Files
hermes-agent/website/docs/user-guide/features/delegation.md
teknium1 d50e9bcef7 docs: add 11 new pages + expand 4 existing pages (26 → 37 total)
New pages (sourced from actual codebase):
- Security: command approval, DM pairing, container isolation, production checklist
- Session Management: resume, export, prune, search, per-platform tracking
- Context Files: AGENTS.md project context, discovery, size limits, security
- Personality: SOUL.md, 14 built-in personalities, custom definitions
- Browser Automation: Browserbase setup, 10 browser tools, stealth mode
- Image Generation: FLUX 2 Pro via FAL, aspect ratios, auto-upscaling
- Provider Routing: OpenRouter sort/only/ignore/order config
- Honcho: AI-native memory integration, setup, peer config
- Home Assistant: HASS setup, 4 HA tools, WebSocket gateway
- Batch Processing: trajectory generation, dataset format, checkpointing
- RL Training: Atropos/Tinker integration, environments, workflow

Expanded pages:
- code-execution: 51 → 195 lines (examples, limits, security, comparison table)
- delegation: 60 → 216 lines (context tips, batch mode, model override)
- cron: 88 → 273 lines (real-world examples, delivery options, expression cheat sheet)
- memory: 98 → 249 lines (best practices, capacity management, examples)
2026-03-05 07:28:41 -08:00

217 lines
8.2 KiB
Markdown

---
sidebar_position: 7
title: "Subagent Delegation"
description: "Spawn isolated child agents for parallel workstreams with delegate_task"
---
# Subagent Delegation
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.
## Single Task
```python
delegate_task(
goal="Debug why tests fail",
context="Error: assertion in test_foo.py line 42",
toolsets=["terminal", "file"]
)
```
## Parallel Batch
Up to 3 concurrent subagents:
```python
delegate_task(tasks=[
{"goal": "Research topic A", "toolsets": ["web"]},
{"goal": "Research topic B", "toolsets": ["web"]},
{"goal": "Fix the build", "toolsets": ["terminal", "file"]}
])
```
## How Subagent Context Works
:::warning Critical: Subagents Know Nothing
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.
:::
This means you must pass **everything** the subagent needs:
```python
# BAD - subagent has no idea what "the error" is
delegate_task(goal="Fix the error")
# GOOD - subagent has all context it needs
delegate_task(
goal="Fix the TypeError in api/handlers.py",
context="""The file api/handlers.py has a TypeError on line 47:
'NoneType' object has no attribute 'get'.
The function process_request() receives a dict from parse_body(),
but parse_body() returns None when Content-Type is missing.
The project is at /home/user/myproject and uses Python 3.11."""
)
```
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.
## Practical Examples
### Parallel Research
Research multiple topics simultaneously and collect summaries:
```python
delegate_task(tasks=[
{
"goal": "Research the current state of WebAssembly in 2025",
"context": "Focus on: browser support, non-browser runtimes, language support",
"toolsets": ["web"]
},
{
"goal": "Research the current state of RISC-V adoption in 2025",
"context": "Focus on: server chips, embedded systems, software ecosystem",
"toolsets": ["web"]
},
{
"goal": "Research quantum computing progress in 2025",
"context": "Focus on: error correction breakthroughs, practical applications, key players",
"toolsets": ["web"]
}
])
```
### Code Review + Fix
Delegate a review-and-fix workflow to a fresh context:
```python
delegate_task(
goal="Review the authentication module for security issues and fix any found",
context="""Project at /home/user/webapp.
Auth module files: src/auth/login.py, src/auth/jwt.py, src/auth/middleware.py.
The project uses Flask, PyJWT, and bcrypt.
Focus on: SQL injection, JWT validation, password handling, session management.
Fix any issues found and run the test suite (pytest tests/auth/).""",
toolsets=["terminal", "file"]
)
```
### Multi-File Refactoring
Delegate a large refactoring task that would flood the parent's context:
```python
delegate_task(
goal="Refactor all Python files in src/ to replace print() with proper logging",
context="""Project at /home/user/myproject.
Use the 'logging' module with logger = logging.getLogger(__name__).
Replace print() calls with appropriate log levels:
- print(f"Error: ...") -> logger.error(...)
- print(f"Warning: ...") -> logger.warning(...)
- print(f"Debug: ...") -> logger.debug(...)
- Other prints -> logger.info(...)
Don't change print() in test files or CLI output.
Run pytest after to verify nothing broke.""",
toolsets=["terminal", "file"]
)
```
## Batch Mode Details
When you provide a `tasks` array, subagents run in **parallel** using a thread pool:
- **Maximum concurrency:** 3 tasks (the `tasks` array is truncated to 3 if longer)
- **Thread pool:** Uses `ThreadPoolExecutor` with `MAX_CONCURRENT_CHILDREN = 3` workers
- **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
- **Result ordering:** Results are sorted by task index to match input order regardless of completion order
- **Interrupt propagation:** Interrupting the parent (e.g., sending a new message) interrupts all active children
Single-task delegation runs directly without thread pool overhead.
## Model Override
You can use a different model for subagents — useful for delegating simple tasks to cheaper/faster models:
```python
delegate_task(
goal="Summarize this README file",
context="File at /project/README.md",
toolsets=["file"],
model="google/gemini-flash-2.0" # Cheaper model for simple tasks
)
```
If omitted, subagents use the same model as the parent.
## Toolset Selection Tips
The `toolsets` parameter controls what tools the subagent has access to. Choose based on the task:
| Toolset Pattern | Use Case |
|----------------|----------|
| `["terminal", "file"]` | Code work, debugging, file editing, builds |
| `["web"]` | Research, fact-checking, documentation lookup |
| `["terminal", "file", "web"]` | Full-stack tasks (default) |
| `["file"]` | Read-only analysis, code review without execution |
| `["terminal"]` | System administration, process management |
Certain toolsets are **always blocked** for subagents regardless of what you specify:
- `delegation` — no recursive delegation (prevents infinite spawning)
- `clarify` — subagents cannot interact with the user
- `memory` — no writes to shared persistent memory
- `code_execution` — children should reason step-by-step
- `send_message` — no cross-platform side effects (e.g., sending Telegram messages)
## Max Iterations
Each subagent has an iteration limit (default: 50) that controls how many tool-calling turns it can take:
```python
delegate_task(
goal="Quick file check",
context="Check if /etc/nginx/nginx.conf exists and print its first 10 lines",
max_iterations=10 # Simple task, don't need many turns
)
```
## Depth Limit
Delegation has a **depth limit of 2** — a parent (depth 0) can spawn children (depth 1), but children cannot delegate further. This prevents runaway recursive delegation chains.
## Key Properties
- Each subagent gets its **own terminal session** (separate from the parent)
- **No nested delegation** — children cannot delegate further (no grandchildren)
- Subagents **cannot** call: `delegate_task`, `clarify`, `memory`, `send_message`, `execute_code`
- **Interrupt propagation** — interrupting the parent interrupts all active children
- Only the final summary enters the parent's context, keeping token usage efficient
- Subagents inherit the parent's **API key and provider configuration**
## Delegation vs execute_code
| Factor | delegate_task | execute_code |
|--------|--------------|-------------|
| **Reasoning** | Full LLM reasoning loop | Just Python code execution |
| **Context** | Fresh isolated conversation | No conversation, just script |
| **Tool access** | All non-blocked tools with reasoning | 7 tools via RPC, no reasoning |
| **Parallelism** | Up to 3 concurrent subagents | Single script |
| **Best for** | Complex tasks needing judgment | Mechanical multi-step pipelines |
| **Token cost** | Higher (full LLM loop) | Lower (only stdout returned) |
| **User interaction** | None (subagents can't clarify) | None |
**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.
## Configuration
```yaml
# In ~/.hermes/config.yaml
delegation:
max_iterations: 50 # Max turns per child (default: 50)
default_toolsets: ["terminal", "file", "web"] # Default toolsets
```
:::tip
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.
:::