ShirokumaLibrary

managing-agents

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# Install this skill:
npx skills add ShirokumaLibrary/shirokuma-skills --skill "managing-agents"

Install specific skill from multi-skill repository

# Description

Create, update, and improve Claude Code agent files following Anthropic's official best practices. Use when user mentions "agent", "AGENT.md", "create agent", "update agent", "improve agent", "generate agent", "agent template", "workflow pattern", or wants help with agents. Triggers include "エージェント作成", "コードレビュー用のエージェントを作って", "エージェント改善".

# SKILL.md


name: managing-agents
description: Create, update, and improve Claude Code agent files following Anthropic's official best practices. Use when user mentions "agent", "AGENT.md", "create agent", "update agent", "improve agent", "generate agent", "agent template", "workflow pattern", or wants help with agents. Triggers include "エージェント作成", "コードレビュー用のエージェントを作って", "エージェント改善".
allowed-tools: Read, Write, Edit, Glob, Grep


Managing Claude Code Agents

Create, update, and improve Claude Code agent files following Anthropic's official best practices.

Core Principle: Start simple. "Success isn't about building the most sophisticated system—it's about building the right system for your needs." — Anthropic

When to Use

Automatically invoke when the user:
- Asks to "create an agent" or "make a new agent"
- Wants to "update an agent" or "improve an agent"
- Requests "agent template" or "agent example"
- Wants to "review an agent" or "check agent quality"

Agentic Systems: Workflows vs Agents

Understanding this distinction is critical for designing effective systems.

Type Control Use When
Workflows Predefined code paths orchestrate LLM calls Subtasks are predictable, need consistency
Agents LLM dynamically decides process & tool usage Open-ended problems, unpredictable steps

Decision Guide

Can you predict all steps?

Answer Use Characteristics
YES WORKFLOW Deterministic, reliable (Prompt Chaining, Routing, Parallelization)
NO AGENT Flexible, autonomous (Higher latency/cost, handles unknowns)

Start with workflows — they provide more control. Add agent autonomy only when results justify the added complexity.

See design-patterns.md for 5 workflow patterns + agent roles.

Quick Reference

Agent File Locations

Simple agent: .claude/agents/agent-name.md (single file)

Complex agent: .claude/agents/agent-name/ (directory)

File Required Purpose
AGENT.md Core prompt (<500 lines)
reference.md Detailed specs
examples.md Use cases
templates/ Reusable templates

Minimal Agent Template

---
name: agent-identifier
description: What it does. Use when [triggers].
tools: Read, Grep, Glob
model: sonnet
---

# Agent Name

Brief description.

## Core Responsibilities
- Task 1
- Task 2

## Workflow
1. **Step 1**: Action
2. **Step 2**: Action

## Output Format
[Expected output structure]

Required Fields

name

  • Lowercase with hyphens: code-reviewer, test-generator
  • Pattern: /^[a-z][a-z0-9-]*$/

description (Critical for Discovery)

Simple Format:

description: Reviews code for quality. Use when user asks "review PR" or "check code".

Rich Format with Examples (Recommended):

description: Use this agent when [task]. Examples:

<example>
Context: [Situation]
user: "[Message]"
assistant: "[Response before invoking]"
<Task tool call to agent-name agent>
</example>

See reference.md for complete examples.

Optional Fields

Field Values Default
tools Read, Write, Edit, Bash, Grep, Glob, WebFetch, Task All tools
model sonnet, opus, haiku, inherit sonnet
permissionMode default, acceptEdits, bypassPermissions default
skills Comma-separated skill names None

See reference.md for details.

Agent Design Principles

1. Simplicity First

Start with the simplest solution. Add complexity only when results justify it.

2. Single Responsibility

One clear, focused purpose per agent. Heavy agents (25k+ tokens) create bottlenecks; lightweight agents (<3k tokens) enable fluid orchestration.

3. Creator-Checker Pattern (Evaluator-Optimizer)

Type Role Rule Style
Creator Implementation "Do" rules only
Checker Review/Audit "Do" + "Don't" rules

Example: nextjs-vibe-coder (Creator) ←→ reviewer (Checker)

4. Minimal Tool Access (ACI)

Agent-Computer Interface — Design tools as carefully as prompts:

Agent Type Recommended Tools
Reviewer (read-only) Read, Grep, Glob, Bash
Generator Read, Write, Bash
Transformer Read, Edit, Bash

See best-practices.md for tool design guidelines.

5. Clear Invocation Triggers

Include phrases like:
- "Use PROACTIVELY when..."
- "Automatically invoke when..."

See design-patterns.md for workflow patterns + agent roles.

Common Agent Types

Creator Agents

Agent Purpose Tools
Coder/Builder Feature implementation Read, Write, Edit, Bash
Test Generator Test suite creation Read, Write, Bash
Doc Builder Documentation Read, Write, Glob

Checker Agents

Agent Purpose Tools
Code Reviewer Quality & security Read, Grep, Glob, Bash
Security Auditor Vulnerability detection Read, Grep, Glob, Bash
Debugger Root cause analysis Read, Bash, Grep, Glob

See examples.md for complete templates.

Workflow: Creating an Agent

  1. Understand Requirements: Task, triggers, tools needed
  2. Choose Format: Single file (<300 lines) or directory
  3. Write Frontmatter: name, description, tools, model
  4. Write System Prompt: Responsibilities, workflow, output format
  5. Create File: .claude/agents/[name].md
  6. Test: Try invocation phrases
  7. Review: Run claude-config-reviewer agent to validate

Quick Start:

# Simple agent
cat > .claude/agents/my-agent.md << 'EOF'
---
name: my-agent
description: Does X. Use when user asks for Y.
tools: Read, Grep, Glob
---

# My Agent

[System prompt...]
EOF

See reference.md for detailed workflow.

Workflow: Updating an Agent

  1. Read Current Agent: Load existing file
  2. Identify Issues: Vague instructions, missing workflow
  3. Apply Changes: Use Edit tool
  4. Verify: Check against quality checklist
  5. Review: Run claude-config-reviewer agent to validate

See reference.md for evaluation criteria.

Progressive Disclosure (Complex Agents)

For agents exceeding 300 lines, use directory structure:

File Purpose
AGENT.md Core prompt (<500 lines)
reference.md Detailed specs
examples.md Use cases
best-practices.md Advanced patterns
templates/ Reusable templates

Key Rules:
- AGENT.md under 500 lines
- References one level deep only
- Include table of contents in long files

See reference.md for complete specification.

Built-in Agents

Agent Model Tools Purpose
General-purpose sonnet All Complex multi-step tasks
Plan haiku Read-only Codebase research
Explore haiku Read-only Lightweight discovery

Resumable Agents

// Resume previous session
Task({
  resume: "previous-agent-id",
  prompt: "Continue from where we left off"
})

Common Mistakes

Mistake Fix
Too broad scope Focus on single responsibility
Vague instructions Add step-by-step workflow
Excessive tools Limit to necessary tools only
Poor description Include invocation triggers

Storage Locations

Priority Location Use Case
Highest .claude/agents/ Project-level, git tracked
Medium --agents CLI flag Dynamic, session-only
Lowest ~/.claude/agents/ Personal, not shared

# Supported AI Coding Agents

This skill is compatible with the SKILL.md standard and works with all major AI coding agents:

Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.