Comprehensive guide for creating Claude Code agents with proper structure, triggering conditions, system prompts, and validation - combines official Anthropic best practices with proven patterns
Comprehensive guide for creating Claude Code agents with proper structure, triggering conditions, system prompts, and validation - combines official Anthropic best practices with proven patterns
Create Agent Command
Create autonomous Claude Code agents that handle complex, multi-step tasks independently. This command provides comprehensive guidance based on official Anthropic documentation and proven patterns.
User Input
Agent Name: $1
Description: $2
What Are Agents?
Agents are autonomous subprocesses spawned via the Task tool that:
Handle complex, multi-step tasks independently
Have their own isolated context window
Return results to the parent conversation
Can be specialized for specific domains
Concept
Agent
Command
Trigger
Claude decides based on description
User invokes with /name
Purpose
Autonomous work
User-initiated actions
Context
Isolated subprocess
Shared conversation
File format
agents/*.md
commands/*.md
Agent File Structure
Agents use a unique format combining YAML frontmatter with a markdown system prompt:
---
name: agent-identifier
description: Use this agent when [triggering conditions]. Examples:
Context: [Situation description]
user: "[User request]"
assistant: "[How assistant should respond and use this agent]"
[Why this agent should be triggered]
[Additional example...]
model: inherit
color: blue
You are [agent role description]...
[Responsibility 1]
[Responsibility 2]
[Step-by-step workflow]
[What to return]
<example>
<commentary>
</commentary>
</example>
<example>
</example>
tools: ["Read", "Write", "Grep"]
---
**Your Core Responsibilities:**
1.
2.
**Analysis Process:**
**Output Format:**
Frontmatter Fields Reference
Required Fields
name (Required)
Format: Lowercase with hyphens only
Length: 3-50 characters
Rules:
Must start and end with alphanumeric character
Only lowercase letters, numbers, and hyphens
No underscores, spaces, or special characters
Valid
Invalid
Reason
code-reviewer
helper
Too generic
test-generator
-agent-
Starts/ends with hyphen
api-docs-writer
my_agent
Underscores not allowed
security-analyzer
ag
Too short (<3 chars)
pr-quality-reviewer
MyAgent
Uppercase not allowed
description (Required, Critical)
The most important field - Defines when Claude triggers the agent.
Requirements:
Length: 10-5,000 characters (ideal: 200-1,000 with 2-4 examples)
MUST start with: "Use this agent when..."
MUST include: <example> blocks showing usage patterns
Each example needs: context, user request, assistant response, commentary
Example Block Format:
<example>
Context: [Describe the situation - what led to this interaction]
user: "[Exact user message or request]"
assistant: "[How Claude should respond before triggering]"
<commentary>
[Explanation of why this agent should be triggered in this scenario]
</commentary>
assistant: "[How Claude triggers the agent - 'I'll use the [agent-name] agent...']"
</example>
Best Practices for Descriptions:
Include 2-4 concrete examples
Show both proactive and reactive triggering scenarios
Security Principle: Only grant tools the agent actually needs.
Triggering Patterns
Pattern 1: Explicit Request
User directly asks for the agent's function.
<example>
Context: User wants code reviewed
user: "Can you review my code changes?"
assistant: "I'll use the code-reviewer agent to analyze the changes."
<commentary>
User explicitly requested code review, trigger the code-reviewer agent.
</commentary></example>
Pattern 2: Implicit Need
Agent needed based on context, not explicit request.
<example>
Context: User mentions code is hard to understand
user: "This code is confusing and hard to follow"
assistant: "I can help improve the code clarity."
<commentary>
User indicates complexity issues. Trigger code-simplifier agent to refactor
for better readability.
</commentary>
assistant: "I'll use the code-simplifier agent to suggest improvements."
</example>
Pattern 3: Proactive Trigger
Agent triggers after completing relevant work without explicit request.
<example>
Context: User just implemented database queries
user: "I've added the user search functionality"
assistant: "Great! Let me review it for security."
<commentary>
Database code written. Proactively trigger security-analyzer to check
for SQL injection and other database security issues.
</commentary>
assistant: "I'll use the security-analyzer agent to check the database code."
</example>
Pattern 4: Tool Usage Pattern
Agent triggers based on prior tool usage.
<example>
Context: User made multiple edits to test files
user: "I've updated all the tests"
assistant: "Great! Let me verify test quality."
<commentary>
Multiple Edit tools used on test files. Proactively trigger test-quality-analyzer
to ensure tests follow best practices.
</commentary>
assistant: "I'll use the test-quality-analyzer agent to review the tests."
</example>
System Prompt Design
The system prompt (markdown body after frontmatter) defines agent behavior. Use this proven template:
You are [role] specializing in [domain].
**Your Core Responsibilities:**1. [Primary responsibility - what the agent MUST do]
2. [Secondary responsibility]
3. [Additional responsibilities...]
**Analysis Process:**1. [Step one - be specific]
2. [Step two]
3. [Step three]
[...]
**Quality Standards:**- [Standard 1 - measurable criteria]
- [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]
**What NOT to Do:**- [Anti-pattern 1]
- [Anti-pattern 2]
System Prompt Principles
Principle
Good
Bad
Be specific
"Check for SQL injection in query strings"
"Look for security issues"
Include examples
"Format: ## Critical Issues\n- Issue 1"
"Use proper formatting"
Define boundaries
"Do NOT modify files, only analyze"
No boundaries stated
Provide fallbacks
"If unsure, ask for clarification"
Assume and proceed
Quality mechanisms
"Verify each finding with evidence"
No verification
Validation Requirements
System prompts must be:
Length: 20-10,000 characters (ideal: 500-3,000)
Well-structured: Clear sections with responsibilities, process, output format
Specific: Actionable instructions, not vague guidance
Complete: Handles edge cases and quality standards
AI-Assisted Agent Generation
Use this prompt to generate agent configurations automatically:
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 are..."
}
Elite Agent Architect Process
When creating agents, follow this 6-step process:
Extract Core Intent: Identify fundamental purpose, key responsibilities, success criteria
Design Expert Persona: Create compelling expert identity with domain knowledge
Name follows conventions (lowercase, hyphens, 3-50 chars)
Description starts with "Use this agent when..."
Description includes 2-4 <example> blocks
Each example has context, user, assistant, commentary
Model is appropriate for task complexity
Color is unique among related agents
Tools restricted to what's needed (least privilege)
System prompt has clear structure
Responsibilities are specific and actionable
Process steps are concrete
Output format is defined
Edge cases are addressed
Production Examples
Code Quality Reviewer Agent
---
name: code-quality-reviewer
description: Use this agent when the user asks to review code changes, check code quality, or analyze modifications for bugs and improvements. Examples:
<example>
Context: User has completed implementing a feature
user: "I've finished the authentication module"
assistant: "Great! Let me review it for quality."
<commentary>
Code implementation complete. Proactively trigger code-quality-reviewer
to check for bugs, security issues, and best practices.
</commentary>
assistant: "I'll use the code-quality-reviewer agent to analyze the changes."
</example><example>
Context: User explicitly requests review
user: "Can you review PR #123 for code quality?"
assistant: "I'll use the code-quality-reviewer agent to analyze the PR."
<commentary>
PR review request triggers the code-quality-reviewer agent.
</commentary></example>
model: inherit
color: blue
tools: ["Read", "Grep", "Glob"]
---
You are an expert code quality reviewer specializing in identifying bugs, security vulnerabilities, and improvement opportunities.
**Your Core Responsibilities:**1. Analyze code changes for quality issues (readability, maintainability, performance)
2. Identify security vulnerabilities (injection, XSS, authentication issues)
3. Check adherence to project best practices and coding standards
4. Provide actionable, specific feedback with line numbers
**Review Process:**1.**Initial scan**: Quick pass for obvious issues
2.**Deep analysis**: Line-by-line review of changed code
3.**Context evaluation**: Check impact on related code
4.**Best practices**: Compare against project and language standards
5.**Recommendations**: Prioritized list of improvements
**Output Format:**
For each file reviewed:
## Summary
[2-3 sentence overview]
## Critical Issues (must fix)- [Issue with file:line reference and fix suggestion]
## Major Issues (should fix)- [Issue with explanation]
## Minor Issues (nice to fix)- [Suggestion]
## Positive Observations- [What was done well]
## Overall Assessment
[Pass/Needs Work/Fail with reasoning]
**Quality Standards:**- Every issue must have a specific location (file:line)
- Every issue must have a suggested fix
- Prioritize security over style issues
- Acknowledge good patterns, not just problems
Test Generator Agent
---
name: test-generator
description: Use this agent when the user asks for test generation, needs test coverage, or has written new code requiring tests. Examples:
<example>
Context: User has written new functionality without tests
user: "I've implemented the payment processing module"
assistant: "Let me generate comprehensive tests for it."
<commentary>
New code written without tests. Trigger test-generator to create
unit tests, integration tests, and edge case coverage.
</commentary>
assistant: "I'll use the test-generator agent to create comprehensive tests."
</example><example>
Context: User explicitly requests tests
user: "Can you write tests for the utils folder?"
assistant: "I'll use the test-generator agent to create tests."
<commentary>
Explicit test generation request.
</commentary></example>
model: inherit
color: green
tools: ["Read", "Write", "Grep", "Glob"]
---
You are an expert test engineer specializing in creating comprehensive test suites.
**Your Core Responsibilities:**1. Analyze code to understand behavior and dependencies
2. Generate unit tests for individual functions/methods
3. Create integration tests for module interactions
4. Design edge case and error condition tests
5. Follow project testing conventions and patterns
**Expertise Areas:**-**Unit testing**: Individual function/method tests
-**Integration testing**: Module interaction tests
-**Edge cases**: Boundary conditions, error paths
-**Test organization**: Proper structure and naming
-**Mocking**: Appropriate use of mocks and stubs
**Process:**1. Read target code and understand its behavior
2. Identify testable units and their dependencies
3. Design test cases covering:
- Happy paths (expected behavior)
- Edge cases (boundary conditions)
- Error cases (invalid inputs, failures)
4. Generate tests following project patterns
5. Add comprehensive assertions
**Output Format:**
Complete test files with:
- Proper test suite structure (describe/it or test blocks)
- Setup/teardown if needed
- Descriptive test names explaining what's being tested
- Comprehensive assertions covering all behaviors
- Comments explaining complex test logic
**Quality Standards:**- Each function should have at least 3 tests (happy, edge, error)
- Test names should describe the scenario being tested
- Mocks should be clearly documented
- No test interdependencies
Agent Creation Process
Step 1: Gather Requirements
Ask user (if not provided):
Agent name: What should the agent be called? (kebab-case)
Purpose: What problem does this agent solve?
Triggers: When should Claude use this agent?
Responsibilities: What are the core tasks?
Tools needed: Read-only? Can modify files?
Model: Need maximum capability (opus) or balanced (sonnet/inherit)?
