v3: Subagent Mechanism

~450 lines. +1 tool. Divide and conquer.

v2 adds planning. But for large tasks like "explore the codebase then refactor auth", a single agent hits context limits. Exploration dumps 20 files into history. Refactoring loses focus.

v3 adds the Task tool: spawn child agents with isolated context.

The Problem

Single-agent context pollution:

Main Agent History:
  [exploring...] cat file1.py -> 500 lines
  [exploring...] cat file2.py -> 300 lines
  ... 15 more files ...
  [now refactoring...] "wait, what did file1 contain?"

The solution: delegate exploration to a subagent:

Main Agent History:
  [Task: explore codebase]
    -> Subagent explores 20 files
    -> Returns: "Auth in src/auth/, DB in src/models/"
  [now refactoring with clean context]

Agent Type Registry

Each agent type defines capabilities:

AGENT_TYPES = {
    "explore": {
        "description": "Read-only for searching and analyzing",
        "tools": ["bash", "read_file"],  # No write
        "prompt": "Search and analyze. Never modify. Return concise summary."
    },
    "code": {
        "description": "Full agent for implementation",
        "tools": "*",  # All tools
        "prompt": "Implement changes efficiently."
    },
    "plan": {
        "description": "Planning and analysis",
        "tools": ["bash", "read_file"],  # Read-only
        "prompt": "Analyze and output numbered plan. Don't change files."
    }
}

The Task Tool

{
    "name": "Task",
    "description": "Spawn a subagent for focused subtask",
    "input_schema": {
        "description": "Short task name (3-5 words)",
        "prompt": "Detailed instructions",
        "agent_type": "explore | code | plan"
    }
}

Main agent calls Task → child agent runs → returns summary.

Subagent Execution

The heart of Task tool:

def run_task(description, prompt, agent_type):
    config = AGENT_TYPES[agent_type]

    # 1. Agent-specific system prompt
    sub_system = f"You are a {agent_type} subagent.\n{config['prompt']}"

    # 2. Filtered tools
    sub_tools = get_tools_for_agent(agent_type)

    # 3. Isolated history (KEY: no parent context)
    sub_messages = [{"role": "user", "content": prompt}]

    # 4. Same query loop
    while True:
        response = client.messages.create(
            model=MODEL, system=sub_system,
            messages=sub_messages, tools=sub_tools
        )
        if response.stop_reason != "tool_use":
            break
        # Execute tools, append results...

    # 5. Return only final text
    return extract_final_text(response)

Key concepts:

Concept	Implementation
Context isolation	Fresh sub_messages = []
Tool filtering	get_tools_for_agent()
Specialized behavior	Agent-specific system prompt
Result abstraction	Only final text returned

Tool Filtering

def get_tools_for_agent(agent_type):
    allowed = AGENT_TYPES[agent_type]["tools"]
    if allowed == "*":
        return BASE_TOOLS  # No Task (no recursion in demo)
    return [t for t in BASE_TOOLS if t["name"] in allowed]

• explore: bash + read_file only
• code: all tools
• plan: bash + read_file only

Subagents don't get Task tool (prevents infinite recursion in this demo).

Progress Display

Subagent output doesn't pollute main chat:

You: explore the codebase
> Task: explore codebase
  [explore] explore codebase ... 5 tools, 3.2s
  [explore] explore codebase - done (8 tools, 5.1s)

Here's what I found: ...

Real-time progress, clean final output.

Typical Flow

User: "Refactor auth to use JWT"

Main Agent:
  1. Task(explore): "Find all auth-related files"
     -> Subagent reads 10 files
     -> Returns: "Auth in src/auth/login.py, session in..."

  2. Task(plan): "Design JWT migration"
     -> Subagent analyzes structure
     -> Returns: "1. Add jwt lib 2. Create token utils..."

  3. Task(code): "Implement JWT tokens"
     -> Subagent writes code
     -> Returns: "Created jwt_utils.py, updated login.py"

  4. Summarize changes

Each subagent has clean context. Main agent stays focused.

Comparison

Aspect	v2	v3
Context	Single, growing	Isolated per task
Exploration	Pollutes history	Contained in subagent
Parallelism	No	Possible (not in demo)
Code added	~300 lines	~450 lines

The Pattern

Complex Task
  └─ Main Agent (coordinator)
       ├─ Subagent A (explore) -> summary
       ├─ Subagent B (plan) -> plan
       └─ Subagent C (code) -> result

Same agent loop, different contexts. That's the whole trick.

---

Divide and conquer. Context isolation.

← v2 | Back to README | v0 →