Creating Claude Code Agents - Expert Skill

Use this skill when creating or improving Claude Code agents. Provides comprehensive guidance on agent structure, schema validation, and best practices for building long-running AI assistants.

When to Use This Skill

Activate this skill when:

• User asks to create a new Claude Code agent
• User wants to improve an existing agent
• User needs help with agent frontmatter or structure
• User is troubleshooting agent validation issues
• User wants to understand agent format requirements
• User asks about agent vs skill vs slash command differences

Quick Reference

Agent File Structure

---
name: agent-name
description: When and why to use this agent
allowed-tools: Read, Write, Bash
model: sonnet
agentType: agent
---

# 🔍 Agent Display Name

You are [persona definition - describe the agent's role and expertise].

## Instructions

[Clear, actionable guidance on what the agent does]

## Process

[Step-by-step workflow the agent follows]

## Examples

[Code samples and use cases demonstrating the agent's capabilities]

File Location

Required Path:

.claude/agents/*.md

Agents must be placed in .claude/agents/ directory as markdown files.

Frontmatter Requirements

Required Fields

| Field | Type | Description | Example | |-------|------|-------------|---------| | name | string | Agent identifier (lowercase, hyphens only) | code-reviewer | | description | string | Brief overview of functionality and use cases | Reviews code for best practices and potential issues |

Optional Fields

| Field | Type | Description | Values | |-------|------|-------------|--------| | allowed-tools | string | Comma-separated list of available tools | Read, Write, Bash, WebSearch | | model | string | Claude model to use | sonnet, opus, haiku, inherit | | agentType | string | Explicit marker for format preservation | agent |

Validation Rules

Name Field:

• Pattern: ^[a-z0-9-]+$ (lowercase letters, numbers, hyphens only)
• Max length: 64 characters
• Example: ✅ code-reviewer ❌ Code_Reviewer

Description Field:

• Max length: 1024 characters
• Should clearly explain when to use the agent
• Start with action words: "Reviews...", "Analyzes...", "Helps with..."

Allowed Tools: Valid tools: Read, Write, Edit, Grep, Glob, Bash, WebSearch, WebFetch, Task, Skill, SlashCommand, TodoWrite, AskUserQuestion

Model Values:

• sonnet - Balanced, good for most agents (default)
• opus - Complex reasoning, architectural decisions
• haiku - Fast, simple tasks
• inherit - Use parent conversation's model

Content Format Requirements

H1 Heading (Required)

The first line of content must be an H1 heading that serves as the agent's display title:

# 🔍 Code Reviewer

Best Practices:

• Include an emoji icon for visual distinction
• Use title case
• Keep concise (2-5 words)
• Make it descriptive and memorable

Persona Definition (Required for Agents)

Immediately after the H1, define the agent's persona using "You are..." format:

You are an expert code reviewer with deep knowledge of software engineering principles and security best practices.

Guidelines:

• Start with "You are..."
• Define role and expertise clearly
• Set expectations for the agent's capabilities
• Establish the agent's approach and tone

Content Structure

# 🔍 Agent Name

You are [persona definition].

## Instructions

[What the agent does and how it approaches tasks]

## Process

1. [Step 1]
2. [Step 2]
3. [Step 3]

## Examples

[Code samples showing good/bad patterns]

## Guidelines

- [Best practice 1]
- [Best practice 2]

Schema Validation

Agents must conform to the JSON schema at: https://github.com/pr-pm/prpm/blob/main/packages/converters/schemas/claude-agent.schema.json

Schema Structure

{
  "frontmatter": {
    "name": "string (required)",
    "description": "string (required)",
    "allowed-tools": "string (optional)",
    "model": "enum (optional)",
    "agentType": "agent (optional)"
  },
  "content": "string (markdown with H1, persona, instructions)"
}

Common Validation Errors

| Error | Cause | Fix | |-------|-------|-----| | Missing required field 'name' | Frontmatter lacks name field | Add name: agent-name | | Missing required field 'description' | Frontmatter lacks description | Add description: ... | | Invalid name pattern | Name contains uppercase or special chars | Use lowercase and hyphens only | | Name too long | Name exceeds 64 characters | Shorten the name | | Invalid model value | Model not in enum | Use: sonnet, opus, haiku, or inherit | | Missing H1 heading | Content doesn't start with # | Add # Agent Name as first line |

Tool Configuration

Inheriting All Tools

Omit the allowed-tools field to inherit all tools from the parent conversation:

---
name: full-access-agent
description: Agent needs access to everything
# No allowed-tools field = inherits all
---

Specific Tools Only

Grant minimal necessary permissions:

---
name: read-only-reviewer
description: Reviews code without making changes
allowed-tools: Read, Grep, Bash
---

Bash Tool Restrictions

Use command patterns to restrict Bash access:

---
name: git-helper
description: Git operations only
allowed-tools: Bash(git *), Read
---

Syntax:

• Bash(git *) - Only git commands
• Bash(npm test:*) - Only npm test scripts
• Bash(git status:*), Bash(git diff:*) - Multiple specific commands

Model Selection Guide

Sonnet (Most Agents)

Use for:

• Code review
• Debugging
• Data analysis
• General problem-solving

model: sonnet

Opus (Complex Reasoning)

Use for:

• Architecture decisions
• Complex refactoring
• Deep security analysis
• Novel problem-solving

model: opus

Haiku (Speed Matters)

Use for:

• Syntax checks
• Simple formatting
• Quick validations
• Low-latency needs

model: haiku

Inherit (Context-Dependent)

Use for:

• Agent should match user's model choice
• Cost sensitivity

model: inherit

Common Mistakes

| Mistake | Problem | Solution | |---------|---------|----------| | Using _ in name | Violates pattern constraint | Use hyphens: code-reviewer not code_reviewer | | Uppercase in name | Violates pattern constraint | Lowercase only: debugger not Debugger | | Missing persona | Agent lacks role definition | Add "You are..." after H1 | | No H1 heading | Content format invalid | Start content with # Agent Name | | Vague description | Agent won't activate correctly | Be specific about when to use | | Too many tools | Security risk, violates least privilege | Grant only necessary tools | | No agentType field | May lose type info in conversion | Add agentType: agent | | Generic agent name | Conflicts or unclear purpose | Use specific, descriptive names |

Best Practices

1. Write Clear, Specific Descriptions

The description determines when Claude automatically invokes your agent.

✅ Good:

description: Reviews code changes for quality, security, and maintainability issues

❌ Poor:

description: A helpful agent  # Too vague

2. Define Strong Personas

Establish expertise and approach immediately after the H1:

# 🔍 Code Reviewer

You are an expert code reviewer specializing in TypeScript and React, with 10+ years of experience in security-focused development. You approach code review systematically, checking for security vulnerabilities, performance issues, and maintainability concerns.

3. Provide Step-by-Step Processes

Guide the agent's workflow explicitly:

## Review Process

1. **Read the changes**
   - Get recent git diff or specified files
   - Understand the context and purpose

2. **Analyze systematically**
   - Check each category (quality, security, performance)
   - Provide specific file:line references
   - Explain why something is an issue

3. **Provide actionable feedback**
   - Categorize by severity
   - Include fix suggestions
   - Highlight positive patterns

4. Include Examples

Show both good and bad patterns:

## Examples

When reviewing error handling:

❌ **Bad - Silent failure:**
\`\`\`typescript
try {
  await fetchData();
} catch (error) {
  console.log(error);
}
\`\`\`

✅ **Good - Proper error handling:**
\`\`\`typescript
try {
  await fetchData();
} catch (error) {
  logger.error('Failed to fetch data', error);
  throw new AppError('Data fetch failed', { cause: error });
}
\`\`\`

5. Use Icons in H1 for Visual Distinction

Choose emojis that represent the agent's purpose:

• 🔍 Code Reviewer
• 🐛 Debugger
• 📊 Data Scientist
• 🔒 Security Auditor
• ⚡ Performance Optimizer
• 📝 Documentation Writer
• 🧪 Test Generator

6. Maintain Single Responsibility

Each agent should excel at ONE specific task:

✅ Good:

• code-reviewer - Reviews code for quality and security
• debugger - Root cause analysis and minimal fixes

❌ Poor:

• code-helper - Reviews, debugs, tests, refactors, documents (too broad)

7. Grant Minimal Tool Access

Follow the principle of least privilege:

# Read-only analysis agent
allowed-tools: Read, Grep

# Code modification agent
allowed-tools: Read, Edit, Bash(git *)

# Full development agent
allowed-tools: Read, Write, Edit, Bash, Grep, Glob

8. Include agentType for Round-Trip Conversion

Always include agentType: agent in frontmatter to preserve type information during format conversions:

---
name: code-reviewer
description: Reviews code for best practices
agentType: agent
---

Example Agent Templates

Minimal Agent

---
name: simple-reviewer
description: Quick code review for common issues
allowed-tools: Read, Grep
model: haiku
agentType: agent
---

# 🔍 Simple Code Reviewer

You are a code reviewer focused on catching common mistakes quickly.

## Instructions

Review code for:
- Syntax errors
- Common anti-patterns
- Missing error handling
- Console.log statements

Provide concise feedback with file:line references.

Comprehensive Agent

---
name: security-auditor
description: Deep security vulnerability analysis for code changes
allowed-tools: Read, Grep, WebSearch, Bash(git *)
model: opus
agentType: agent
---

# 🔒 Security Auditor

You are a security expert specializing in application security, with expertise in OWASP Top 10, secure coding practices, and threat modeling. You perform thorough security analysis of code changes.

## Review Process

1. **Gather Context**
   - Read changed files
   - Review git history for context
   - Identify data flows and trust boundaries

2. **Security Analysis**
   - Input validation and sanitization
   - Authentication and authorization
   - SQL injection risks
   - XSS vulnerabilities
   - CSRF protection
   - Secrets exposure
   - Cryptography usage
   - Dependency vulnerabilities

3. **Threat Assessment**
   - Rate severity (Critical/High/Medium/Low)
   - Assess exploitability
   - Determine business impact
   - Provide remediation guidance

4. **Report Findings**
   Use structured format with CVE references where applicable.

## Output Format

**Security Score: X/10**

### Critical Issues (Fix Immediately)
- [Vulnerability] (file:line) - [Explanation] - [CVE if applicable] - [Fix]

### High Priority
- [Issue] (file:line) - [Explanation] - [Fix]

### Medium Priority
- [Concern] (file:line) - [Explanation] - [Recommendation]

### Best Practices
- [Positive security pattern observed]

**Recommendation:** [Approve/Request Changes/Block]

## Examples

### SQL Injection Check

❌ **Vulnerable:**
\`\`\`typescript
const query = \`SELECT * FROM users WHERE id = \${userId}\`;
db.query(query);
\`\`\`

✅ **Safe:**
\`\`\`typescript
const query = 'SELECT * FROM users WHERE id = $1';
db.query(query, [userId]);
\`\`\`

Validation Checklist

Before finalizing an agent:

• [ ] Name is lowercase with hyphens only
• [ ] Name is 64 characters or less
• [ ] Description clearly explains when to use the agent
• [ ] Description is 1024 characters or less
• [ ] Content starts with H1 heading (with emoji icon)
• [ ] Persona is defined using "You are..." format
• [ ] Process or instructions are clearly outlined
• [ ] Examples are included (showing good/bad patterns)
• [ ] Tool access is minimal and specific
• [ ] Model selection is appropriate for task complexity
• [ ] agentType field is set to "agent"
• [ ] File is saved in .claude/agents/ directory
• [ ] Agent has been tested with real tasks
• [ ] Edge cases are considered

Schema Reference

Official Schema URL:

https://github.com/pr-pm/prpm/blob/main/packages/converters/schemas/claude-agent.schema.json

Local Schema Path:

/Users/khaliqgant/Projects/prpm/app/packages/converters/schemas/claude-agent.schema.json

Related Documentation

• agent-builder skill - Creating effective subagents
• slash-command-builder skill - For simpler, command-based prompts
• creating-skills skill - For context-aware reference documentation
• Claude Code Docs: https://docs.claude.com/claude-code

Agents vs Skills vs Commands

Use Agents When:

• ✅ Long-running assistants with persistent context
• ✅ Complex multi-step workflows
• ✅ Specialized expertise needed
• ✅ Tool access required
• ✅ Repeatable processes with quality standards

Use Skills When:

• ✅ Context-aware automatic activation
• ✅ Reference documentation and patterns
• ✅ Team standardization
• ✅ No persistent state needed

Use Slash Commands When:

• ✅ Simple, focused prompts
• ✅ Quick manual invocation
• ✅ Personal productivity shortcuts
• ✅ Single-file prompts

Decision Tree:

Need specialized AI assistant?
├─ Yes → Needs tools and persistent context?
│         ├─ Yes → Use Agent
│         └─ No → Quick invocation?
│                 ├─ Yes → Use Slash Command
│                 └─ No → Use Skill
└─ No → Just documentation? → Use Skill

Troubleshooting

Agent Not Activating

Problem: Agent doesn't get invoked when expected

Solutions:

1. Make description more specific to match use case
2. Verify file is in .claude/agents/*.md
3. Check for frontmatter syntax errors
4. Explicitly request: "Use the [agent-name] agent"

Validation Errors

Problem: Agent file doesn't validate against schema

Solutions:

1. Check name pattern (lowercase, hyphens only)
2. Verify required fields (name, description)
3. Ensure content starts with H1 heading
4. Validate model value is in enum
5. Check allowed-tools spelling and capitalization

Tool Permission Denied

Problem: Agent can't access needed tools

Solutions:

1. Add tools to allowed-tools in frontmatter
2. Use correct capitalization (e.g., Read, not read)
3. For Bash restrictions, use pattern syntax: Bash(git *)
4. Omit allowed-tools field to inherit all tools

Poor Agent Performance

Problem: Agent produces inconsistent or low-quality results

Solutions:

1. Strengthen persona definition
2. Add more specific process steps
3. Include examples of good/bad patterns
4. Define explicit output format
5. Consider using more powerful model (opus)
6. Break complex agents into specialized ones

Remember: Great agents are specialized experts with clear personas, step-by-step processes, and minimal tool access. Focus each agent on doing ONE thing exceptionally well with measurable outcomes.