agent-lifecycle-management

# Agent Lifecycle Management Skill

Manage agent fleets through Create, Command, Monitor, and Delete operations.

## Purpose

Guide the implementation of CRUD operations for agent fleets, ensuring proper lifecycle management and resource cleanup.

## When to Use

- Setting up agent lifecycle patterns
- Implementing agent management tools
- Designing cleanup and resource management
- Building agent state tracking

## Prerequisites

- Understanding of orchestrator architecture (@single-interface-pattern.md)
- Familiarity with the Three Pillars (@three-pillars-orchestration.md)
- Access to Claude Agent SDK documentation

## SDK Requirement

> **Implementation Note**: Full lifecycle management requires Claude Agent SDK with custom MCP tools. This skill provides design patterns for SDK implementation.

## Lifecycle Pattern

```text
Create --> Command --> Monitor --> Aggregate --> Delete
|  |  |  |  |
   v          v           v            v           v
Template   Prompt      Status      Results     Cleanup
```

## CRUD Operations

### Create Operation

Spin up a new specialized agent.

**Parameters**:

- `template`: Pre-defined configuration to use
- `name`: Unique identifier for this agent
- `system_prompt`: Custom prompt (alternative to template)
- `model`: haiku, sonnet, or opus
- `allowed_tools`: Tools this agent can use

**Example**:

```python
create_agent(
    name="scout_1",
    template="scout-fast",
    # OR
    system_prompt="...",
    model="haiku",
    allowed_tools=["Read", "Glob", "Grep"]
)
```

**Best Practices**:

- Use templates for consistency
- Give descriptive names
- Select appropriate model
- Minimize tool access

### Command Operation

Send prompts to an agent.

**Parameters**:

- `agent_id`: Which agent to command
- `prompt`: The detailed instruction

**Example**:

```python
command_agent(
    agent_id="scout_1",
    prompt="""
    Analyze the authentication module in src/auth/.
    Focus on:
    1. Current implementation patterns
    2. Security