* refactor(tauri): update development scripts and configuration for CEF integration - Modified `package.json` scripts to consistently export `CEF_PATH` for all `cargo tauri` commands, ensuring a unified CEF binary distribution location. - Removed the overlay window configuration from `tauri.conf.json` and updated related Rust functions to reflect this change, while retaining helper functions for potential future use. - Updated documentation in `install.md` to clarify the importance of setting `CEF_PATH` for consistent CEF integration across builds. - Enhanced the `ensure-tauri-cli.sh` script to set `CEF_PATH` and ensure proper installation of the vendored CEF-aware `tauri-cli`. These changes streamline the development workflow and improve the reliability of CEF integration in the application. * refactor(release): enhance macOS signing script for nested frameworks and helper apps - Introduced a new `codesign_hardened` function to streamline the signing process with consistent options. - Improved the signing logic for nested frameworks and helper applications, ensuring all binaries are signed correctly. - Updated output messages for better clarity during the signing process, including detailed listings of bundle contents. - Disabled the summarizer payload threshold in the configuration to prevent recursive invocations until the issue is resolved. These changes improve the reliability and maintainability of the macOS signing and notarization workflow. * feat(orchestrator): add current_time tool and enhance agent capabilities - Introduced the `current_time` tool to provide the current date and time in UTC and local time zones, facilitating scheduling and reminders. - Updated `agent.toml` to include new tools: `current_time`, `cron_add`, `cron_list`, `cron_remove`, and `schedule`, enhancing the orchestrator's functionality. - Expanded documentation in `prompt.md` to guide users on utilizing the new direct tools effectively. These changes improve the orchestrator's ability to handle time-related queries and scheduling tasks directly, enhancing user experience. * feat(gmail): implement post-processing for Gmail responses to convert HTML to markdown - Added a new `post_process` module specifically for Gmail, which modifies action responses to convert HTML content into markdown format, improving usability and reducing context token usage. - Enhanced the `ComposioProvider` trait with a `post_process_action_result` method to allow providers to handle response modifications. - Introduced a `post_process` function that checks for a `raw_html` flag in the arguments to determine whether to apply the conversion. - Implemented tests to validate the HTML detection and conversion logic, ensuring the integrity of the post-processing functionality. These changes enhance the handling of Gmail responses, making them more suitable for further processing and display in the application. * refactor(gmail): improve HTML to markdown conversion and tool result budget - Enhanced the `post_process` module for Gmail to handle large HTML payloads more efficiently, implementing a fallback mechanism for oversized content. - Updated the `DEFAULT_TOOL_RESULT_BUDGET_BYTES` to `0`, disabling the budget temporarily while reworking the oversized-output path. - Refined the `extract_markdown_body` function to better manage HTML content, ensuring cleaner markdown output and improved performance. - Added utility functions for stripping HTML noise and handling large email bodies, enhancing the overall robustness of the email processing logic. These changes optimize the handling of Gmail responses, improving usability and performance in processing large HTML content. * feat(thread): implement thread title generation from user and assistant messages - Added a new `generateTitleIfNeeded` function in the `threadApi` to create a thread title based on the first user message and the assistant's reply. - Introduced a new `GenerateConversationThreadTitleRequest` struct to handle requests for title generation. - Updated the `ChatRuntimeProvider` to dispatch the title generation action after processing inference responses. - Enhanced the `threadSlice` with a new async thunk for generating thread titles, ensuring proper error handling and thread loading. - Added tests for the new title generation functionality to validate the integration with the threads RPC. These changes improve the user experience by automatically generating relevant thread titles, enhancing the organization of conversations. * feat(conversations): add thread title update functionality - Implemented `update_thread_title` method in `ConversationStore` to allow updating the title of existing conversation threads. - Added a corresponding public function `update_thread_title` for external access. - Enhanced tests to verify that thread titles are correctly updated and persisted in the store. These changes improve the management of conversation threads by enabling dynamic title updates, enhancing user experience and organization. * feat(docs): add comprehensive agent and subagent tool flow documentation - Introduced a new document detailing the runtime flow of the agent harness, including execution paths for main agents and tools. - Explained the differences between typed and fork subagents, and provided guidance for debugging harness and delegation issues. - Included a file map outlining key components and their roles within the Rust implementation. - Added a flow diagram to visually represent the interaction between agents, tools, and subagents. These changes enhance the understanding of the agent architecture and improve the documentation for developers working with the system. * feat(subagent): implement extraction tool and handoff cache for oversized results - Introduced `extract_from_result` tool to allow targeted queries against oversized tool outputs, improving efficiency by directly interacting with the extraction model. - Added `ResultHandoffCache` to manage oversized payloads, enabling progressive disclosure and reducing context length issues in sub-agent history. - Implemented hygiene helpers for cleaning tool outputs before caching, ensuring only relevant data is stored. - Enhanced the sub-agent runner with new modules for tool preparation and execution, streamlining the overall agent workflow. These changes enhance the sub-agent's ability to handle large tool results effectively, improving performance and user experience. * feat(conversations): enhance message bubble rendering and timeline entry formatting - Introduced new utility functions for parsing and rendering agent messages, including `splitAgentMessageIntoBubbles` and `parseMarkdownTable`, to improve the display of messages in conversation threads. - Implemented `BubbleMarkdown` and `TableCellMarkdown` components for better formatting of user and agent messages, ensuring consistent styling and interaction. - Enhanced the `formatTimelineEntry` function to provide clearer titles and details for tool timeline entries, improving the user experience during interactions with subagents. - Updated the `ChatRuntimeProvider` to utilize the new formatting functions, ensuring that tool timeline entries are displayed with relevant context and detail. These changes improve the overall presentation and usability of conversation messages and tool interactions, enhancing user engagement and clarity. * feat(subagent): enforce restrictions on sub-agent spawning tools - Introduced a filter to prevent sub-agents from invoking their own spawning tools, specifically `spawn_subagent` and `delegate_*`, to avoid recursion issues and ensure proper delegation by the top-level orchestrator. - Updated the `is_subagent_spawn_tool` function to identify these tools and integrated checks in both `run_typed_mode` and `run_fork_mode` to maintain the integrity of the sub-agent execution environment. - Enhanced logging to track the removal of restricted tools from the sub-agent's tool surface, improving observability and debugging capabilities. These changes strengthen the sub-agent architecture by enforcing strict boundaries on tool invocation, enhancing stability and performance. * feat(conversations): add ToolTimelineBlock component and enhance timeline entry formatting - Introduced the `ToolTimelineBlock` component to display tool timeline entries with improved formatting and user interaction, including auto-expansion for running entries. - Enhanced the `formatTimelineEntry` function to include user-friendly titles for specific tool actions, such as 'Viewing your Integrations'. - Updated the rendering logic in the `Conversations` component to filter and display visible messages more effectively, improving user experience during conversations. These changes enhance the clarity and usability of tool interactions within conversation threads, providing users with better context and engagement. * refactor(conversations): streamline component imports and enhance formatting consistency - Consolidated import statements in `Conversations.tsx` and `ChatRuntimeProvider.tsx` for improved readability. - Refactored the `ToolTimelineBlock` component to simplify its props structure. - Enhanced formatting consistency in the rendering logic of agent message bubbles and timeline entries, ensuring cleaner code and better maintainability. - Updated test cases for `splitAgentMessageIntoBubbles` and `formatTimelineEntry` to reflect formatting changes and ensure accuracy. These changes improve code clarity and maintainability while enhancing the overall user experience in conversation threads. * fix: satisfy pre-push lint on fix/tauri * fix(chat): refresh usage counters after responses * refactor(ChatRuntimeProvider): remove redundant import of requestUsageRefresh - Eliminated the duplicate import statement for `requestUsageRefresh` in `ChatRuntimeProvider.tsx`, streamlining the code for better readability and maintainability. * fix(chat): satisfy pre-push checks * refactor(conversations): improve error handling and remove unused title generation logic - Removed the unused `generateThreadTitleIfNeeded` function call from the `Conversations` component, simplifying the message dispatch logic. - Enhanced error handling during message dispatch by using `unwrap()` to catch and log errors, providing clearer feedback on send failures. - Updated the `ChatRuntimeProvider` to ensure proper error logging when generating thread titles, improving observability of issues related to title generation. These changes streamline the conversation handling process and improve the robustness of error management in the chat system. * refactor(conversations): improve formatting of title redaction and streamline test assertions - Reformatted the `redact_title_for_log` function for better readability by adjusting the formatting of the output string. - Simplified the assertion in the timezone test to enhance clarity and maintainability. These changes contribute to cleaner code and improved test structure in the conversations module. * refactor(tokenjuice): sort fact parts for improved formatting in inline summary - Modified the `format_inline` function to sort the fact parts before generating the summary string. This change enhances the readability and consistency of the output by ensuring that facts are presented in a stable order. These changes contribute to better formatted summaries in the token juice module. * fix: address remaining CodeRabbit review comments * refactor: streamline error handling and improve code readability - Updated error handling in prompt loading to use `std::io::Error::other` for better clarity. - Simplified conditional checks using `is_none_or` and `is_some_and` for improved readability. - Refactored string trimming logic to utilize array syntax for better clarity. - Enhanced default implementations for several structs to reduce boilerplate code. These changes contribute to cleaner code and improved maintainability across various modules. * refactor: improve code formatting and structure - Adjusted formatting in `post_process.rs` for better readability by aligning the conditional block. - Combined derive attributes in `tools.rs` for the `ComputerControlConfig` struct to reduce redundancy. - Streamlined entry retrieval in `compatible.rs` by condensing multiple lines into a single line for clarity. These changes enhance code readability and maintainability across the affected modules.
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Agent / Subagent / Tool Flow
This document explains the current runtime flow around the agent harness, with emphasis on:
- how the main agent turn executes
- how tools are exposed and executed
- how
spawn_subagentworks - how typed vs fork subagents differ
- where to look when debugging harness and delegation issues
Scope: current Rust implementation under src/openhuman/agent/ and src/openhuman/tools/.
Why This Exists
The code path is split across several layers:
- built-in agent definitions in
src/openhuman/agent/agents/ - harness data + task-local plumbing in
src/openhuman/agent/harness/ - main session lifecycle in
src/openhuman/agent/harness/session/ - delegation tools in
src/openhuman/tools/impl/agent/ - synthesised
delegate_*tools insrc/openhuman/tools/orchestrator_tools.rs
If you only read one file, the system looks simpler than it is. The actual runtime path crosses all of them.
File Map
Registry and definitions
src/openhuman/agent/agents/loader.rsLoads built-in agents fromagent.tomlplus dynamicprompt.rsbuilders.src/openhuman/agent/harness/definition.rsDefinesAgentDefinition,ToolScope,SubagentEntry,PromptSource, and registry-facing data.src/openhuman/agent/harness/mod.rsRe-exports the harness entrypoints.
Main agent session
src/openhuman/agent/harness/session/builder.rsBuilds anAgent, chooses dispatcher, applies visible-tool filtering, synthesises delegation tools.src/openhuman/agent/harness/session/turn.rsMain turn lifecycle, tool execution, parent/fork context setup, transcript persistence, post-turn hooks.
Subagent path
src/openhuman/tools/impl/agent/spawn_subagent.rsRuntime tool entrypoint for explicit subagent spawns.src/openhuman/agent/harness/fork_context.rsTask-local parent and fork context.src/openhuman/agent/harness/subagent_runner.rsTyped/fork subagent execution, inner loop, tool filtering, transcript writes, large-result handoff.
Generic tool loop / bus path
src/openhuman/agent/harness/tool_loop.rsShared LLM -> tool -> tool result -> LLM loop used by the bus handler and legacy call sites.src/openhuman/agent/bus.rsNative event-bus entrypointagent.run_turn.
High-Level Model
There are two related but distinct execution tiers:
-
Agent::turnThis is the stateful session runtime. It owns conversation history, system prompt reuse, memory loading, hooks, transcript resume, and the parent context needed for subagents. -
run_subagentThis is an isolated delegated run. It does not become a nested fullAgentsession. It runs a smaller inner loop and returns a single compact text result to the parent as a normal tool result.
That distinction matters when debugging. A subagent is not a second copy of the full session runtime.
Flow Diagram
Full parent -> tool -> subagent flow
User message
|
v
+---------------------------+
| Agent::turn |
| session/turn.rs |
+---------------------------+
|
| 1. resume transcript if present
| 2. build/reuse system prompt
| 3. load memory context
| 4. install ParentExecutionContext task-local
v
+---------------------------+
| Parent iteration loop |
| provider call |
+---------------------------+
|
| provider response
v
+---------------------------+
| Parse tool calls |
| dispatcher + parser |
+---------------------------+
|
+-------------------------------+
| no tool calls |
| |
v |
+---------------------------+ |
| Final assistant text | |
| appended to parent history| |
+---------------------------+ |
| |
v |
Return to caller |
|
| has tool calls
v
+---------------------------+
| Execute tool calls |
| parent tool runtime |
+---------------------------+
|
+-------------------+-------------------+
| |
| regular tool | spawn_subagent
v v
+---------------------------+ +---------------------------+
| Tool::execute(...) | | SpawnSubagentTool |
+---------------------------+ | impl/agent/ |
| | spawn_subagent.rs |
| result +---------------------------+
v |
+---------------------------+ | validate args
| append tool result | | lookup AgentDefinition
| to parent history | | publish spawn event
+---------------------------+ v
| +---------------------------+
+-------------------------->| run_subagent(...) |
| subagent_runner.rs |
+---------------------------+
|
+-------------------------+-------------------------+
| |
| typed mode | fork mode
v v
+---------------------------+ +---------------------------+
| run_typed_mode | | run_fork_mode |
| - resolve model | | - require ForkContext |
| - filter tools | | - replay parent prefix |
| - build narrow prompt | | - reuse parent tool specs |
+---------------------------+ +---------------------------+
| |
+-------------------------+-------------------------+
|
v
+---------------------------+
| run_inner_loop |
| subagent private loop |
+---------------------------+
|
+---------------------------+---------------------------+
| |
| no tool calls | tool calls
v v
+---------------------------+ +---------------------------+
| final child text | | child executes allowed |
| returned to parent tool | | tools, appends results, |
+---------------------------+ | loops again |
+---------------------------+
|
v
+---------------------------+
| SpawnSubagentTool returns |
| ToolResult(output) |
+---------------------------+
|
v
+---------------------------+
| parent appends tool |
| result to history |
+---------------------------+
|
v
+---------------------------+
| next parent iteration |
| synthesizes final answer |
+---------------------------+
Context wiring for subagents
Agent::turn
|
+--> build ParentExecutionContext
| - provider
| - all_tools / all_tool_specs
| - model / temperature
| - memory / memory_context
| - connected_integrations
| - composio_client
| - tool_call_format
| - session lineage
|
+--> with_parent_context(...)
|
+--> any tool call inside this turn can read current_parent()
|
+--> SpawnSubagentTool
|
+--> run_subagent(...)
|
+--> typed mode uses ParentExecutionContext directly
|
+--> fork mode also requires current_fork()
|
+--> exact parent prompt + prefix replay
Startup and Registry Loading
Built-in agents live under src/openhuman/agent/agents/*/ as:
agent.tomlprompt.rs- optional
prompt.mdkept as nearby reference material
loader.rs parses each agent.toml, stamps the source as builtin, and installs the prompt.rs builder as PromptSource::Dynamic.
The global AgentDefinitionRegistry is initialized at startup. spawn_subagent depends on it. If the registry is missing, the tool returns a clear error instead of trying to run.
Important consequence: agent delegation is data-driven. The runtime does not hardcode an enum of built-in agents.
How a Main Agent Session Is Built
AgentBuilder::build in session/builder.rs assembles:
- provider
- full tool registry
- visible tool specs
- memory backend
- prompt builder
- dispatcher
- context manager
Two tool sets exist at build time:
- full tool registry: what the runtime can execute
- visible tool set: what the model can see in its schema/prompt
That split is intentional. The parent may have access to more runtime tools than it exposes directly to the model.
Synthesised delegation tools
For agents with subagents = [...] in their definition, the builder synthesises delegate_* tools using collect_orchestrator_tools():
SubagentEntry::AgentId("researcher")becomes anArchetypeDelegationToolSubagentEntry::Skills({ skills = "*" })expands to oneSkillDelegationToolper connected integration
These tools are added to the model-visible surface at build time. They are wrappers around delegation, not standalone business logic.
Main Turn Flow
Agent::turn in session/turn.rs is the main harness path.
1. Transcript resume and prompt bootstrap
On a fresh session:
- it tries to resume a previous transcript for KV-cache reuse
- fetches connected integrations
- fetches learned context
- builds the system prompt once
- stores that system prompt as the first message
On later turns it deliberately does not rebuild the system prompt. Byte stability is treated as a runtime invariant for backend prefix caching.
2. Memory context injection
Per turn, it asks the memory loader for relevant context and prepends that context to the user message. This is parent-session behavior. Subagents do not run the same memory lookup path.
3. Parent execution context is captured
Before the loop starts, Agent::turn snapshots a ParentExecutionContext and installs it on the task-local via with_parent_context(...).
That context carries the data subagents need:
- provider
- all tools and tool specs
- model / temperature
- memory handle
- loaded memory context
- connected integrations
- composio client
- tool call format
- session / transcript lineage
Without this task-local, spawn_subagent cannot work.
4. Iterative provider loop
For each iteration:
- context reduction runs first
- the dispatcher converts history into provider messages
- the provider is called
- response text and tool calls are parsed
- tool calls are executed
- tool results are appended to history
- the loop repeats until no tool calls remain
This is the full parent loop. It also emits progress events and drives post-turn hooks.
Tool Execution in the Parent Loop
The parent loop special-cases delegation but otherwise treats tools generically.
Core behaviors:
- unknown or filtered-out tools become structured error results
CliRpcOnlytools are blocked in the autonomous loop- approval-gated tools can be denied before execution
- successful outputs may be scrubbed / compacted / summarized
The parent’s history preserves:
- assistant tool call intent
- tool results
- final assistant response
That history format is what the next iteration reasons from.
Where spawn_subagent Enters
The explicit delegation tool lives in src/openhuman/tools/impl/agent/spawn_subagent.rs.
Its flow is:
- parse
agent_id,prompt, optionalcontext, optionaltoolkit, optionalmode - require the global
AgentDefinitionRegistry - resolve the target definition
- run pre-flight validation for
integrations_agent - publish
DomainEvent::SubagentSpawned - call
run_subagent(...) - publish completed or failed event
- return the subagent’s final text as a normal
ToolResult
Important: the parent model never sees the subagent’s internal transcript. It only sees the final tool result string returned by spawn_subagent.
Typed vs Fork Subagents
run_subagent chooses one of two modes.
Typed mode
Default path. Implemented by run_typed_mode(...).
Behavior:
- resolves model from the definition
- filters the parent’s tools down to what the child is allowed to use
- builds a fresh narrow system prompt
- optionally injects inherited memory context
- runs an isolated inner tool loop
This is the normal specialist-agent path.
Fork mode
Optimization path. Implemented by run_fork_mode(...).
Behavior:
- requires a
ForkContexttask-local - replays the parent’s exact rendered prompt and exact message prefix
- reuses the parent’s tool schema snapshot
- appends only the new fork task prompt
- runs the same inner loop
This is for prefix-cache reuse, not for stricter isolation. It is deliberately byte-stable and closely coupled to the parent request shape.
How Tool Filtering Works for Subagents
Typed subagents do not get a cloned tool registry. Instead the runner filters the parent’s tool list by index.
Filtering inputs:
definition.toolsdefinition.disallowed_toolsdefinition.skill_filterSubagentRunOptions.skill_filter_overridedefinition.extra_tools
Additional runtime rules:
- non-
welcomesubagents losecomplete_onboarding tools_agentstrips Composio skill toolsintegrations_agentwith a bound toolkit may inject dynamic per-action Composio tools
The allowed tool names become both:
- the execution allowlist
- the prompt-visible tool catalog
If the model emits a tool call outside that allowlist, the runner feeds back an error result and continues.
Prompt Construction for Typed Subagents
Typed mode creates a PromptContext and then does one of:
PromptSource::Dynamic: call the Rust prompt builder directlyPromptSource::InlineorPromptSource::File: load raw body, then wrap it withrender_subagent_system_prompt(...)
Definition flags control which standard sections are omitted:
omit_identityomit_memory_contextomit_safety_preambleomit_skills_catalogomit_profileomit_memory_md
This is one of the main token-saving levers in the harness.
The Subagent Inner Loop
The actual delegated execution happens in run_inner_loop(...).
It is a slimmed-down tool loop:
- call provider
- parse tool calls
- persist transcript after provider response
- execute tools
- append results
- persist transcript again
- stop on final text or max iterations
It returns:
- final output text
- iteration count
- aggregated usage
Unlike the parent Agent::turn, it does not own the broader session lifecycle.
Integrations Agent Special Cases
integrations_agent is the trickiest subagent path.
Toolkit gate in spawn_subagent
If agent_id == "integrations_agent":
toolkitis mandatory- the toolkit must exist in the allowlist
- if it exists but is not connected, the tool returns a success message explaining that authorization is required
This is intentionally not always treated as a hard tool failure, because disconnected integrations are a user-facing state, not necessarily a runtime error.
Text-mode override
In run_inner_loop, integrations_agent with tool specs forces text mode instead of native tool calling.
Why:
- large Composio JSON schemas can blow provider grammar/context limits
What changes:
- tool specs are omitted from the API payload
- XML-style tool instructions are injected into the system prompt
- the runner parses
<tool_call>...</tool_call>blocks out of plain text - tool results in text mode are fed back as a user message containing
<tool_result>tags
If a delegated integration run looks different from native-tool runs, this is usually why.
Large result handoff cache
For toolkit-scoped integrations_agent runs, oversized tool results may be replaced by placeholders and stashed in an in-memory ResultHandoffCache.
The child can then call extract_from_result(result_id, query) to ask targeted follow-up questions against the cached payload.
This is not the same as generic payload summarization. It is a progressive-disclosure path specific to oversized delegated tool outputs.
Parent -> Subagent -> Parent Result Shape
Conceptually the data flow is:
- parent model emits
spawn_subagent(...) - tool runtime executes the delegated subagent loop
- subagent finishes with one final text output
spawn_subagentreturns that text as its tool result- parent history receives the tool result
- parent model gets another iteration and synthesizes the user-facing answer
The parent does not absorb the child’s internal reasoning trace or full message history. Only the compact final output crosses the boundary.
Bus Path vs Session Path
There are two outer entrypoints to keep straight.
Agent::turn
Used for full stateful sessions. This is the richer harness.
agent.run_turn via src/openhuman/agent/bus.rs
This native event-bus handler calls run_tool_call_loop(...) directly using owned Rust payloads.
It supports:
- provider reuse
- tool filtering
- per-turn extra tools
- progress streaming
But it does not create a full Agent session object. If you are debugging channel-dispatch behavior, this distinction matters.
Debugging Checklist
1. Confirm which execution tier you are in
Ask first:
- full
Agent::turnsession? - bus
agent.run_turnpath? - explicit
spawn_subagenttool? - synthesised
delegate_*tool leading intospawn_subagent?
If you confuse these, logs will look contradictory.
2. Check registry state
If delegation fails very early, confirm:
AgentDefinitionRegistry::init_global(...)ran at startup- the target agent id exists
- workspace overrides did not shadow the expected built-in definition
3. Check task-local availability
If run_subagent errors with missing context:
NoParentContextmeans the tool ran outside a parent turnNoForkContextmeans fork mode was requested but the fork snapshot was never installed
These are wiring issues, not prompt issues.
4. Check tool visibility vs tool execution
A tool can exist in the parent registry but still be invisible to a child due to:
- named
ToolScope disallowed_toolsskill_filter- welcome-only stripping
- toolkit narrowing
If the model says “Unknown tool” or “not available to this sub-agent”, inspect filtering first.
5. Check transcript artifacts
Subagents persist transcripts per iteration using the parent session lineage plus a child session key. This is useful for debugging partial runs and crashes during tool execution.
Parent sessions and subagents do not write identical transcript shapes, so compare like with like.
6. Check the provider mode
If tool calling is malformed, verify whether the run used:
- native tools
- p-format / xml instructions
- integrations-agent text mode
The parser and message shape differ.
Useful Log Prefixes
These prefixes are the most useful grep anchors:
[agent_loop][agent][tool-loop][spawn_subagent][subagent_runner][subagent_runner:typed][subagent_runner:fork][subagent_runner:text-mode][subagent_runner:handoff][orchestrator_tools][agent::bus][transcript]
Best Existing Tests to Read First
For end-to-end harness behavior:
src/openhuman/agent/harness/session/tests.rsturn_dispatches_spawn_subagent_through_full_pathturn_dispatches_spawn_subagent_in_fork_mode
For runner behavior in isolation:
src/openhuman/agent/harness/subagent_runner.rstests- typed mode returns text
- memory-context inclusion/omission
- tool filtering
- one-tool execution
- blocked tool recovery
- fork prefix replay
- missing parent/fork context errors
For orchestration-tool synthesis:
src/openhuman/tools/orchestrator_tools.rstests
For generic parent loop behavior:
src/openhuman/agent/tests.rs
Common Failure Modes
Subagent never starts
Usually one of:
- registry not initialized
- invalid
agent_id - missing parent context
- missing fork context
Subagent starts but cannot call expected tools
Usually one of:
- tool filtered out by definition scope
skill_filteror toolkit override narrowed too aggressively- tool is
CliRpcOnly - dynamic integration tools were not injected because the toolkit/client state was missing
Integrations agent behaves unlike other agents
Usually expected. It may be in text mode and may be using the oversized-result handoff cache.
Parent seems to “lose” child reasoning
Expected. Only the child’s final output is returned to the parent. Internal child history stays isolated.
Practical Mental Model
The safest mental model is:
- the parent session is the durable conversation runtime
- tools are the execution boundary
- subagents are tool implementations that happen to run their own mini LLM loop
- fork mode is a cache-optimization path, not a different product feature
integrations_agentis a special delegated runtime with extra provider and payload safeguards
If you debug from that model, the current codebase makes much more sense.