Subagent Creator
This skill provides guidance for creating effective, agent-agnostic subagents.
What are Subagents?
Subagents are specialized assistants that an AI agent can delegate tasks to. Characteristics:
- Isolated context: Each subagent has its own context window
- Parallel execution: Multiple subagents can run simultaneously
- Specialization: Configured with specific prompts and expertise
- Reusable: Defined once, used in multiple contexts
When to Use Subagents vs Skills
Is the task complex with multiple steps? ├─ YES → Does it require isolated context? │ ├─ YES → Use SUBAGENT │ └─ NO → Use SKILL │ └─ NO → Use SKILL
Use Subagents for:
- Complex workflows requiring isolated context
- Long-running tasks that benefit from specialization
- Verification and auditing (independent perspective)
- Parallel workstreams
Use Skills for:
- Quick, one-off actions
- Domain knowledge without context isolation
- Reusable procedures that don't need isolation
Subagent Structure
A subagent is typically a markdown file with frontmatter metadata:
markdown--- name: agent-name description: Description of when to use this subagent. model: inherit # or fast, or specific model ID readonly: false # true to restrict write permissions --- You are an [expert in X]. When invoked: 1. [Step 1] 2. [Step 2] 3. [Step 3] [Detailed instructions about expected behavior] Report [type of expected result]: - [Output format] - [Metrics or specific information]
Subagent Creation Process
1. Define the Purpose
- What specific responsibility does the subagent have?
- Why does it need isolated context?
- Does it involve multiple complex steps?
- Does it require deep specialization?
2. Configure the Metadata
name (required)
Unique identifier. Use kebab-case.
yamlname: security-auditor
description (critical)
CRITICAL for automatic delegation. Explains when to use this subagent.
Good descriptions:
- "Security specialist. Use when implementing auth, payments, or handling sensitive data."
- "Debugging specialist for errors and test failures. Use when encountering issues."
- "Validates completed work. Use after tasks are marked done."
Phrases that encourage automatic delegation:
- "Use proactively when..."
- "Always use for..."
- "Automatically delegate when..."
model (optional)
yamlmodel: inherit # Uses same model as parent (default) model: fast # Uses fast model for quick tasks
readonly (optional)
yamlreadonly: true # Restricts write permissions
3. Write the Subagent Prompt
Define:
- Identity: "You are an [expert]..."
- When invoked: Context of use
- Process: Specific steps to follow
- Expected output: Format and content
Template:
markdownYou are an [expert in X] specialized in [Y]. When invoked: 1. [First action] 2. [Second action] 3. [Third action] [Detailed instructions about approach] Report [type of result]: - [Specific format] - [Information to include] - [Metrics or criteria] [Philosophy or principles to follow]
Common Subagent Patterns
1. Verification Agent
Purpose: Independently validates that completed work actually works.
markdown--- name: verifier description: Validates completed work. Use after tasks are marked done. model: fast --- You are a skeptical validator. When invoked: 1. Identify what was declared as complete 2. Verify the implementation exists and is functional 3. Execute tests or relevant verification steps 4. Look for edge cases that may have been missed Be thorough. Report: - What was verified and passed - What is incomplete or broken - Specific issues to address
2. Debugger
Purpose: Expert in root cause analysis.
markdown--- name: debugger description: Debugging specialist. Use when encountering errors or test failures. --- You are a debugging expert. When invoked: 1. Capture the error message and stack trace 2. Identify reproduction steps 3. Isolate the failure location 4. Implement minimal fix 5. Verify the solution works For each issue, provide: - Root cause explanation - Evidence supporting the diagnosis - Specific code fix - Testing approach
3. Security Auditor
Purpose: Security expert auditing code.
markdown--- name: security-auditor description: Security specialist. Use for auth, payments, or sensitive data. --- You are a security expert. When invoked: 1. Identify security-sensitive code paths 2. Check for common vulnerabilities 3. Confirm secrets are not hardcoded 4. Review input validation Report findings by severity: - **Critical** (must fix before deploy) - **High** (fix soon) - **Medium** (address when possible) - **Low** (suggestions)
4. Code Reviewer
Purpose: Code review with focus on quality.
markdown--- name: code-reviewer description: Code review specialist. Use when changes are ready for review. --- You are a code review expert. When invoked: 1. Analyze the code changes 2. Check readability, performance, patterns, error handling 3. Identify code smells and potential bugs 4. Suggest specific improvements Report: **✅ Approved / ⚠️ Approved with caveats / ❌ Changes needed** **Issues Found:** - **[Severity]** [Location]: [Issue] - Suggestion: [How to fix]
Best Practices
✅ DO
- Write focused subagents: One clear responsibility
- Invest in the description: Determines when to delegate
- Keep prompts concise: Direct and specific
- Share with team: Version control subagent definitions
- Test the description: Check correct subagent is triggered
❌ AVOID
- Vague descriptions: "Use for general tasks" gives no signal
- Prompts too long: 2000 words don't make it smarter
- Too many subagents: Start with 2-3 focused ones
Quality Checklist
Before finalizing:
- Description is specific about when to delegate
- Name uses kebab-case
- One clear responsibility (not generic)
- Prompt is concise but complete
- Instructions are actionable
- Output format is well defined
- Model configuration appropriate
Output Messages
When creating a subagent:
✅ Subagent created successfully! 📁 Location: .agent/subagents/[name].md 🎯 Purpose: [brief description] 🔧 How to invoke: - Automatic: Agent delegates when it detects [context] - Explicit: /[name] [instruction] 💡 Tip: Include keywords like "use proactively" to encourage delegation.
