing_tests": ["test_encoded_value", "test_value_with_equals"],
         "originally_passing_tests": ["test_basic", "test_no_params"],
     },
@@ -1093,8 +1252,17 @@ _HARD_TASKS: List[Dict[str, Any]] = [
             "    time.sleep(0.1)\n"
             "    assert rl.allow() is True\n"
         ),
-        "bugs": [{"description": "Never removes old requests; always appends even when over limit", "file": "solution.py", "line": 10}],
-        "originally_failing_tests": ["test_blocks_over_limit", "test_allows_after_window"],
+        "bugs": [
+            {
+                "description": "Never removes old requests; always appends even when over limit",
+                "file": "solution.py",
+                "line": 10,
+            }
+        ],
+        "originally_failing_tests": [
+            "test_blocks_over_limit",
+            "test_allows_after_window",
+        ],
         "originally_passing_tests": ["test_allows_within_limit"],
     },
     {
@@ -1148,7 +1316,13 @@ _HARD_TASKS: List[Dict[str, Any]] = [
             "    greet(name='Alice', greeting='hey')\n"
             "    assert len(calls) == 2\n"
         ),
-        "bugs": [{"description": "Wrapper doesn't accept or cache kwargs", "file": "solution.py", "line": 3}],
+        "bugs": [
+            {
+                "description": "Wrapper doesn't accept or cache kwargs",
+                "file": "solution.py",
+                "line": 3,
+            }
+        ],
         "originally_failing_tests": ["test_kwargs", "test_different_kwargs"],
         "originally_passing_tests": ["test_positional"],
     },
@@ -1194,7 +1368,13 @@ _HARD_TASKS: List[Dict[str, Any]] = [
             "    ee = EventEmitter()\n"
             "    ee.emit('missing')  # should not raise\n"
         ),
-        "bugs": [{"description": "on() overwrites listener instead of appending to list", "file": "solution.py", "line": 6}],
+        "bugs": [
+            {
+                "description": "on() overwrites listener instead of appending to list",
+                "file": "solution.py",
+                "line": 6,
+            }
+        ],
         "originally_failing_tests": ["test_multiple_listeners"],
         "originally_passing_tests": ["test_single_listener", "test_no_listeners"],
     },
@@ -1240,7 +1420,13 @@ _HARD_TASKS: List[Dict[str, Any]] = [
             "    result = json_flatten(obj)\n"
             "    assert result == {'a.b.c[0]': 1, 'a.b.c[1]': 2}\n"
         ),
-        "bugs": [{"description": "Does not handle list values, only dicts", "file": "solution.py", "line": 5}],
+        "bugs": [
+            {
+                "description": "Does not handle list values, only dicts",
+                "file": "solution.py",
+                "line": 5,
+            }
+        ],
         "originally_failing_tests": ["test_with_array", "test_deeply_nested"],
         "originally_passing_tests": ["test_flat", "test_nested"],
     },
@@ -1295,7 +1481,13 @@ _HARD_TASKS: List[Dict[str, Any]] = [
             "    assert len(results) == 2\n"
             "    assert all(r[0] == 'error' for r in results)\n"
         ),
-        "bugs": [{"description": "Silently swallows exceptions instead of recording them", "file": "solution.py", "line": 9}],
+        "bugs": [
+            {
+                "description": "Silently swallows exceptions instead of recording them",
+                "file": "solution.py",
+                "line": 9,
+            }
+        ],
         "originally_failing_tests": ["test_one_fails", "test_all_fail"],
         "originally_passing_tests": ["test_all_succeed"],
     },
@@ -1354,7 +1546,13 @@ _HARD_TASKS: List[Dict[str, Any]] = [
             "    with pytest.raises(ValueError, match='Cycle'):\n"
             "        topological_sort(graph)\n"
         ),
-        "bugs": [{"description": "No cycle detection — infinite recursion on cyclic graphs", "file": "solution.py", "line": 5}],
+        "bugs": [
+            {
+                "description": "No cycle detection — infinite recursion on cyclic graphs",
+                "file": "solution.py",
+                "line": 5,
+            }
+        ],
         "originally_failing_tests": ["test_cycle_detection"],
         "originally_passing_tests": ["test_linear", "test_diamond"],
     },

src/openjarvis/evals/datasets/coding_task.py

@@ -200,7 +200,7 @@ _TASKS = [
     {
         "spec": "Implement a function that serializes and deserializes a binary tree. The tree node has val, left, right attributes.",
         "signature": "def serialize(root) -> str\ndef deserialize(data: str) -> TreeNode",
-        "examples": 'serialize a tree [1,2,3,null,null,4,5] -> some string\ndeserialize that string -> same tree',
+        "examples": "serialize a tree [1,2,3,null,null,4,5] -> some string\ndeserialize that string -> same tree",
         "test_cases": "class TreeNode:\n    def __init__(self, val=0, left=None, right=None):\n        self.val, self.left, self.right = val, left, right\nroot = TreeNode(1, TreeNode(2), TreeNode(3, TreeNode(4), TreeNode(5)))\ns = serialize(root)\nnew_root = deserialize(s)\nassert new_root.val == 1\nassert new_root.left.val == 2\nassert new_root.right.val == 3\nassert new_root.right.left.val == 4",
         "reference": "class TreeNode:\n    def __init__(self, val=0, left=None, right=None):\n        self.val, self.left, self.right = val, left, right\ndef serialize(root):\n    if not root: return 'null'\n    return f'{root.val},{serialize(root.left)},{serialize(root.right)}'\ndef deserialize(data):\n    vals = iter(data.split(','))\n    def build():\n        v = next(vals)\n        if v == 'null': return None\n        node = TreeNode(int(v))\n        node.left = build()\n        node.right = build()\n        return node\n    return build()",
     },
@@ -260,17 +260,19 @@ class CodingTaskDataset(DatasetProvider):
                 signature=task["signature"],
                 examples=task["examples"],
             )
-            self._records.append(EvalRecord(
-                record_id=f"coding-task-{idx}",
-                problem=prompt,
-                reference=task["reference"],
-                category="use-case",
-                subject="coding_task",
-                metadata={
-                    "test_cases": task["test_cases"],
-                    "signature": task["signature"],
-                },
-            ))
+            self._records.append(
+                EvalRecord(
+                    record_id=f"coding-task-{idx}",
+                    problem=prompt,
+                    reference=task["reference"],
+                    category="use-case",
+                    subject="coding_task",
+                    metadata={
+                        "test_cases": task["test_cases"],
+                        "signature": task["signature"],
+                    },
+                )
+            )
 
     def iter_records(self) -> Iterable[EvalRecord]:
         return iter(self._records)

src/openjarvis/evals/datasets/daily_digest.py

@@ -97,7 +97,12 @@ _EASY_TASKS: List[Dict[str, Any]] = [
         "todos": "- Finalize Q4 roadmap draft\n- Send release notes for v3.2",
         "messages": "- Slack from @eng-lead: 'v3.2 deployed to staging, all green'\n- Email from VP: 'Need roadmap by EOD Monday'",
         "news_interests": "Fintech regulations, payment APIs",
-        "must_mention": ["stakeholder demo", "v3.2 staging", "Q4 roadmap", "EOD Monday deadline"],
+        "must_mention": [
+            "stakeholder demo",
+            "v3.2 staging",
+            "Q4 roadmap",
+            "EOD Monday deadline",
+        ],
         "priority_order": ["stakeholder demo", "v3.2 staging", "Q4 roadmap"],
     },
     {
@@ -119,7 +124,11 @@ _EASY_TASKS: List[Dict[str, Any]] = [
         "todos": "- Fix crash in offline mode (Sentry issue #891)\n- Implement push notification deep links",
         "messages": "- Slack from QA: 'Sentry #891 affecting 2% of users on iOS 17'\n- App Store Connect: 'v4.1 approved for release'",
         "news_interests": "Swift, iOS",
-        "must_mention": ["Sentry #891 crash", "v4.1 approved", "push notification deep links"],
+        "must_mention": [
+            "Sentry #891 crash",
+            "v4.1 approved",
+            "push notification deep links",
+        ],
         "priority_order": ["Sentry #891 crash", "v4.1 approved"],
     },
     {
@@ -141,7 +150,11 @@ _EASY_TASKS: List[Dict[str, Any]] = [
         "todos": "- Run regression suite for v5.0\n- Update test plan for payment module",
         "messages": "- Jira: 'RELEASE-50: v5.0 release candidate tagged'\n- Slack from dev: 'Payment module refactored, old tests may break'",
         "news_interests": "Test automation, Playwright",
-        "must_mention": ["v5.0 regression suite", "payment module tests", "release readiness"],
+        "must_mention": [
+            "v5.0 regression suite",
+            "payment module tests",
+            "release readiness",
+        ],
         "priority_order": ["v5.0 regression suite", "payment module tests"],
     },
     {
@@ -152,7 +165,11 @@ _EASY_TASKS: List[Dict[str, Any]] = [
         "todos": "- Write post-mortem for Wednesday's outage\n- Update runbook for database failover",
         "messages": "- Datadog: 'API p99 latency back to normal (12ms)'\n- Manager: 'Post-mortem draft needed before Monday'",
         "news_interests": "SRE practices, observability",
-        "must_mention": ["post-mortem draft", "API latency normal", "capacity planning"],
+        "must_mention": [
+            "post-mortem draft",
+            "API latency normal",
+            "capacity planning",
+        ],
         "priority_order": ["post-mortem draft", "capacity planning"],
     },
 ]
@@ -170,8 +187,18 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
         "todos": "- Finalize RFC for webhook retry redesign\n- Review perf regression in checkout API\n- Respond to security review findings",
         "messages": "- Slack from @payments-lead: 'Webhook failures up 3x since Friday deploy'\n- Email from VP Eng: 'RFC deadline extended to Wednesday'\n- Jira INFRA-2847: 'Checkout API p99 jumped from 200ms to 800ms'",
         "news_interests": "distributed systems, payment processing",
-        "must_mention": ["webhook failures 3x", "INFRA-2847 checkout latency", "RFC deadline Wednesday", "architecture review", "security review findings"],
-        "priority_order": ["webhook failures 3x", "INFRA-2847 checkout latency", "RFC deadline"],
+        "must_mention": [
+            "webhook failures 3x",
+            "INFRA-2847 checkout latency",
+            "RFC deadline Wednesday",
+            "architecture review",
+            "security review findings",
+        ],
+        "priority_order": [
+            "webhook failures 3x",
+            "INFRA-2847 checkout latency",
+            "RFC deadline",
+        ],
     },
     {
         "role": "ML Engineer",
@@ -181,7 +208,13 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
         "todos": "- Investigate 5% CTR drop in product recommendations\n- Prepare training data for v3 model\n- Review feature store PR from junior engineer",
         "messages": "- Slack from product: 'Recommendation CTR dropped on mobile — exec visibility'\n- Airflow alert: 'DAG user_features failed at 03:00, 2 retries exhausted'\n- Email from research: 'New embedding approach shows 12% improvement in offline eval'",
         "news_interests": "recommendation systems, transformer architectures",
-        "must_mention": ["CTR drop", "Airflow DAG failure", "v3 model training data", "A/B test review", "new embedding approach"],
+        "must_mention": [
+            "CTR drop",
+            "Airflow DAG failure",
+            "v3 model training data",
+            "A/B test review",
+            "new embedding approach",
+        ],
         "priority_order": ["CTR drop", "Airflow DAG failure", "A/B test review"],
     },
     {
@@ -192,8 +225,18 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
         "todos": "- Complete service mesh POC documentation\n- Fix flaky integration tests in CI pipeline\n- Review IAM policy changes for staging env",
         "messages": "- Slack from SRE: 'CI pipeline blocked — flaky test_payment_flow failing 40% of runs'\n- Email from CTO: 'Need vendor recommendation by Friday for budget approval'\n- GitHub: '3 new Dependabot PRs — 1 critical (lodash prototype pollution)'",
         "news_interests": "service mesh, platform engineering",
-        "must_mention": ["CI flaky test", "vendor recommendation Friday", "lodash critical CVE", "migration planning", "IAM policy review"],
-        "priority_order": ["CI flaky test", "lodash critical CVE", "vendor recommendation"],
+        "must_mention": [
+            "CI flaky test",
+            "vendor recommendation Friday",
+            "lodash critical CVE",
+            "migration planning",
+            "IAM policy review",
+        ],
+        "priority_order": [
+            "CI flaky test",
+            "lodash critical CVE",
+            "vendor recommendation",
+        ],
     },
     {
         "role": "Tech Lead",
@@ -203,8 +246,18 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
         "todos": "- Audit PHI access logs for September\n- Design API for lab results integration\n- Mentor new hire on HIPAA data handling",
         "messages": "- Compliance team: 'September PHI audit due Oct 15 — need your section by Oct 10'\n- PM: 'Patient portal launch moved up to Nov 1'\n- QA: 'Found PHI leak in staging logs — ticket SEC-445'",
         "news_interests": "healthcare APIs, HIPAA compliance",
-        "must_mention": ["PHI leak SEC-445", "audit due Oct 10", "patient portal Nov 1", "lab results API", "HIPAA compliance review"],
-        "priority_order": ["PHI leak SEC-445", "audit due Oct 10", "patient portal Nov 1"],
+        "must_mention": [
+            "PHI leak SEC-445",
+            "audit due Oct 10",
+            "patient portal Nov 1",
+            "lab results API",
+            "HIPAA compliance review",
+        ],
+        "priority_order": [
+            "PHI leak SEC-445",
+            "audit due Oct 10",
+            "patient portal Nov 1",
+        ],
     },
     {
         "role": "Backend Lead",
@@ -214,8 +267,18 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
         "todos": "- Sign off on deploy for order management refactor\n- Review load test results (target: 10x normal traffic)\n- Update on-call rotation for holiday season",
         "messages": "- Load test results: 'System handles 7x but OOM at 8x on order-service'\n- Slack from payments: 'New Stripe API version — migration needed by Dec 1'\n- PagerDuty: 'Memory leak alert on cart-service, auto-scaled to 8 pods'",
         "news_interests": "e-commerce scaling, distributed systems",
-        "must_mention": ["OOM at 8x load", "cart-service memory leak", "Stripe migration Dec 1", "Black Friday capacity", "deploy review"],
-        "priority_order": ["OOM at 8x load", "cart-service memory leak", "Black Friday capacity"],
+        "must_mention": [
+            "OOM at 8x load",
+            "cart-service memory leak",
+            "Stripe migration Dec 1",
+            "Black Friday capacity",
+            "deploy review",
+        ],
+        "priority_order": [
+            "OOM at 8x load",
+            "cart-service memory leak",
+            "Black Friday capacity",
+        ],
     },
     {
         "role": "Data Engineer",
@@ -225,8 +288,17 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
         "todos": "- Debug Spark job OOM on customer_360 pipeline\n- Implement CDC for new orders table\n- Review dbt model changes from analytics team",
         "messages": "- Airflow: 'customer_360 DAG failed — Spark executor OOM'\n- Marketing: 'Attribution numbers look off by 15% since last week'\n- Slack from manager: 'Quarterly data infrastructure review next Tuesday, prep needed'",
         "news_interests": "data engineering, Apache Spark",
-        "must_mention": ["Spark OOM customer_360", "attribution 15% discrepancy", "CDC orders table", "infrastructure review prep"],
-        "priority_order": ["Spark OOM", "attribution discrepancy", "infrastructure review"],
+        "must_mention": [
+            "Spark OOM customer_360",
+            "attribution 15% discrepancy",
+            "CDC orders table",
+            "infrastructure review prep",
+        ],
+        "priority_order": [
+            "Spark OOM",
+            "attribution discrepancy",
+            "infrastructure review",
+        ],
     },
     {
         "role": "iOS Lead",
@@ -236,8 +308,18 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
         "todos": "- Fix crash in background refresh (Sentry #1204)\n- Prepare submission for iOS 18 compatibility update\n- Review accessibility audit findings",
         "messages": "- App Store Connect: 'v6.2.1 rejected — missing privacy manifest for tracking'\n- Sentry: '#1204 crash rate increased to 0.8% (was 0.2%)'\n- Apple developer news: 'Privacy manifest deadline extended to Oct 31'",
         "news_interests": "iOS development, SwiftUI",
-        "must_mention": ["v6.2.1 rejected", "privacy manifest deadline Oct 31", "Sentry #1204 crash", "accessibility audit", "SwiftUI migration"],
-        "priority_order": ["v6.2.1 rejected", "Sentry #1204 crash", "privacy manifest deadline"],
+        "must_mention": [
+            "v6.2.1 rejected",
+            "privacy manifest deadline Oct 31",
+            "Sentry #1204 crash",
+            "accessibility audit",
+            "SwiftUI migration",
+        ],
+        "priority_order": [
+            "v6.2.1 rejected",
+            "Sentry #1204 crash",
+            "privacy manifest deadline",
+        ],
     },
     {
         "role": "VP of Engineering",
@@ -247,7 +329,13 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
         "todos": "- Finalize engineering section of board deck\n- Approve Q1 hiring plan (8 headcount)\n- Review SOC 2 Type II readiness",
         "messages": "- CEO: 'Board meeting moved to Oct 20, deck due Oct 17'\n- HR: 'Director candidate strong — competing offer from FAANG, need to move fast'\n- CTO: 'SOC 2 auditor found 2 medium findings, remediation needed'",
         "news_interests": "engineering leadership, scaling teams",
-        "must_mention": ["board deck due Oct 17", "director candidate competing offer", "SOC 2 findings", "Q1 hiring plan", "engineering all-hands"],
+        "must_mention": [
+            "board deck due Oct 17",
+            "director candidate competing offer",
+            "SOC 2 findings",
+            "Q1 hiring plan",
+            "engineering all-hands",
+        ],
         "priority_order": ["director candidate", "board deck Oct 17", "SOC 2 findings"],
     },
     {
@@ -258,8 +346,18 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
         "todos": "- Fix video player buffering on slow connections\n- Implement quiz auto-save feature\n- Update staging with latest migrations",
         "messages": "- Support: '15 teachers reported video playback issues today'\n- PM: 'Quiz module launch is hard deadline — Nov 15'\n- Slack from DevOps: 'Staging DB needs migration, currently 3 behind'",
         "news_interests": "video streaming, education technology",
-        "must_mention": ["video playback issues", "quiz module Nov 15", "staging migrations behind", "feature demo", "tech debt review"],
-        "priority_order": ["video playback issues", "quiz module Nov 15", "staging migrations"],
+        "must_mention": [
+            "video playback issues",
+            "quiz module Nov 15",
+            "staging migrations behind",
+            "feature demo",
+            "tech debt review",
+        ],
+        "priority_order": [
+            "video playback issues",
+            "quiz module Nov 15",
+            "staging migrations",
+        ],
     },
     {
         "role": "Infrastructure Engineer",
@@ -269,8 +367,18 @@ _MEDIUM_TASKS: List[Dict[str, Any]] = [
         "todos": "- Prepare DR test runbook for Q4 drill\n- Migrate legacy monitoring to Grafana\n- Review firewall rule change requests",
         "messages": "- AWS: 'Scheduled maintenance us-east-1: Oct 25, 02:00-06:00 UTC'\n- Compliance: 'Annual DR test must complete before Dec 31'\n- Slack from SRE: 'Grafana migration 60% complete, need help with alert rules'",
         "news_interests": "cloud infrastructure, disaster recovery",
-        "must_mention": ["AWS maintenance Oct 25", "DR test before Dec 31", "Grafana migration 60%", "firewall rule review", "change advisory board"],
-        "priority_order": ["AWS maintenance Oct 25", "DR test planning", "Grafana migration"],
+        "must_mention": [
+            "AWS maintenance Oct 25",
+            "DR test before Dec 31",
+            "Grafana migration 60%",
+            "firewall rule review",
+            "change advisory board",
+        ],
+        "priority_order": [
+            "AWS maintenance Oct 25",
+            "DR test planning",
+            "Grafana migration",
+        ],
     },
 ]
 
@@ -287,8 +395,21 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "todos": "- Complete post-mortem document for payment outage (5h downtime, $2.3M impact)\n- Implement circuit breaker for payment gateway\n- Review and merge hotfix for connection pool exhaustion\n- Update incident response playbook with lessons learned",
         "messages": "- PagerDuty: 'CRITICAL — Payment success rate dropped to 45% at 02:14, recovered at 07:30'\n- CEO: 'Need customer communication plan by noon'\n- VP Eng: 'Board wants root cause by Wednesday'\n- Slack from payments team: 'Connection pool fix in PR #891, needs urgent review'\n- Datadog: '3 new anomaly alerts on order-service since 08:00'\n- Customer success: '47 enterprise customers opened tickets about Friday outage'",
         "news_interests": "SRE, payment systems, incident management",
-        "must_mention": ["payment outage $2.3M", "PR #891 connection pool", "customer communication noon", "board root cause Wednesday", "new anomaly alerts", "47 enterprise tickets", "post-mortem"],
-        "priority_order": ["customer communication noon", "PR #891 connection pool", "anomaly alerts", "board root cause Wednesday"],
+        "must_mention": [
+            "payment outage $2.3M",
+            "PR #891 connection pool",
+            "customer communication noon",
+            "board root cause Wednesday",
+            "new anomaly alerts",
+            "47 enterprise tickets",
+            "post-mortem",
+        ],
+        "priority_order": [
+            "customer communication noon",
+            "PR #891 connection pool",
+            "anomaly alerts",
+            "board root cause Wednesday",
+        ],
     },
     {
         "role": "CISO",
@@ -298,8 +419,21 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "todos": "- Coordinate response to detected data exfiltration attempt\n- Prepare board briefing on security incident\n- Review forensic analysis from IR team\n- Determine notification obligations under GDPR/CCPA",
         "messages": "- SOC: 'Detected unusual data transfer — 2.3GB to external IP from staging-db-02 at 01:47'\n- IR team: 'Attack vector identified: compromised service account via phished credentials'\n- Legal: 'If PII confirmed, 72h GDPR notification clock starts now'\n- CEO: 'No external communication until legal approves messaging'\n- AWS GuardDuty: 'UnauthorizedAccess:IAMUser/MaliciousIPCaller on staging account'\n- HR: 'Phished employee identified, account disabled'",
         "news_interests": "cybersecurity, data breach response, compliance",
-        "must_mention": ["2.3GB exfiltration", "phished credentials", "GDPR 72h notification", "board briefing", "legal messaging approval", "GuardDuty alert", "compromised service account"],
-        "priority_order": ["exfiltration incident", "GDPR notification", "board briefing", "legal approval"],
+        "must_mention": [
+            "2.3GB exfiltration",
+            "phished credentials",
+            "GDPR 72h notification",
+            "board briefing",
+            "legal messaging approval",
+            "GuardDuty alert",
+            "compromised service account",
+        ],
+        "priority_order": [
+            "exfiltration incident",
+            "GDPR notification",
+            "board briefing",
+            "legal approval",
+        ],
     },
     {
         "role": "Engineering Director",
@@ -309,8 +443,20 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "todos": "- Resolve broken Salesforce integration (blocking $4M deal)\n- Prepare Q1 roadmap proposal for exec review\n- Address team morale issues in Platform team (3 resignations in 2 months)\n- Review compensation adjustments for retention",
         "messages": "- Salesforce partner: 'API breaking change in v58 — our integration returns 400s since midnight'\n- Sales VP: '$4M Acme deal closes Friday, integration must work by Thursday EOD'\n- HR: 'Exit interview themes: lack of growth, below-market comp'\n- CTO: 'Q1 roadmap proposal due Friday, include AI strategy'\n- Slack from platform-lead: 'Two more engineers gave notice yesterday'\n- GitHub: 'Salesforce integration fix in draft PR, needs API key rotation'",
         "news_interests": "engineering management, API integrations",
-        "must_mention": ["Salesforce API breaking change", "$4M deal Thursday deadline", "platform team resignations", "Q1 roadmap Friday", "compensation adjustments", "API key rotation"],
-        "priority_order": ["Salesforce integration", "$4M deal deadline", "platform team resignations", "Q1 roadmap"],
+        "must_mention": [
+            "Salesforce API breaking change",
+            "$4M deal Thursday deadline",
+            "platform team resignations",
+            "Q1 roadmap Friday",
+            "compensation adjustments",
+            "API key rotation",
+        ],
+        "priority_order": [
+            "Salesforce integration",
+            "$4M deal deadline",
+            "platform team resignations",
+            "Q1 roadmap",
+        ],
     },
     {
         "role": "Lead SRE",
@@ -320,8 +466,21 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "todos": "- Coordinate failover to backup CDN\n- Estimate customer impact (MAU affected, SLA credits)\n- Prepare status page communications\n- Document timeline for incident report",
         "messages": "- CDN provider: 'Global edge outage affecting EU and APAC, ETA 4h for full recovery'\n- Monitoring: 'Video start failures at 78% (normal: 2%), 3.2M users affected'\n- Customer success: 'ESPN, Netflix, Disney+ all escalating — SLA breach imminent'\n- CEO: 'Status page must update every 30 minutes'\n- Finance: 'Estimated SLA credits: $850K if not resolved by noon'\n- Engineering: 'Backup CDN can handle 60% of traffic, degraded quality'",
         "news_interests": "CDN, video streaming, incident management",
-        "must_mention": ["CDN outage EU APAC", "3.2M users affected", "SLA credits $850K", "backup CDN 60%", "status page updates 30min", "ETA 4h recovery", "ESPN Netflix Disney escalation"],
-        "priority_order": ["CDN failover", "status page updates", "customer escalations", "SLA credit estimate"],
+        "must_mention": [
+            "CDN outage EU APAC",
+            "3.2M users affected",
+            "SLA credits $850K",
+            "backup CDN 60%",
+            "status page updates 30min",
+            "ETA 4h recovery",
+            "ESPN Netflix Disney escalation",
+        ],
+        "priority_order": [
+            "CDN failover",
+            "status page updates",
+            "customer escalations",
+            "SLA credit estimate",
+        ],
     },
     {
         "role": "CTO",
@@ -331,8 +490,20 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "todos": "- Address GPU cost overrun ($180K over budget this quarter)\n- Prepare technical due diligence materials for Series B\n- Evaluate build vs buy for vector database\n- Respond to acquisition interest from BigTech",
         "messages": "- CFO: 'GPU costs 40% over budget — need cost reduction plan by Monday'\n- Lead investor: 'Series B term sheet ready, need tech DD materials by next Friday'\n- BigTech BD: 'Acquisition conversation request — CEO says explore quietly'\n- AWS: 'Reserved instance commitment expires Nov 30'\n- ML team: 'New model achieves SOTA on benchmark but requires 2x GPU'\n- VP Eng: 'Team burnout is real — 60h average weeks for past month'",
         "news_interests": "AI infrastructure, venture capital, GPU optimization",
-        "must_mention": ["GPU cost overrun $180K", "Series B DD materials", "acquisition interest", "RI expiration Nov 30", "SOTA model 2x GPU", "team burnout 60h weeks"],
-        "priority_order": ["GPU cost reduction Monday", "Series B DD", "acquisition exploration", "team burnout"],
+        "must_mention": [
+            "GPU cost overrun $180K",
+            "Series B DD materials",
+            "acquisition interest",
+            "RI expiration Nov 30",
+            "SOTA model 2x GPU",
+            "team burnout 60h weeks",
+        ],
+        "priority_order": [
+            "GPU cost reduction Monday",
+            "Series B DD",
+            "acquisition exploration",
+            "team burnout",
+        ],
     },
     {
         "role": "Principal Engineer",
@@ -342,8 +513,20 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "todos": "- Investigate 50ms latency spike in order matching engine\n- Review SEC Rule 15c3-5 compliance for new algorithm\n- Design circuit breaker for third-party market data feeds\n- Prepare tech brief on microsecond timestamping upgrade",
         "messages": "- Trading desk: 'Order matching 50ms slower since Friday deploy — losing $40K/day in slippage'\n- Compliance: 'SEC audit next month, need algorithm documentation by Nov 20'\n- Vendor: 'Market data feed v3 deprecating Dec 15, migration required'\n- CTO: 'Board approved microsecond upgrade budget, need timeline'\n- Monitoring: 'Memory leak detected in risk engine — growing 50MB/hour'\n- DevOps: 'Friday deploy rollback available but needs 2h maintenance window'",
         "news_interests": "low-latency systems, financial technology",
-        "must_mention": ["order matching latency $40K/day", "SEC audit Nov 20", "market data feed migration Dec 15", "memory leak risk engine", "deploy rollback option", "microsecond upgrade timeline"],
-        "priority_order": ["order matching latency", "memory leak risk engine", "SEC audit documentation", "market data migration"],
+        "must_mention": [
+            "order matching latency $40K/day",
+            "SEC audit Nov 20",
+            "market data feed migration Dec 15",
+            "memory leak risk engine",
+            "deploy rollback option",
+            "microsecond upgrade timeline",
+        ],
+        "priority_order": [
+            "order matching latency",
+            "memory leak risk engine",
+            "SEC audit documentation",
+            "market data migration",
+        ],
     },
     {
         "role": "VP Platform",
@@ -353,8 +536,21 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "todos": "- Coordinate DDoS mitigation (attack started 22:00 last night)\n- Prepare customer impact assessment\n- Evaluate WAF vendor proposals (Cloudflare vs Akamai)\n- Draft risk committee presentation",
         "messages": "- NOC: 'DDoS attack ongoing — 340Gbps, Cloudflare mitigating 95% but 5% getting through'\n- Fortune 500 client: 'Our SLA guarantees 99.99%, currently at 99.2% for November'\n- Legal: 'Three customers sent breach of contract notices'\n- Cloudflare TAM: 'Can upgrade to Enterprise+ with 1Tbps mitigation, $50K/month'\n- CFO: 'Board wants cyber insurance claim assessment'\n- CISO: 'Attack signature matches known botnet, FBI notified'",
         "news_interests": "DDoS mitigation, cloud security, SaaS operations",
-        "must_mention": ["DDoS 340Gbps", "Fortune 500 SLA breach", "breach of contract notices", "Cloudflare upgrade $50K", "FBI notified", "cyber insurance claim", "risk committee prep"],
-        "priority_order": ["DDoS mitigation", "Fortune 500 SLA", "breach of contract", "cyber insurance"],
+        "must_mention": [
+            "DDoS 340Gbps",
+            "Fortune 500 SLA breach",
+            "breach of contract notices",
+            "Cloudflare upgrade $50K",
+            "FBI notified",
+            "cyber insurance claim",
+            "risk committee prep",
+        ],
+        "priority_order": [
+            "DDoS mitigation",
+            "Fortune 500 SLA",
+            "breach of contract",
+            "cyber insurance",
+        ],
     },
     {
         "role": "Head of ML",
@@ -364,8 +560,20 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "todos": "- Investigate false negative in pedestrian detection model\n- Prepare safety data package for NHTSA\n- Review validation results for model v4.2\n- Coordinate OTA update for affected vehicles",
         "messages": "- Safety team: 'Vehicle #4892 near-miss incident — pedestrian not detected at dusk'\n- NHTSA: 'Requesting incident data within 48 hours per Standing General Order'\n- ML validation: 'v4.2 shows 0.3% regression in low-light pedestrian detection'\n- Legal: 'Do not communicate externally until safety review complete'\n- Fleet ops: '12,000 vehicles on v4.1, OTA update requires 72h rollout'\n- PR: 'Reuters reporter asking about safety incident reports'",
         "news_interests": "autonomous vehicles, ML safety, computer vision",
-        "must_mention": ["pedestrian detection near-miss", "NHTSA 48h data request", "v4.2 low-light regression", "12000 vehicles OTA", "Reuters inquiry", "legal communication hold"],
-        "priority_order": ["NHTSA data request", "pedestrian detection investigation", "OTA update planning", "legal hold"],
+        "must_mention": [
+            "pedestrian detection near-miss",
+            "NHTSA 48h data request",
+            "v4.2 low-light regression",
+            "12000 vehicles OTA",
+            "Reuters inquiry",
+            "legal communication hold",
+        ],
+        "priority_order": [
+            "NHTSA data request",
+            "pedestrian detection investigation",
+            "OTA update planning",
+            "legal hold",
+        ],
     },
     {
         "role": "VP Engineering",
@@ -375,8 +583,21 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "todos": "- Resolve core banking system freeze (customer transactions blocked)\n- Prepare OCC examination response materials\n- Coordinate Oracle emergency support (database deadlock)\n- Assess customer impact and communication plan",
         "messages": "- NOC: 'Core banking frozen at 06:15 — Oracle RAC deadlock, 450K transactions queued'\n- OCC examiner: 'Examination starts Monday, technology resilience focus area'\n- Customer ops: '2,300 customers called about failed transactions'\n- Oracle support: 'Severity 1 case opened, engineer assigned ETA 2h'\n- CFO: 'Regulatory fine risk if transactions not processed by EOD'\n- CISO: 'No security incident indicated, pure technology failure'",
         "news_interests": "banking technology, database systems, regulatory compliance",
-        "must_mention": ["core banking freeze", "450K queued transactions", "OCC examination Monday", "Oracle RAC deadlock", "2300 customer calls", "regulatory fine risk EOD", "Oracle engineer ETA 2h"],
-        "priority_order": ["Oracle deadlock resolution", "regulatory fine risk", "customer communication", "OCC examination prep"],
+        "must_mention": [
+            "core banking freeze",
+            "450K queued transactions",
+            "OCC examination Monday",
+            "Oracle RAC deadlock",
+            "2300 customer calls",
+            "regulatory fine risk EOD",
+            "Oracle engineer ETA 2h",
+        ],
+        "priority_order": [
+            "Oracle deadlock resolution",
+            "regulatory fine risk",
+            "customer communication",
+            "OCC examination prep",
+        ],
     },
     {
         "role": "Director of Engineering",
@@ -386,8 +607,20 @@ _HARD_TASKS: List[Dict[str, Any]] = [
         "todos": "- Finalize FDA 510(k) pre-submission package\n- Review clinical trial results for diagnostic AI accuracy\n- Address model drift detected in production deployment\n- Prepare for Monday's IRB ethics review",
         "messages": "- FDA liaison: 'Pre-submission meeting confirmed Nov 21, final materials due Nov 18'\n- Clinical team: 'Trial results: 94.2% sensitivity, 91.8% specificity — below 95% target for sensitivity'\n- ML ops: 'Model drift alert — AUC dropped from 0.96 to 0.89 over 30 days'\n- Legal: 'IRB flagged consent form language, revision needed before Monday'\n- Research lead: 'Promising approach to improve sensitivity — needs 2 weeks'\n- Quality: 'CAPA-2847 open: production model version mismatch between regions'",
         "news_interests": "medical AI, FDA regulation, clinical trials",
-        "must_mention": ["FDA materials due Nov 18", "sensitivity below target 94.2%", "model drift AUC 0.89", "IRB consent revision Monday", "CAPA-2847 version mismatch", "2-week sensitivity improvement"],
-        "priority_order": ["model drift", "IRB consent revision", "FDA materials", "sensitivity improvement decision"],
+        "must_mention": [
+            "FDA materials due Nov 18",
+            "sensitivity below target 94.2%",
+            "model drift AUC 0.89",
+            "IRB consent revision Monday",
+            "CAPA-2847 version mismatch",
+            "2-week sensitivity improvement",
+        ],
+        "priority_order": [
+            "model drift",
+            "IRB consent revision",
+            "FDA materials",
+            "sensitivity improvement decision",
+        ],
     },
 ]
 
@@ -429,19 +662,21 @@ class DailyDigestDataset(DatasetProvider):
                 news_interests=task["news_interests"],
             )
 
-            self._records.append(EvalRecord(
-                record_id=f"daily-digest-{idx:03d}",
-                problem=prompt,
-                reference="; ".join(task["must_mention"]),
-                category="agentic",
-                subject=diff,
-                metadata={
-                    "role": task["role"],
-                    "company": task["company"],
-                    "must_mention": task["must_mention"],
-                    "priority_order": task["priority_order"],
-                },
-            ))
+            self._records.append(
+                EvalRecord(
+                    record_id=f"daily-digest-{idx:03d}",
+                    problem=prompt,
+                    reference="; ".join(task["must_mention"]),
+                    category="agentic",
+                    subject=diff,
+                    metadata={
+                        "role": task["role"],
+                        "company": task["company"],
+                        "must_mention": task["must_mention"],
+                        "priority_order": task["priority_order"],
+                    },
+                )
+            )
 
     def iter_records(self) -> Iterable[EvalRecord]:
         return iter(self._records)

src/openjarvis/evals/datasets/deepplanning.py

@@ -110,15 +110,16 @@ class DeepPlanningDataset(DatasetProvider):
             from datasets import load_dataset
         except ImportError:
             raise ImportError(
-                "datasets required for DeepPlanning. "
-                "Install with: pip install datasets"
+                "datasets required for DeepPlanning. Install with: pip install datasets"
             )
         logger.info("Downloading Qwen/DeepPlanning from HuggingFace...")
         # Loading triggers the download even though we don't use the result
         load_dataset("Qwen/DeepPlanning", split="train")
 
     def _extract_cases(
-        self, tar_path: Path, level: int,
+        self,
+        tar_path: Path,
+        level: int,
     ) -> List[EvalRecord]:
         """Extract shopping cases from a tar.gz archive."""
         records: List[EvalRecord] = []
@@ -152,7 +153,10 @@ class DeepPlanningDataset(DatasetProvider):
                             products_text = pf.read().decode("utf-8").strip()
 
                     rec = self._case_to_record(
-                        data, level, case_name, products_text,
+                        data,
+                        level,
+                        case_name,
+                        products_text,
                     )
                     if rec:
                         records.append(rec)
@@ -185,15 +189,9 @@ class DeepPlanningDataset(DatasetProvider):
         reference = "; ".join(ref_parts) if ref_parts else ""
 
         # Count constraints
-        n_constraints = sum(
-            len(m.get("features", [])) for m in meta_info
-        )
+        n_constraints = sum(len(m.get("features", [])) for m in meta_info)
 
-        difficulty = (
-            "easy" if level == 1
-            else "medium" if level == 2
-            else "hard"
-        )
+        difficulty = "easy" if level == 1 else "medium" if level == 2 else "hard"
 
         # Build product catalog section
         catalog_section = ""

src/openjarvis/evals/datasets/email_triage.py

@@ -307,23 +307,22 @@ class EmailTriageDataset(DatasetProvider):
                 date=email["date"],
                 body=email["body"],
             )
-            reference = (
-                f"urgency: {email['urgency']}\n"
-                f"category: {email['category']}"
+            reference = f"urgency: {email['urgency']}\ncategory: {email['category']}"
+            self._records.append(
+                EvalRecord(
+                    record_id=f"email-triage-{idx}",
+                    problem=prompt,
+                    reference=reference,
+                    category="use-case",
+                    subject="email_triage",
+                    metadata={
+                        "urgency": email["urgency"],
+                        "category": email["category"],
+                        "sender": email["sender"],
+                        "subject_line": email["subject"],
+                    },
+                )
             )
-            self._records.append(EvalRecord(
-                record_id=f"email-triage-{idx}",
-                problem=prompt,
-                reference=reference,
-                category="use-case",
-                subject="email_triage",
-                metadata={
-                    "urgency": email["urgency"],
-                    "category": email["category"],
-                    "sender": email["sender"],
-                    "subject_line": email["subject"],
-                },
-            ))
 
     def iter_records(self) -> Iterable[EvalRecord]:
         return iter(self._records)