agent-development

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]. Typical triggers include [scenario 1 in prose], [scenario 2 in prose], and [scenario 3 in prose]. See "When to invoke" in the agent body for worked scenarios. model: inherit color: blue tools: ["Read", "Write", "Grep"] --- You are [agent role description]... ## When to invoke [Two to four representative scenarios written as prose, e.g.:] - **[Scenario name].** [What the situation looks like and what the agent should do.] - **[Scenario name].** [Same.] **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 — it is loaded into context whenever the agent is registered, so the harness can decide when to dispatch. Must include: Triggering conditions ("Use this agent when...") A short prose summary of the typical trigger scenarios A pointer to a "When to invoke" section in the agent body for the detailed worked scenarios Format: Use this agent when [conditions]. Typical triggers include [scenario 1 in prose], [scenario 2 in prose], and [scenario 3 in prose]. See "When to invoke" in the agent body for worked scenarios. Best practices: Name 2-4 trigger scenarios in the prose summary Cover both proactive (assistant invokes itself) and reactive (user requests) triggering Cover different phrasings of the same intent Be specific about when NOT to use the agent Put detailed scenarios in the body under "When to invoke" as a bullet list of prose descriptions 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 - A "When to invoke" section listing 2-4 trigger scenarios as prose bullets 4. Create identifier (lowercase, hyphens, 3-50 chars) 5. Write description with triggering conditions and a short prose summary of trigger scenarios Return JSON with: { "identifier": "agent-name", "whenToUse": "Use this agent when... Typical triggers include [...]. See \"When to invoke\" in the agent body.", "systemPrompt": "You are..." } Then convert to agent file format with frontmatter. See examples/agent-creation-prompt.md for complete template. Method 2: Manual Creation Choose agent identifier (3-50 chars, lowercase, hyphens) Write description with examples Select model (usually inherit ) Choose color for visual identification Define tools (if restricting access) Write system prompt with structure above Save as agents/agent-name.md Validation Rules Identifier Validation ✅ Valid: code-reviewer, test-gen, api-analyzer-v2 ❌ Invalid: ag (too short), -start (starts with hyphen), my_agent (underscore) Rules: 3-50 characters Lowercase letters, numbers, hyphens only Must start and end with alphanumeric No underscores, spaces, or special characters Description Validation Length: 10-5,000 characters Must include: Triggering conditions and examples Best: 200-1,000 characters with 2-4 examples System Prompt Validation Length: 20-10,000 characters Best: 500-3,000 characters Structure: Clear responsibilities, process, output format Agent Organization Plugin Agents Directory plugin-name/ └── agents/ ├── analyzer.md ├── reviewer.md └── generator.md All .md files in agents/ are auto-discovered. Namespacing Agents are namespaced automatically: Single plugin: agent-name With subdirectories: plugin:subdir:agent-name Testing Agents Test Triggering Create test scenarios to verify agent triggers correctly: Write agent with specific triggering examples Use similar phrasing to examples in test Check Claude loads the agent Verify agent provides expected functionality Test System Prompt Ensure system prompt is complete: Give agent typical task Check it follows process steps Verify output format is correct Test edge cases mentioned in prompt Confirm quality standards are met Quick Reference Minimal Agent --- name: simple-agent description: Use this agent when [condition]. Typical triggers include [trigger 1] and [trigger 2]. See "When to invoke" in the agent body. model: inherit color: blue --- You are an agent that [does X]. ## When to invoke - **[Scenario A].** [Description.] - **[Scenario B].** [Description.] Process: 1. [Step 1] 2. [Step 2] Output: [What to provide] Frontmatter Fields Summary Field Required Format Example name Yes lowercase-hyphens code-reviewer description Yes Prose triggers Use when... Typical triggers include... model Yes inherit/sonnet/opus/haiku inherit color Yes Color name blue tools No Array of tool names ["Read", "Grep"] Best Practices DO: ✅ Name 2-4 trigger scenarios in the description (as prose) ✅ Put detailed worked scenarios in a "When to invoke" body section, as prose bullets ✅ Write specific triggering conditions ✅ Use inherit for model unless specific need ✅ Choose appropriate tools (least privilege) ✅ Write clear, structured system prompts ✅ Test agent triggering thoroughly DON'T: ❌ Use generic descriptions without trigger scenarios ❌ Omit triggering conditions ❌ Give all agents same color ❌ Grant unnecessary tool access ❌ Write vague system prompts ❌ Skip testing Additional Resources Reference Files For detailed guidance, consult: references/system-prompt-design.md - Complete system prompt patterns references/triggering-examples.md - Example formats and best practices references/agent-creation-system-prompt.md - The exact prompt from Claude Code Example Files Working examples in examples/ : agent-creation-prompt.md - AI-assisted agent generation template complete-agent-examples.md - Full agent examples for different use cases Utility Scripts Development tools in scripts/ : validate-agent.sh - Validate agent file structure test-agent-trigger.sh - Test if agent triggers correctly Implementation Workflow To create an agent for a plugin: Define agent purpose and triggering conditions Choose creation method (AI-assisted or manual) Create agents/agent-name.md file Write frontmatter with all required fields Write system prompt following best practices Name 2-4 trigger scenarios in description (prose) and detail them in a "When to invoke" body section Validate with scripts/validate-agent.sh Test triggering with real scenarios Document agent in plugin README Focus on clear triggering conditions and comprehensive system prompts for autonomous operation.