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Adds role='leaf'|'orchestrator' to delegate_task. With max_spawn_depth>=2, an orchestrator child retains the 'delegation' toolset and can spawn its own workers; leaf children cannot delegate further (identical to today). Default posture is flat — max_spawn_depth=1 means a depth-0 parent's children land at the depth-1 floor and orchestrator role silently degrades to leaf. Users opt into nested delegation by raising max_spawn_depth to 2 or 3 in config.yaml. Also threads acp_command/acp_args through the main agent loop's delegate dispatch (previously silently dropped in the schema) via a new _dispatch_delegate_task helper, and adds a DelegateEvent enum with legacy-string back-compat for gateway/ACP/CLI progress consumers. Config (hermes_cli/config.py defaults): delegation.max_concurrent_children: 3 # floor-only, no upper cap delegation.max_spawn_depth: 1 # 1=flat (default), 2-3 unlock nested delegation.orchestrator_enabled: true # global kill switch Salvaged from @pefontana's PR #11215. Overrides vs. the original PR: concurrency stays at 3 (PR bumped to 5 + cap 8 — we keep the floor only, no hard ceiling); max_spawn_depth defaults to 1 (PR defaulted to 2 which silently enabled one level of orchestration for every user). Co-authored-by: pefontana <fontana.pedro93@gmail.com>
240 lines
10 KiB
Markdown
240 lines
10 KiB
Markdown
---
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sidebar_position: 7
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title: "Subagent Delegation"
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description: "Spawn isolated child agents for parallel workstreams with delegate_task"
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---
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# Subagent Delegation
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The `delegate_task` tool spawns child AIAgent instances with isolated context, restricted toolsets, and their own terminal sessions. Each child gets a fresh conversation and works independently — only its final summary enters the parent's context.
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## Single Task
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```python
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delegate_task(
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goal="Debug why tests fail",
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context="Error: assertion in test_foo.py line 42",
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toolsets=["terminal", "file"]
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)
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```
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## Parallel Batch
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Up to 3 concurrent subagents by default (configurable, no hard ceiling):
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```python
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delegate_task(tasks=[
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{"goal": "Research topic A", "toolsets": ["web"]},
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{"goal": "Research topic B", "toolsets": ["web"]},
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{"goal": "Fix the build", "toolsets": ["terminal", "file"]}
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])
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```
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## How Subagent Context Works
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:::warning Critical: Subagents Know Nothing
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Subagents start with a **completely fresh conversation**. They have zero knowledge of the parent's conversation history, prior tool calls, or anything discussed before delegation. The subagent's only context comes from the `goal` and `context` fields you provide.
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:::
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This means you must pass **everything** the subagent needs:
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```python
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# BAD - subagent has no idea what "the error" is
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delegate_task(goal="Fix the error")
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# GOOD - subagent has all context it needs
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delegate_task(
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goal="Fix the TypeError in api/handlers.py",
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context="""The file api/handlers.py has a TypeError on line 47:
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'NoneType' object has no attribute 'get'.
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The function process_request() receives a dict from parse_body(),
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but parse_body() returns None when Content-Type is missing.
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The project is at /home/user/myproject and uses Python 3.11."""
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)
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```
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The subagent receives a focused system prompt built from your goal and context, instructing it to complete the task and provide a structured summary of what it did, what it found, any files modified, and any issues encountered.
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## Practical Examples
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### Parallel Research
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Research multiple topics simultaneously and collect summaries:
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```python
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delegate_task(tasks=[
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{
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"goal": "Research the current state of WebAssembly in 2025",
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"context": "Focus on: browser support, non-browser runtimes, language support",
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"toolsets": ["web"]
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},
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{
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"goal": "Research the current state of RISC-V adoption in 2025",
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"context": "Focus on: server chips, embedded systems, software ecosystem",
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"toolsets": ["web"]
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},
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{
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"goal": "Research quantum computing progress in 2025",
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"context": "Focus on: error correction breakthroughs, practical applications, key players",
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"toolsets": ["web"]
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}
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])
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```
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### Code Review + Fix
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Delegate a review-and-fix workflow to a fresh context:
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```python
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delegate_task(
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goal="Review the authentication module for security issues and fix any found",
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context="""Project at /home/user/webapp.
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Auth module files: src/auth/login.py, src/auth/jwt.py, src/auth/middleware.py.
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The project uses Flask, PyJWT, and bcrypt.
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Focus on: SQL injection, JWT validation, password handling, session management.
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Fix any issues found and run the test suite (pytest tests/auth/).""",
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toolsets=["terminal", "file"]
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)
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```
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### Multi-File Refactoring
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Delegate a large refactoring task that would flood the parent's context:
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```python
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delegate_task(
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goal="Refactor all Python files in src/ to replace print() with proper logging",
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context="""Project at /home/user/myproject.
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Use the 'logging' module with logger = logging.getLogger(__name__).
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Replace print() calls with appropriate log levels:
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- print(f"Error: ...") -> logger.error(...)
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- print(f"Warning: ...") -> logger.warning(...)
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- print(f"Debug: ...") -> logger.debug(...)
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- Other prints -> logger.info(...)
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Don't change print() in test files or CLI output.
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Run pytest after to verify nothing broke.""",
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toolsets=["terminal", "file"]
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)
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```
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## Batch Mode Details
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When you provide a `tasks` array, subagents run in **parallel** using a thread pool:
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- **Maximum concurrency:** 5 tasks by default (configurable via `delegation.max_concurrent_children`, absolute cap of 8)
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- **Thread pool:** Uses `ThreadPoolExecutor` with the configured concurrency limit as max workers
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- **Progress display:** In CLI mode, a tree-view shows tool calls from each subagent in real-time with per-task completion lines. In gateway mode, progress is batched and relayed to the parent's progress callback
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- **Result ordering:** Results are sorted by task index to match input order regardless of completion order
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- **Interrupt propagation:** Interrupting the parent (e.g., sending a new message) interrupts all active children
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Single-task delegation runs directly without thread pool overhead.
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## Model Override
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You can configure a different model for subagents via `config.yaml` — useful for delegating simple tasks to cheaper/faster models:
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```yaml
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# In ~/.hermes/config.yaml
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delegation:
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model: "google/gemini-flash-2.0" # Cheaper model for subagents
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provider: "openrouter" # Optional: route subagents to a different provider
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```
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If omitted, subagents use the same model as the parent.
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## Toolset Selection Tips
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The `toolsets` parameter controls what tools the subagent has access to. Choose based on the task:
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| Toolset Pattern | Use Case |
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|----------------|----------|
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| `["terminal", "file"]` | Code work, debugging, file editing, builds |
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| `["web"]` | Research, fact-checking, documentation lookup |
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| `["terminal", "file", "web"]` | Full-stack tasks (default) |
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| `["file"]` | Read-only analysis, code review without execution |
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| `["terminal"]` | System administration, process management |
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Certain toolsets are blocked for subagents regardless of what you specify:
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- `delegation` — blocked for leaf subagents (the default). Retained for `role="orchestrator"` children, bounded by `max_spawn_depth` — see [Depth Limit and Nested Orchestration](#depth-limit-and-nested-orchestration) below.
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- `clarify` — subagents cannot interact with the user
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- `memory` — no writes to shared persistent memory
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- `code_execution` — children should reason step-by-step
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- `send_message` — no cross-platform side effects (e.g., sending Telegram messages)
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## Max Iterations
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Each subagent has an iteration limit (default: 50) that controls how many tool-calling turns it can take:
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```python
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delegate_task(
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goal="Quick file check",
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context="Check if /etc/nginx/nginx.conf exists and print its first 10 lines",
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max_iterations=10 # Simple task, don't need many turns
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)
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```
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## Depth Limit and Nested Orchestration
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By default, delegation is **flat**: a parent (depth 0) spawns children (depth 1), and those children cannot delegate further. This prevents runaway recursive delegation.
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For multi-stage workflows (research → synthesis, or parallel orchestration over sub-problems), a parent can spawn **orchestrator** children that *can* delegate their own workers:
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```python
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delegate_task(
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goal="Survey three code review approaches and recommend one",
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role="orchestrator", # Allows this child to spawn its own workers
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context="...",
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)
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```
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- `role="leaf"` (default): child cannot delegate further — identical to the flat-delegation behavior.
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- `role="orchestrator"`: child retains the `delegation` toolset. Gated by `delegation.max_spawn_depth` (default **1** = flat, so `role="orchestrator"` is a no-op at defaults). Raise `max_spawn_depth` to 2 to allow orchestrator children to spawn leaf grandchildren; 3 for three levels (cap).
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- `delegation.orchestrator_enabled: false`: global kill switch that forces every child to `leaf` regardless of the `role` parameter.
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**Cost warning:** With `max_spawn_depth: 3` and `max_concurrent_children: 3`, the tree can reach 3×3×3 = 27 concurrent leaf agents. Each extra level multiplies spend — raise `max_spawn_depth` intentionally.
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## Key Properties
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- Each subagent gets its **own terminal session** (separate from the parent)
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- **Nested delegation is opt-in** — only `role="orchestrator"` children can delegate further, and only when `max_spawn_depth` is raised from its default of 1 (flat). Disable globally with `orchestrator_enabled: false`.
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- Leaf subagents **cannot** call: `delegate_task`, `clarify`, `memory`, `send_message`, `execute_code`. Orchestrator subagents retain `delegate_task` but still cannot use the other four.
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- **Interrupt propagation** — interrupting the parent interrupts all active children (including grandchildren under orchestrators)
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- Only the final summary enters the parent's context, keeping token usage efficient
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- Subagents inherit the parent's **API key, provider configuration, and credential pool** (enabling key rotation on rate limits)
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## Delegation vs execute_code
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| Factor | delegate_task | execute_code |
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|--------|--------------|-------------|
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| **Reasoning** | Full LLM reasoning loop | Just Python code execution |
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| **Context** | Fresh isolated conversation | No conversation, just script |
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| **Tool access** | All non-blocked tools with reasoning | 7 tools via RPC, no reasoning |
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| **Parallelism** | 3 concurrent subagents by default (configurable) | Single script |
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| **Best for** | Complex tasks needing judgment | Mechanical multi-step pipelines |
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| **Token cost** | Higher (full LLM loop) | Lower (only stdout returned) |
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| **User interaction** | None (subagents can't clarify) | None |
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**Rule of thumb:** Use `delegate_task` when the subtask requires reasoning, judgment, or multi-step problem solving. Use `execute_code` when you need mechanical data processing or scripted workflows.
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## Configuration
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```yaml
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# In ~/.hermes/config.yaml
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delegation:
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max_iterations: 50 # Max turns per child (default: 50)
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# max_concurrent_children: 3 # Parallel children per batch (default: 3)
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# max_spawn_depth: 1 # Tree depth (1-3, default 1 = flat). Raise to 2 to allow orchestrator children to spawn leaves; 3 for three levels.
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# orchestrator_enabled: true # Disable to force all children to leaf role.
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model: "google/gemini-3-flash-preview" # Optional provider/model override
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provider: "openrouter" # Optional built-in provider
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# Or use a direct custom endpoint instead of provider:
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delegation:
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model: "qwen2.5-coder"
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base_url: "http://localhost:1234/v1"
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api_key: "local-key"
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```
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:::tip
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The agent handles delegation automatically based on the task complexity. You don't need to explicitly ask it to delegate — it will do so when it makes sense.
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:::
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