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This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts,

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open-claudecode
97415 skills14 agents14 commands1 MCP

Claude Code

$ npx -y skills add LING71671/Open-ClaudeCode --skill agent-development --agent claude-code

SKILL.md

agent-development.SKILL.md
name: Agent Development
description: This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
version: 0.1.0

Agent Development for Claude Code Plugins

Overview

Agents are autonomous subprocesses that handle complex, multi-step tasks independently. Understanding agent structure, triggering conditions, and system prompt design enables creating powerful autonomous capabilities.

**Key concepts:**

  • Agents are FOR autonomous work, commands are FOR user-initiated actions
  • Markdown file format with YAML frontmatter
  • Triggering via description field with examples
  • System prompt defines agent behavior
  • Model and color customization

Agent File Structure

Complete Format

---
name: agent-identifier
description: Use this agent when [triggering conditions]. Examples:

<example>
Context: [Situation description]
user: "[User request]"
assistant: "[How assistant should respond and use this agent]"
<commentary>
[Why this agent should be triggered]
</commentary>
</example>

<example>
[Additional example...]
</example>

model: inherit
color: blue
tools: ["Read", "Write", "Grep"]
---

You are [agent role description]...

**Your Core Responsibilities:**
1. [Responsibility 1]
2. [Responsibility 2]

**Analysis Process:**
[Step-by-step workflow]

**Output Format:**
[What to return]

Frontmatter Fields

name (required)

Agent identifier used for namespacing and invocation.

**Format:** lowercase, numbers, hyphens only **Length:** 3-50 characters **Pattern:** Must start and end with alphanumeric

**Good examples:**

  • `code-reviewer`
  • `test-generator`
  • `api-docs-writer`
  • `security-analyzer`

**Bad examples:**

  • `helper` (too generic)
  • `-agent-` (starts/ends with hyphen)
  • `my_agent` (underscores not allowed)
  • `ag` (too short, < 3 chars)

description (required)

Defines when Claude should trigger this agent. **This is the most critical field.**

**Must include:** 1. Triggering conditions ("Use this agent when...") 2. Multiple `<example>` blocks showing usage 3. Context, user request, and assistant response in each example 4. `<commentary>` explaining why agent triggers

**Format:**

Use this agent when [conditions]. Examples:

<example>
Context: [Scenario description]
user: "[What user says]"
assistant: "[How Claude should respond]"
<commentary>
[Why this agent is appropriate]
</commentary>
</example>

[More examples...]

**Best practices:**

  • Include 2-4 concrete examples
  • Show proactive and reactive triggering
  • Cover different phrasings of same intent
  • Explain reasoning in commentary
  • Be specific about when NOT to use the agent

model (required)

Which model the agent should use.

**Options:**

  • `inherit` - Use same model as parent (recommended)
  • `sonnet` - Claude Sonnet (balanced)
  • `opus` - Claude Opus (most capable, expensive)
  • `haiku` - Claude Haiku (fast, cheap)

**Recommendation:** Use `inherit` unless agent needs specific model capabilities.

color (required)

Visual identifier for agent in UI.

**Options:** `blue`, `cyan`, `green`, `yellow`, `magenta`, `red`

**Guidelines:**

  • Choose distinct colors for different agents in same plugin
  • Use consistent colors for similar agent types
  • Blue/cyan: Analysis, review
  • Green: Success-oriented tasks
  • Yellow: Caution, validation
  • Red: Critical, security
  • Magenta: Creative, generation

tools (optional)

Restrict agent to specific tools.

**Format:** Array of tool names

tools: ["Read", "Write", "Grep", "Bash"]

**Default:** If omitted, agent has access to all tools

**Best practice:** Limit tools to minimum needed (principle of least privilege)

**Common tool sets:**

  • Read-only analysis: `["Read", "Grep", "Glob"]`
  • Code generation: `["Read", "Write", "Grep"]`
  • Testing: `["Read", "Bash", "Grep"]`
  • Full access: Omit field or use `["*"]`

System Prompt Design

The markdown body becomes the agent's system prompt. Write in second person, addressing the agent directly.

Structure

**Standard template:**

You are [role] specializing in [domain].

**Your Core Responsibilities:**
1. [Primary responsibility]
2. [Secondary responsibility]
3. [Additional responsibilities...]

**Analysis Process:**
1. [Step one]
2. [Step two]
3. [Step three]
[...]

**Quality Standards:**
- [Standard 1]
- [Standard 2]

**Output Format:**
Provide results in this format:
- [What to include]
- [How to structure]

**Edge Cases:**
Handle these situations:
- [Edge case 1]: [How to handle]
- [Edge case 2]: [How to handle]

Best Practices

✅ **DO:**

  • Write in second person ("You are...", "You will...")
  • Be specific about responsibilities
  • Provide step-by-step process
  • Define output format
  • Include quality standards
  • Address edge cases
  • Keep under 10,000 characters

❌ **DON'T:**

  • Write in first person ("I am...", "I will...")
  • Be vague or generic
  • Omit process steps
  • Leave output format undefined
  • Skip quality guidance
  • Ignore error cases

Creating Agents

Method 1: AI-Assisted Generation

Use this prompt pattern (extracted from Claude Code):

Create an agent configuration based on this request: "[YOUR DESCRIPTION]"

Requirements:
1. Extract core intent and responsibilities
2. Design expert persona for the domain
3. Create comprehensive system prompt with:
   - Clear behavioral boundaries
   - Specific methodologies
   - Edge case handling
   - Output format
4. Create identifier (lowercase, hyphens, 3-50 chars)
5. Write description with triggering conditions
6. Include 2-3 <example> blocks showing when to use

Return JSON with:
{
  "identifier": "agent-name",
  "whenToUse": "Use this agent when... Examples: <example>...</example>",
  "systemPrompt": "You a
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完整开源的 Claude Code 项目 - 基于 Anthropic 官方源码重建 🌐 Languages: 中文 | English

97415 skills14 agents1 MCP
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Questions about agent-development.

Which coding agents can use agent-development?
agent-development installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.