| name | agent-factory |
| description | Claude Code agent generation system that creates custom agents and sub-agents with enhanced YAML frontmatter, tool access patterns, and MCP integration support following proven production patterns |
Agent Factory
A comprehensive system for generating production-ready Claude Code agents and sub-agents. This skill provides templates, standards, and generation tools to create custom agents that seamlessly integrate with Claude Code's agent system.
What This Skill Does
This skill helps you create custom Claude Code agents for any domain or workflow. It generates properly formatted agent files that Claude Code can automatically discover and invoke when relevant.
Capabilities
- Generate Custom Agents - Create specialized agents for any domain (frontend, backend, testing, product, etc.)
- Enhanced YAML Frontmatter - Rich metadata including color coding, field categorization, expertise levels
- Tool Access Guidance - Recommends optimal tool configurations based on agent type
- MCP Integration - Suggests relevant MCP server tools for enhanced capabilities
- Execution Pattern Assignment - Ensures proper parallel/sequential execution for safety
- Validation - Checks agent configuration against best practices
Agent Types Supported
Strategic Agents (Lightweight, Parallel-Safe)
- Purpose: Planning, research, analysis
- Tools: Read, Write, Grep only
- Execution: 4-5 agents can run in parallel
- Color: Blue
- Examples: product-planner, market-researcher, architect
Implementation Agents (Full Tools, Coordinated)
- Purpose: Code writing, feature building
- Tools: Read, Write, Edit, Bash, Grep, Glob
- Execution: 2-3 agents coordinated
- Color: Green
- Examples: frontend-developer, backend-developer, api-builder
Quality Agents (Heavy Bash, Sequential Only)
- Purpose: Testing, validation, review
- Tools: Read, Write, Edit, Bash, Grep, Glob
- Execution: 1 agent at a time (NEVER parallel)
- Color: Red
- Examples: test-runner, code-reviewer, security-auditor
Coordination Agents (Lightweight, Orchestration)
- Purpose: Manages other agents, validates integration
- Tools: Read, Write, Grep
- Execution: Orchestrates others
- Color: Purple
- Examples: fullstack-coordinator, workflow-manager
Enhanced YAML Frontmatter
Every generated agent includes rich metadata:
---
name: agent-name-kebab-case
description: When to invoke this agent
tools: Read, Write, Edit
model: sonnet
color: green
field: frontend
expertise: expert
mcp_tools: mcp__playwright
---
Field Categories
Development: frontend, backend, fullstack, mobile, devops
Quality: testing, security, performance
Strategic: product, architecture, research, design
Domain: data, ai, content, finance, infrastructure
Color Coding
- Blue: Strategic/planning agents
- Green: Implementation/development agents
- Red: Quality/testing agents
- Purple: Coordination/orchestration agents
- Orange: Domain-specific specialists
Expertise Levels
- Beginner: Simple, focused tasks
- Intermediate: Moderate complexity workflows
- Expert: Advanced, complex operations
How to Use
Quick Start
- Open the prompt template: documentation/templates/AGENTS_FACTORY_PROMPT.md
- Scroll to bottom - Find template variables
- Fill in your details:
AGENT_NAME: my-custom-agent
DESCRIPTION: What this agent does and when to invoke it
DOMAIN_FIELD: frontend
TOOLS_NEEDED: Read, Write, Edit, Bash
- Copy entire prompt - Include filled variables
- Paste into Claude - Claude.ai, Claude Code, or API
- Receive agent file - Complete .md file ready to use
- Install agent - Copy to
.claude/agents/ or ~/.claude/agents/
Example Invocation
@agent-factory
Create a custom agent:
Name: api-integration-specialist
Type: Implementation
Domain: backend
Description: API integration expert for third-party services
Capabilities: OAuth, REST clients, error handling
Tools: Read, Write, Edit, Bash
MCP: mcp__github
Output: Complete .claude/agents/api-integration-specialist.md file
Generated Agent Structure
Each generated agent is a single Markdown file:
---
name: custom-agent
description: Triggers auto-invocation
tools: Read, Write, Edit
model: sonnet
color: green
field: backend
expertise: expert
mcp_tools: mcp__github
---
You are a [role] specializing in [domain].
When invoked:
1. [Step 1]
2. [Step 2]
3. [Step 3]
[Detailed instructions]
[Checklists]
[Best practices]
[Output format]
Integration Workflows
Workflow 1: Feature Development
1. product-planner → Creates requirements
2. frontend-developer + backend-developer → Build (parallel)
3. test-runner → Validates (sequential)
4. code-reviewer → Reviews (sequential)
Workflow 2: Bug Fix
1. debugger → Analyzes issue
2. [appropriate-dev-agent] → Fixes
3. test-runner → Validates fix
Workflow 3: Code Review
1. code-reviewer → Quality review (can run solo)
2. security-auditor → Security scan (can run solo)
MCP Tool Integration
Common MCP servers to integrate:
- mcp__github: PR reviews, issues, repo operations
- mcp__playwright: E2E testing, screenshots, browser automation
- mcp__context7: Documentation search, knowledge queries
- mcp__filesystem: Advanced file operations
- Custom MCP servers: Any user-configured MCP tools
Agents automatically reference MCP tools in their capabilities when configured.
Safety & Performance
Process Monitoring
Agents consume system resources. Monitor with:
ps aux | grep -E "mcp|npm|claude" | wc -l
Safe ranges:
- 15-20: Strategic agents (parallel)
- 20-30: Implementation agents (coordinated)
- 12-18: Quality agents (sequential)
Warnings:
-
30: Reduce parallelization
-
60: Critical - restart system
Execution Rules
✅ Safe: 4-5 strategic agents in parallel
✅ Safe: 2-3 implementation agents coordinated
❌ Unsafe: Quality agents in parallel (crashes system)
Best Practices
- Keep agents focused - One clear responsibility per agent
- Use descriptive descriptions - Enables auto-invocation
- Follow tool access patterns - Match tools to agent type
- Specify execution pattern - Prevents performance issues
- Leverage MCP tools - Enhance agent capabilities
- Test agents incrementally - Start simple, add complexity
- Version control agents - Check project agents into git
Limitations
- Agents are templates - customize for your specific needs
- Tool suggestions are guidelines, not requirements
- MCP tools require servers to be configured
- Performance depends on system resources
- Generated agents need testing in your environment
Installation
Generated Agent Files:
Place in one of these locations:
Project agents (shared with team):
.claude/agents/custom-agent.md
Personal agents (available everywhere):
~/.claude/agents/custom-agent.md
When to Use This Skill
Create custom agents for:
- Domain-specific workflows (data science, ML, finance)
- Team-specific conventions (your code style, testing approach)
- Specialized tools or frameworks (Shopify, AWS, Kubernetes)
- Custom MCP server integrations
- Rapid prototyping of agent ideas
Use the AGENTS_FACTORY_PROMPT.md template when:
- You need multiple related agents
- You want consistent agent patterns
- You're building an agentic framework
- You want to test agent concepts quickly
Version: 1.0.0
Last Updated: October 22, 2025
Compatibility: Claude Code (agents system)
Template Location: documentation/templates/AGENTS_FACTORY_PROMPT.md
