diff --git a/docs/architecture/engine.md b/docs/architecture/engine.md
index 0be515d0..7fad6232 100644
--- a/docs/architecture/engine.md
+++ b/docs/architecture/engine.md
@@ -116,7 +116,7 @@ All providers produce the same output format consumed by agents:
 | **LM Studio** | `lmstudio` | OpenAI-compatible | 1234 | No (GPU optional) | Desktop GUI, easy model management |
 | **Exo** | `exo` | OpenAI-compatible | 52415 | No (distributed) | Distributed inference across heterogeneous devices |
 | **Nexa** | `nexa` | OpenAI-compatible | 18181 | No (CPU/GPU) | On-device inference with GGUF models |
-| **Lemonade** | `lemonade` | OpenAI-compatible | 8000 | AMD GPU/NPU | AMD consumer GPUs (RDNA), Ryzen AI NPUs |
+| **Lemonade** | `lemonade` | OpenAI-compatible | 13305 | AMD GPU/NPU | AMD consumer GPUs (RDNA), Ryzen AI NPUs |
 | **Uzu** | `uzu` | OpenAI-compatible | 8000 | Varies | Uzu inference runtime |
 | **Apple FM** | `apple_fm` | OpenAI-compatible | 8079 | Apple Silicon | Apple Foundation Model on-device inference |
 | **LiteLLM** | `litellm` | OpenAI-compatible | — | No | Unified proxy to 100+ LLM providers |
@@ -135,7 +135,7 @@ The Ollama backend communicates via Ollama's native HTTP API at `/api/chat` and
 
 The vLLM backend uses the OpenAI-compatible `/v1/chat/completions` API. It is recommended for datacenter GPUs (NVIDIA A100, H100, L40, A10, A30 and AMD MI300, MI325, MI350, MI355).
 
-- **Default host:** `http://localhost:8000`
+- **Default host:** `http://localhost:13305`
 - **Health check:** `GET /v1/models`
 - **Tool fallback:** If the server returns HTTP 400 when tools are included, the engine automatically retries without tools
 
@@ -204,7 +204,7 @@ The Nexa backend connects to the Nexa SDK on-device inference server via a FastA
 
 The Lemonade backend connects to the [Lemonade](https://lemonade-server.ai/) inference server, which is optimized for AMD consumer GPUs (RDNA architecture) and Ryzen AI Neural Processing Units (NPUs). It uses the OpenAI-compatible `/v1/chat/completions` API.
 
-- **Default host:** `http://localhost:8000`
+- **Default host:** `http://localhost:13305`
 - **Health check:** `GET /v1/models`
 - **Install:** Visit [lemonade-server.ai](https://lemonade-server.ai/) for platform-specific installation instructions
 - **Best for:** Ryzen AI GPUs and NPUs, and AMD-based desktop and laptop systems
@@ -357,7 +357,7 @@ host = "http://localhost:30000"
 # binary_path = ""
 
 # [engine.lemonade]
-# host = "http://localhost:8000"
+# host = "http://localhost:13305"
 ```
 
 The `EngineConfig` dataclass and its per-engine sub-dataclasses map these settings:
@@ -370,7 +370,7 @@ The `EngineConfig` dataclass and its per-engine sub-dataclasses map these settin
 | `SGLangEngineConfig` | `host` | `http://localhost:30000` | SGLang server URL |
 | `LlamaCppEngineConfig` | `host` | `http://localhost:8080` | llama.cpp server URL |
 | `LlamaCppEngineConfig` | `binary_path` | `""` | Path to llama.cpp binary (for managed mode) |
-| `LemonadeEngineConfig` | `host` | `http://localhost:8000` | Lemonade server URL |
+| `LemonadeEngineConfig` | `host` | `http://localhost:13305` | Lemonade server URL |
 
 !!! note "Backward compatibility"
     The old flat field names `ollama_host`, `vllm_host`, `llamacpp_host`, `llamacpp_path`, `sglang_host`, and `lemonade_host` under `[engine]` are still accepted as backward-compatible properties on `EngineConfig`. New configurations should use the nested sub-section format.
diff --git a/docs/user-guide/skills.md b/docs/user-guide/skills.md
index 05717262..9786fdc4 100644
--- a/docs/user-guide/skills.md
+++ b/docs/user-guide/skills.md
@@ -148,6 +148,14 @@ jarvis skill sync openclaw --search "web3|crypto"
 jarvis skill install github:user/repo/path/to/skill --url https://github.com/user/repo
 ```
 
+For example, install the Hermes Tweet skill when you want an agent to search
+Twitter/X, read tweet replies, monitor tweets, export followers, and run
+gated post, reply, or DM workflows:
+
+```bash
+jarvis skill install github:Xquik-dev/hermes-tweet/skills/hermes-tweet --url https://github.com/Xquik-dev/hermes-tweet
+```
+
 ### Config-Driven Auto Import
 
 Add sources to `~/.openjarvis/config.toml` for automatic syncing:
diff --git a/src/openjarvis/agents/executor.py b/src/openjarvis/agents/executor.py
index 8d6be76f..3feed1d3 100644
--- a/src/openjarvis/agents/executor.py
+++ b/src/openjarvis/agents/executor.py
@@ -317,6 +317,24 @@ class AgentExecutor:
                         tool_instances.append(tool)
                     except Exception:
                         logger.warning("Failed to instantiate tool %s", tname)
+
+            # Pull tools already discovered by SystemBuilder (e.g. external MCP
+            # adapters) that aren't in the static ToolRegistry. Without this,
+            # agents declaring MCP-discovered tools in their template would
+            # silently fall back to natives only.
+            if (
+                self._system is not None
+                and getattr(self._system, "tool_executor", None) is not None
+            ):
+                mcp_pool = getattr(self._system.tool_executor, "_tools", {}) or {}
+                existing = {t.spec.name for t in tool_instances}
+                for tname in tool_names:
+                    if tname in existing:
+                        continue
+                    pooled = mcp_pool.get(tname)
+                    if pooled is not None:
+                        tool_instances.append(pooled)
+
             if tool_instances:
                 logger.info(
                     "Agent %s: resolved %d/%d tools",
@@ -332,6 +350,12 @@ class AgentExecutor:
             agent_kwargs["system_prompt"] = sys_prompt
         if getattr(agent_cls, "accepts_tools", False) and tool_instances:
             agent_kwargs["tools"] = tool_instances
+        # Propagate confirmation policy from the AgentExecutor down to the
+        # agent's own ToolExecutor. Set by CLI paths like `jarvis agents ask`
+        # so non-interactive runs can auto-approve tool execution.
+        if getattr(self, "_confirm_callback", None) is not None:
+            agent_kwargs["interactive"] = True
+            agent_kwargs["confirm_callback"] = self._confirm_callback
         try:
             agent_instance = agent_cls(engine, model, **agent_kwargs)
         except TypeError:
diff --git a/src/openjarvis/cli/agent_cmd.py b/src/openjarvis/cli/agent_cmd.py
index db24144c..31724ef5 100644
--- a/src/openjarvis/cli/agent_cmd.py
+++ b/src/openjarvis/cli/agent_cmd.py
@@ -702,16 +702,34 @@ def errors():
 @agent.command("ask")
 @click.argument("agent_id")
 @click.argument("message")
-def ask(agent_id, message):
+@click.option(
+    "--yes/--no-yes",
+    "auto_approve",
+    default=True,
+    help="Auto-approve tool execution that would otherwise need confirmation. "
+    "Default: on (suits non-interactive CLI use). Pass --no-yes to require a "
+    "TTY prompt for tools whose ToolSpec sets requires_confirmation=True.",
+)
+def ask(agent_id, message, auto_approve):
     """Ask an agent a question (immediate response)."""
     manager = _get_manager()
     agent_id = _resolve_agent_id(manager, agent_id)
     manager.send_message(agent_id, message, mode="immediate")
     click.echo("Asking agent...")
-    _, executor, _ = _get_scheduler_and_executor()
+    _, executor, system = _get_scheduler_and_executor()
     if executor is None:
         click.echo("Executor not available", err=True)
         raise SystemExit(1)
+    # Wire a confirmation callback so the agent's own ToolExecutor can actually
+    # run tools whose ToolSpec sets requires_confirmation=True (e.g. shell_exec,
+    # git_*). `executor` is the AgentExecutor; the callback is read in
+    # _invoke_agent and propagated to the constructed agent via agent_kwargs.
+    if auto_approve:
+        executor._confirm_callback = lambda _prompt: True
+    else:
+        executor._confirm_callback = (
+            lambda prompt: click.confirm(f"\n{prompt}", default=False)
+        )
     executor.execute_tick(agent_id)
     msgs = manager.list_messages(agent_id)
     responses = [m for m in msgs if m["direction"] == "agent_to_user"]
diff --git a/src/openjarvis/core/config.py b/src/openjarvis/core/config.py
index a00f48cd..c7f6bb7d 100644
--- a/src/openjarvis/core/config.py
+++ b/src/openjarvis/core/config.py
@@ -280,14 +280,14 @@ _MODEL_TIERS = [
     (64, "qwen3.5:27b"),
 ]
 _MODEL_TIER_FALLBACK = "qwen3.5:27b"
+_LEMONADE_DEFAULT_MODEL = "Qwen3.6-35B-A3B-GGUF"
 
 
 def recommend_model(hw: HardwareInfo, engine: str) -> str:
-    """Suggest the best Qwen3.5 model that fits the detected hardware.
+    """Suggest a default model for the selected engine and hardware.
 
-    Uses an explicit tier table mapping available memory to model size.
-    Falls back to scanning the full catalog if the tiered model is not
-    compatible with the selected engine.
+    For Lemonade, prefer the validated Qwen3.6 35B A3B GGUF default.
+    For other local engines, use the generic Qwen3.5 tier mapping.
     """
     from openjarvis.intelligence.model_catalog import BUILTIN_MODELS
 
@@ -295,6 +295,9 @@ def recommend_model(hw: HardwareInfo, engine: str) -> str:
     if available_gb <= 0:
         return ""
 
+    if engine == "lemonade":
+        return _LEMONADE_DEFAULT_MODEL
+
     # Build a lookup for quick engine-compatibility checks
     catalog = {spec.model_id: spec for spec in BUILTIN_MODELS}
 
@@ -422,7 +425,7 @@ class GemmaCppEngineConfig:
 class LemonadeEngineConfig:
     """Per-engine config for Lemonade."""
 
-    host: str = "http://localhost:8000"
+    host: str = "http://localhost:13305"
 
 
 @dataclass
diff --git a/src/openjarvis/engine/openai_compat_engines.py b/src/openjarvis/engine/openai_compat_engines.py
index 95ec1200..6d191f3d 100644
--- a/src/openjarvis/engine/openai_compat_engines.py
+++ b/src/openjarvis/engine/openai_compat_engines.py
@@ -13,7 +13,7 @@ _ENGINES = {
     "nexa": ("NexaEngine", "http://localhost:18181", "/v1"),
     "uzu": ("UzuEngine", "http://localhost:8000", ""),
     "apple_fm": ("AppleFmEngine", "http://localhost:8079", "/v1"),
-    "lemonade": ("LemonadeEngine", "http://localhost:8000", "/v1"),
+    "lemonade": ("LemonadeEngine", "http://localhost:13305", "/v1"),
 }
 
 for _key, (_cls_name, _default_host, _api_prefix) in _ENGINES.items():
diff --git a/src/openjarvis/mcp/client.py b/src/openjarvis/mcp/client.py
index c37a04a0..5b495922 100644
--- a/src/openjarvis/mcp/client.py
+++ b/src/openjarvis/mcp/client.py
@@ -84,11 +84,15 @@ class MCPClient:
         """
         response = self._send("tools/list")
         tools = response.result.get("tools", [])
+        # MCP tools often wrap long-running pentest/scan commands. The default
+        # ToolSpec timeout (30s) kills them mid-scan. Bump to 600s — individual
+        # MCP servers can shorten via their own protocol if needed.
         return [
             ToolSpec(
                 name=t["name"],
                 description=t.get("description", ""),
                 parameters=t.get("inputSchema", {}),
+                timeout_seconds=600.0,
             )
             for t in tools
         ]
diff --git a/src/openjarvis/telemetry/gpu_monitor.py b/src/openjarvis/telemetry/gpu_monitor.py
index 6690b941..23927db9 100644
--- a/src/openjarvis/telemetry/gpu_monitor.py
+++ b/src/openjarvis/telemetry/gpu_monitor.py
@@ -13,7 +13,6 @@ logger = logging.getLogger(__name__)
 
 try:
     import pynvml
-
     _PYNVML_AVAILABLE = True
 except ImportError:
     _PYNVML_AVAILABLE = False
@@ -23,7 +22,6 @@ except ImportError:
 # Hardware spec database
 # ---------------------------------------------------------------------------
 
-
 @dataclass(frozen=True)
 class GpuHardwareSpec:
     """Peak theoretical capabilities for a known GPU model."""
@@ -50,6 +48,26 @@ GPU_SPECS: Dict[str, GpuHardwareSpec] = {
     # Apple Silicon
     "M4 Max": GpuHardwareSpec(tflops_fp16=53, bandwidth_gb_s=546, tdp_watts=40),
     "M2 Ultra": GpuHardwareSpec(tflops_fp16=27, bandwidth_gb_s=800, tdp_watts=60),
+    # Intel Arc
+    "Arc B580": GpuHardwareSpec(tflops_fp16=196, bandwidth_gb_s=456, tdp_watts=190),
+    "Arc B570": GpuHardwareSpec(tflops_fp16=136, bandwidth_gb_s=380, tdp_watts=150),
+    # NVIDIA Jetson
+    "Jetson Orin NX 16GB": GpuHardwareSpec(
+        tflops_fp16=50, bandwidth_gb_s=102, tdp_watts=25
+    ),
+    "Jetson Orin NX 8GB": GpuHardwareSpec(
+        tflops_fp16=25, bandwidth_gb_s=68, tdp_watts=15
+    ),
+    "Jetson AGX Orin": GpuHardwareSpec(
+        tflops_fp16=108, bandwidth_gb_s=204, tdp_watts=60
+    ),
+    # Qualcomm
+    "Snapdragon X Elite": GpuHardwareSpec(
+        tflops_fp16=4.6, bandwidth_gb_s=136, tdp_watts=80
+    ),
+    "Snapdragon X Plus": GpuHardwareSpec(
+        tflops_fp16=3.8, bandwidth_gb_s=136, tdp_watts=80
+    ),
 }
 
 
@@ -70,7 +88,6 @@ def lookup_gpu_spec(name: str) -> Optional[GpuHardwareSpec]:
 # Snapshot & aggregated sample
 # ---------------------------------------------------------------------------
 
-
 @dataclass
 class GpuSnapshot:
     """A single point-in-time reading from one GPU device."""
@@ -103,7 +120,6 @@ class GpuSample:
 # Monitor
 # ---------------------------------------------------------------------------
 
-
 class GpuMonitor:
     """Background GPU poller using pynvml.
 
@@ -219,6 +235,7 @@ class GpuMonitor:
             mean_util = sum(s.utilization_pct for s in tick_snaps) / len(tick_snaps)
             total_mem = sum(s.memory_used_gb for s in tick_snaps)
             mean_temp = sum(s.temperature_c for s in tick_snaps) / len(tick_snaps)
+
             tick_powers.append(total_power)
             tick_utils.append(mean_util)
             tick_mems.append(total_mem)
@@ -256,7 +273,6 @@ class GpuMonitor:
         :class:`GpuSample` without starting a background thread.
         """
         result = GpuSample()
-
         if not self._initialized or self._device_count == 0:
             t_start = time.monotonic()
             yield result
@@ -276,11 +292,13 @@ class GpuMonitor:
 
         t_start = time.monotonic()
         thread.start()
+
         try:
             yield result
         finally:
             stop_event.set()
             thread.join(timeout=2.0)
+
             wall = time.monotonic() - t_start
 
             with lock:
diff --git a/tests/core/test_config.py b/tests/core/test_config.py
index 864e843e..337f671f 100644
--- a/tests/core/test_config.py
+++ b/tests/core/test_config.py
@@ -37,10 +37,12 @@ class TestDefaults:
         assert ec.vllm.host == "http://localhost:8000"
         assert ec.sglang.host == "http://localhost:30000"
         assert ec.llamacpp.host == "http://localhost:8080"
+        assert ec.lemonade.host == "http://localhost:13305"
         assert ec.llamacpp.binary_path == ""
         # Backward-compat properties still work
         assert ec.ollama_host == ""
         assert ec.vllm_host == "http://localhost:8000"
+        assert ec.lemonade_host == "http://localhost:13305"
 
 
 class TestRecommendEngine:
@@ -93,6 +95,17 @@ class TestTomlLoading:
         assert cfg.engine.default == "vllm"
         assert cfg.memory.default_backend == "faiss"
 
+    def test_loads_nested_lemonade_host_override(self, tmp_path: Path) -> None:
+        toml_file = tmp_path / "config.toml"
+        toml_file.write_text(
+            '[engine]\ndefault = "lemonade"\n\n'
+            '[engine.lemonade]\nhost = "http://custom-lemonade:19000"\n'
+        )
+        cfg = load_config(toml_file)
+        assert cfg.engine.default == "lemonade"
+        assert cfg.engine.lemonade.host == "http://custom-lemonade:19000"
+        assert cfg.engine.lemonade_host == "http://custom-lemonade:19000"
+
 
 class TestGenerateToml:
     def test_contains_engine_section(self) -> None:
@@ -213,6 +226,7 @@ class TestNestedEngineConfig:
         assert ec.vllm.host == "http://localhost:8000"
         assert ec.sglang.host == "http://localhost:30000"
         assert ec.llamacpp.host == "http://localhost:8080"
+        assert ec.lemonade.host == "http://localhost:13305"
         assert ec.llamacpp.binary_path == ""
 
     def test_backward_compat_setter(self) -> None:
@@ -250,6 +264,17 @@ class TestNestedEngineConfig:
         assert cfg.engine.ollama.host == "http://old:11434"
         assert cfg.engine.vllm.host == "http://old:8000"
 
+    def test_loads_old_flat_lemonade_host(self, tmp_path: Path) -> None:
+        toml_file = tmp_path / "config.toml"
+        toml_file.write_text(
+            '[engine]\ndefault = "lemonade"\n'
+            'lemonade_host = "http://legacy-lemonade:19191"\n'
+        )
+        cfg = load_config(toml_file)
+        assert cfg.engine.default == "lemonade"
+        assert cfg.engine.lemonade.host == "http://legacy-lemonade:19191"
+        assert cfg.engine.lemonade_host == "http://legacy-lemonade:19191"
+
 
 class TestNestedLearningConfig:
     def test_defaults(self) -> None:
diff --git a/tests/core/test_recommend_model.py b/tests/core/test_recommend_model.py
index 77b0be89..b8c95f8d 100644
--- a/tests/core/test_recommend_model.py
+++ b/tests/core/test_recommend_model.py
@@ -86,6 +86,20 @@ class TestRecommendModelGpu:
         # available = 288 GB → tier fallback qwen3.5:27b, valid for vllm
         assert result == "qwen3.5:27b"
 
+    def test_amd_lemonade_picks_qwen36_35b_a3b(self) -> None:
+        hw = HardwareInfo(
+            platform="linux",
+            ram_gb=64.0,
+            gpu=GpuInfo(
+                vendor="amd",
+                name="Radeon RX 7900 XTX",
+                vram_gb=24.0,
+                count=1,
+            ),
+        )
+        result = recommend_model(hw, "lemonade")
+        assert result == "Qwen3.6-35B-A3B-GGUF"
+
 
 class TestRecommendModelEdgeCases:
     """Edge cases."""
diff --git a/tests/engine/test_engine_model_matrix.py b/tests/engine/test_engine_model_matrix.py
index 9547ff0b..36888a41 100644
--- a/tests/engine/test_engine_model_matrix.py
+++ b/tests/engine/test_engine_model_matrix.py
@@ -32,7 +32,7 @@ _OPENAI_COMPAT_ENGINES = [
     ("nexa", "http://testhost:18181", NexaEngine),
     ("uzu", "http://testhost:8000", UzuEngine),
     ("apple_fm", "http://testhost:8079", AppleFmEngine),
-    ("lemonade", "http://testhost:8000", LemonadeEngine),
+    ("lemonade", "http://testhost:13305", LemonadeEngine),
 ]
 
 
diff --git a/tests/engine/test_lemonade.py b/tests/engine/test_lemonade.py
index d5bc0e37..385ed25d 100644
--- a/tests/engine/test_lemonade.py
+++ b/tests/engine/test_lemonade.py
@@ -19,7 +19,7 @@ from openjarvis.engine.openai_compat_engines import LemonadeEngine
 @pytest.fixture()
 def engine() -> LemonadeEngine:
     EngineRegistry.register_value("lemonade", LemonadeEngine)
-    return LemonadeEngine(host="http://testhost:8000")
+    return LemonadeEngine(host="http://testhost:13305")
 
 
 class TestLemonadeEngineBasics:
@@ -27,7 +27,7 @@ class TestLemonadeEngineBasics:
         assert LemonadeEngine.engine_id == "lemonade"
 
     def test_default_host(self) -> None:
-        assert LemonadeEngine._default_host == "http://localhost:8000"
+        assert LemonadeEngine._default_host == "http://localhost:13305"
 
     def test_api_prefix(self) -> None:
         assert LemonadeEngine._api_prefix == "/v1"
@@ -36,11 +36,22 @@ class TestLemonadeEngineBasics:
         EngineRegistry.register_value("lemonade", LemonadeEngine)
         assert EngineRegistry.get("lemonade") is LemonadeEngine
 
+    def test_env_var_overrides_default_host(
+        self,
+        monkeypatch: pytest.MonkeyPatch,
+    ) -> None:
+        monkeypatch.setenv("LEMONADE_HOST", "http://env-lemonade:17777")
+        engine = LemonadeEngine()
+        try:
+            assert engine._host == "http://env-lemonade:17777"
+        finally:
+            engine.close()
+
 
 class TestLemonadeGenerate:
     def test_generate_uses_v1_prefix(self, engine: LemonadeEngine) -> None:
         with respx.mock:
-            respx.post("http://testhost:8000/v1/chat/completions").mock(
+            respx.post("http://testhost:13305/v1/chat/completions").mock(
                 return_value=httpx.Response(
                     200,
                     json={
@@ -67,7 +78,7 @@ class TestLemonadeGenerate:
 
     def test_generate_connection_error(self, engine: LemonadeEngine) -> None:
         with respx.mock:
-            respx.post("http://testhost:8000/v1/chat/completions").mock(
+            respx.post("http://testhost:13305/v1/chat/completions").mock(
                 side_effect=httpx.ConnectError("refused")
             )
             with pytest.raises(EngineConnectionError):
@@ -80,14 +91,14 @@ class TestLemonadeGenerate:
 class TestLemonadeHealth:
     def test_health_true(self, engine: LemonadeEngine) -> None:
         with respx.mock:
-            respx.get("http://testhost:8000/v1/models").mock(
+            respx.get("http://testhost:13305/v1/models").mock(
                 return_value=httpx.Response(200, json={"data": []})
             )
             assert engine.health() is True
 
     def test_health_false(self, engine: LemonadeEngine) -> None:
         with respx.mock:
-            respx.get("http://testhost:8000/v1/models").mock(
+            respx.get("http://testhost:13305/v1/models").mock(
                 side_effect=httpx.ConnectError("refused")
             )
             assert engine.health() is False
@@ -96,7 +107,7 @@ class TestLemonadeHealth:
 class TestLemonadeListModels:
     def test_list_models_uses_v1_prefix(self, engine: LemonadeEngine) -> None:
         with respx.mock:
-            respx.get("http://testhost:8000/v1/models").mock(
+            respx.get("http://testhost:13305/v1/models").mock(
                 return_value=httpx.Response(
                     200,
                     json={
diff --git a/tests/telemetry/test_gpu_monitor.py b/tests/telemetry/test_gpu_monitor.py
index e4b0f1dc..9ba6dfc5 100644
--- a/tests/telemetry/test_gpu_monitor.py
+++ b/tests/telemetry/test_gpu_monitor.py
@@ -14,7 +14,6 @@ import pytest
 # Helpers: build a fake pynvml module
 # ---------------------------------------------------------------------------
 
-
 @dataclass
 class _FakeUtilization:
     gpu: int = 80
@@ -60,7 +59,6 @@ def _snap(power=300, util=80, mem=12, temp=65, dev=0):
 # Tests: GpuHardwareSpec lookup
 # ---------------------------------------------------------------------------
 
-
 class TestGpuHardwareSpec:
     def test_lookup_exact_key(self):
         from openjarvis.telemetry.gpu_monitor import lookup_gpu_spec
@@ -107,6 +105,13 @@ class TestGpuHardwareSpec:
             "MI250X",
             "M4 Max",
             "M2 Ultra",
+            "Arc B580",
+            "Arc B570",
+            "Jetson Orin NX 16GB",
+            "Jetson Orin NX 8GB",
+            "Jetson AGX Orin",
+            "Snapdragon X Elite",
+            "Snapdragon X Plus",
         }
         assert set(GPU_SPECS.keys()) == expected
 
@@ -122,7 +127,6 @@ class TestGpuHardwareSpec:
 # Tests: energy integration math (trapezoidal rule)
 # ---------------------------------------------------------------------------
 
-
 class TestEnergyIntegration:
     def test_constant_power(self):
         """Constant 300W for 10 seconds = 3000 J."""
@@ -130,7 +134,6 @@ class TestEnergyIntegration:
 
         snapshots = [[_snap(power=300)] for _ in range(11)]
         timestamps = [float(i) for i in range(11)]
-
         sample = GpuMonitor._aggregate(snapshots, timestamps, wall_duration=10.0)
         assert sample.energy_joules == pytest.approx(3000.0, rel=1e-6)
         assert sample.mean_power_watts == pytest.approx(300.0, rel=1e-6)
@@ -146,7 +149,6 @@ class TestEnergyIntegration:
             [_snap(power=100.0 * i, util=50, mem=8, temp=60)] for i in range(5)
         ]
         timestamps = [float(i) for i in range(5)]
-
         sample = GpuMonitor._aggregate(snapshots, timestamps, wall_duration=4.0)
         assert sample.energy_joules == pytest.approx(800.0, rel=1e-6)
         assert sample.mean_power_watts == pytest.approx(200.0, rel=1e-6)
@@ -167,7 +169,6 @@ class TestEnergyIntegration:
 
         snapshots = [[_snap(power=250, util=90, mem=16, temp=70)]]
         timestamps = [0.0]
-
         sample = GpuMonitor._aggregate(snapshots, timestamps, wall_duration=0.05)
         assert sample.energy_joules == 0.0
         assert sample.num_snapshots == 1
@@ -178,7 +179,6 @@ class TestEnergyIntegration:
 # Tests: GpuSample aggregation
 # ---------------------------------------------------------------------------
 
-
 class TestGpuSampleAggregation:
     def test_peak_values(self):
         from openjarvis.telemetry.gpu_monitor import GpuMonitor
@@ -189,7 +189,6 @@ class TestGpuSampleAggregation:
             [_snap(power=300, util=70, mem=15, temp=65)],
         ]
         timestamps = [0.0, 1.0, 2.0]
-
         sample = GpuMonitor._aggregate(snapshots, timestamps, wall_duration=2.0)
         assert sample.peak_power_watts == pytest.approx(400.0)
         assert sample.peak_utilization_pct == pytest.approx(95.0)
@@ -205,7 +204,6 @@ class TestGpuSampleAggregation:
             [_snap(power=300, util=80, mem=16, temp=70)],
         ]
         timestamps = [0.0, 1.0, 2.0]
-
         sample = GpuMonitor._aggregate(snapshots, timestamps, wall_duration=2.0)
         assert sample.mean_power_watts == pytest.approx(200.0)
         assert sample.mean_utilization_pct == pytest.approx(60.0)
@@ -217,7 +215,6 @@ class TestGpuSampleAggregation:
 # Tests: Multi-GPU aggregation
 # ---------------------------------------------------------------------------
 
-
 class TestMultiGpu:
     def test_multi_device_power_sum(self):
         """Power summed across devices; util/temp averaged."""
@@ -229,7 +226,6 @@ class TestMultiGpu:
         ]
         snapshots = [tick, tick]
         timestamps = [0.0, 1.0]
-
         sample = GpuMonitor._aggregate(snapshots, timestamps, wall_duration=1.0)
         assert sample.energy_joules == pytest.approx(500.0)
         assert sample.mean_power_watts == pytest.approx(500.0)
@@ -252,7 +248,6 @@ class TestMultiGpu:
             ],
         ]
         timestamps = [0.0, 2.0]
-
         sample = GpuMonitor._aggregate(snapshots, timestamps, wall_duration=2.0)
         # Tick powers: 200, 600 => 0.5*(200+600)*2 = 800
         assert sample.energy_joules == pytest.approx(800.0)
@@ -263,7 +258,6 @@ class TestMultiGpu:
 # Tests: context manager flow (with mocked pynvml)
 # ---------------------------------------------------------------------------
 
-
 class TestContextManager:
     def test_sample_context_manager(self):
         """sample() starts/stops polling and populates result."""
@@ -280,10 +274,8 @@ class TestContextManager:
             monitor._initialized = True
             monitor._device_count = 1
             monitor._handles = ["handle-0"]
-
             with monitor.sample() as result:
                 time.sleep(0.1)
-
             assert result.duration_seconds > 0
             assert result.num_snapshots > 0
             assert result.mean_power_watts > 0
@@ -301,10 +293,8 @@ class TestContextManager:
         monitor._handles = []
         monitor._device_count = 0
         monitor._initialized = False
-
         with monitor.sample() as result:
             pass
-
         assert result.num_snapshots == 0
         assert result.energy_joules == 0.0
         assert result.duration_seconds >= 0
@@ -314,7 +304,6 @@ class TestContextManager:
 # Tests: available()
 # ---------------------------------------------------------------------------
 
-
 class TestAvailable:
     def test_available_false_when_pynvml_missing(self):
         """available() returns False when pynvml not importable."""
@@ -330,7 +319,6 @@ class TestAvailable:
     def test_available_true_with_fake_pynvml(self):
         """available() returns True when pynvml can init."""
         fake_pynvml = _make_fake_pynvml()
-
         with patch.dict(sys.modules, {"pynvml": fake_pynvml}):
             import openjarvis.telemetry.gpu_monitor as mod
 
@@ -348,7 +336,6 @@ class TestAvailable:
         """available() returns False when nvmlInit raises."""
         fake_pynvml = _make_fake_pynvml()
         fake_pynvml.nvmlInit.side_effect = RuntimeError("no driver")
-
         with patch.dict(sys.modules, {"pynvml": fake_pynvml}):
             import openjarvis.telemetry.gpu_monitor as mod
 
@@ -365,7 +352,6 @@ class TestAvailable:
 # Tests: dataclass defaults
 # ---------------------------------------------------------------------------
 
-
 class TestDataclasses:
     def test_gpu_snapshot_defaults(self):
         from openjarvis.telemetry.gpu_monitor import GpuSnapshot