A curated collection of specialized AI agent templates for Claude MPM - the multi-agent orchestration framework for Claude Code.
Key Features:
- 🏗️ BASE-AGENT.md Inheritance System - Convention-based template inheritance eliminates duplication
- 📦 Hierarchical Organization - Agents organized by functional relationships (engineer, qa, ops, etc.)
- 🤖 Auto-Deployment - Intelligent agent selection based on project type detection
- 🔍 Agent Discovery - Cache scanning with semantic matching for recommendations
- ⚡ 57% Less Duplication - Shared instructions managed in one place
This repository contains production-ready agent templates in Markdown format with YAML frontmatter. Each agent is designed for specific engineering, operations, or quality assurance tasks within the Claude MPM framework.
The repository uses a hierarchical organization with BASE-AGENT.md inheritance to eliminate duplication and maintain consistency across related agents. When building an agent, content from BASE-AGENT.md files at each directory level is automatically combined, allowing shared instructions to be defined once and inherited by all agents in that category.
claude-mpm-agents/
├── agents/ # Deployable agent templates
│ ├── BASE-AGENT.md # Universal instructions (ALL agents inherit)
│ │
│ ├── claude-mpm/ # Claude MPM framework agents
│ │ ├── BASE-AGENT.md # MPM framework awareness
│ │ └── mpm-agent-manager.md # Agent discovery & deployment
│ │
│ ├── universal/ # Cross-cutting concerns
│ │ ├── memory-manager.md
│ │ ├── research.md
│ │ └── ...
│ │
│ ├── engineer/ # Implementation specialists
│ │ ├── BASE-AGENT.md # Shared engineering principles
│ │ ├── core/
│ │ │ └── engineer.md
│ │ ├── frontend/
│ │ │ ├── react-engineer.md
│ │ │ ├── nextjs-engineer.md
│ │ │ └── ...
│ │ ├── backend/
│ │ │ ├── python-engineer.md
│ │ │ ├── golang-engineer.md
│ │ │ └── ...
│ │ └── ...
│ │
│ ├── qa/ # Quality assurance
│ │ ├── BASE-AGENT.md # Shared QA standards
│ │ ├── qa.md
│ │ ├── api-qa.md
│ │ └── web-qa.md
│ │
│ └── ops/ # Operations & deployment
│ ├── BASE-AGENT.md # Shared ops protocols
│ ├── core/
│ │ └── ops.md
│ ├── platform/
│ │ ├── vercel-ops.md
│ │ └── ...
│ └── ...
│
├── templates/ # Reference materials (NOT agents)
│ ├── circuit-breakers.md # PM violation patterns
│ ├── pm-examples.md # PM behavior examples
│ ├── validation-templates.md # Verification templates
│ └── ...
│
├── build-agent.py # Build script for flattening agents
└── AUTO-DEPLOY-INDEX.md # Project type detection rules
This repository uses a convention-based inheritance system to reduce duplication and maintain consistency.
When building an agent, content is combined in this order:
- Agent-specific content (
{agent-name}.md) - Unique instructions for this agent - Directory BASE-AGENT.md (if exists) - Shared instructions for agents in this directory
- Parent BASE-AGENT.md files (recursive) - Instructions from parent directories
- Root BASE-AGENT.md (always) - Universal instructions for ALL agents
Example: For agents/engineer/backend/python-engineer.md:
python-engineer.md
+ agents/engineer/backend/BASE-AGENT.md (if exists)
+ agents/engineer/BASE-AGENT.md
+ agents/BASE-AGENT.md
Universal instructions for ALL agents:
- Git workflow standards
- Memory routing protocols
- Output format standards
- Handoff protocols
- Quality standards
Shared instructions for all agents in a category:
- Engineer: SOLID principles, code reduction, type safety, testing requirements
- QA: Testing strategies, coverage standards, memory-efficient testing
- Ops: Deployment verification, security scanning, monitoring requirements
Specific instructions for subcategories (optional, as needed)
Agents in this repository are modular (source files) and must be flattened before use:
# Build a single agent
./build-agent.py agents/engineer/backend/python-engineer.md
# Build all agents
./build-agent.py --all
# Build to specific output directory
./build-agent.py --all --output-dir dist/agents
# Validate all agent definitions
./build-agent.py --validateBuilt agents are placed in dist/agents/ with the full inheritance chain combined.
Benefits:
- âś… DRY (Don't Repeat Yourself): Common instructions defined once
- âś… Consistency: All agents in a category follow same standards
- âś… Maintainability: Update shared instructions in one place
- âś… Modularity: Agent-specific content stays focused
- âś… Flexibility: Add BASE-AGENT.md at any level as needed
Example: All engineering agents inherit:
- Root: Git workflows, output standards (200 lines)
- Engineer: SOLID principles, code reduction (300 lines)
- Agent: Python-specific patterns (150 lines)
Total: 650 lines, but only 150 lines are Python-specific!
Framework-level agents with MPM-specific awareness:
- mpm-agent-manager - Agent discovery, cache scanning, intelligent recommendations, and deployment orchestration
Cross-cutting concerns that apply to multiple domains:
- memory-manager - Project-specific memory management
- product-owner - Product strategy and prioritization
- project-organizer - Project organization and workflow
- research - Codebase investigation and analysis
- code-analyzer - Code review and pattern identification
- content-agent - Content optimization and SEO
- engineer - General-purpose software engineering
- web-ui - Generic web UI development
- react-engineer - React with hooks and modern patterns
- nextjs-engineer - Next.js App Router and Server Components
- svelte-engineer - Svelte 5 with Runes and SvelteKit
- python-engineer - Python 3.12+ with type safety and async
- golang-engineer - Go with concurrency patterns
- phoenix-engineer - Elixir/Phoenix with LiveView, Ecto, and OTP foundations
- java-engineer - Java/Spring Boot with hexagonal architecture
- ruby-engineer - Ruby/Rails with service objects
- rust-engineer - Rust with ownership and safety
- php-engineer - PHP/Laravel with strict types
- javascript-engineer - Node.js/Express backend
- dart-engineer - Dart/Flutter with clean architecture
- tauri-engineer - Tauri desktop applications
- data-engineer - Data pipelines and ETL
- typescript-engineer - TypeScript 5.6+ with branded types
- refactoring-engineer - Safe code refactoring
- agentic-coder-optimizer - Build system optimization
- imagemagick - Image optimization specialist
- prompt-engineer - Prompt optimization for Claude 4.5
- qa - General quality assurance
- api-qa - API testing and validation
- web-qa - Web application testing with Playwright
- ops - General DevOps and infrastructure
- vercel-ops - Vercel deployment
- gcp-ops - Google Cloud Platform
- clerk-ops - Clerk authentication
- local-ops - Local development with PM2/Docker
- version-control - Git operations and release coordination
- security - Security analysis and vulnerability assessment
- documentation - Technical documentation and API docs
- ticketing - Ticket management and tracking
Each agent template uses Markdown with YAML frontmatter:
---
name: agent-name
description: Agent purpose and capabilities
agent_id: unique-identifier
agent_type: engineer|qa|ops|universal|documentation
model: sonnet|opus|haiku
version: 2.0.0
tags:
- technology
- domain
category: engineering|qa|ops|research
---
# Agent Name
Agent-specific instructions...
<!-- BASE-AGENT.md content automatically appended during build -->These templates are designed to be used with Claude MPM:
-
Build agents (flattened with inheritance):
./build-agent.py --all --output-dir ~/.claude-mpm/agents -
Deploy agents via Claude MPM CLI:
claude-mpm agents deploy <agent-name>
-
Use in Claude Code via delegation:
PM delegates to engineer agent for implementation tasks
- Fork this repository
- Modify BASE-AGENT.md files for project standards
- Add custom agents as needed
- Build and deploy to your Claude MPM instance
- Edit agent files in
agents/directory - Rebuild with
./build-agent.py --all - Deploy updated agents
All templates follow the Claude MPM Agent Template Schema v1.3.0:
- Metadata: Name, version, description, tags, category
- Configuration: Model selection, resource limits, timeouts
- Capabilities: Memory limits, CPU allocation, network access
- Dependencies: Python packages, system requirements
- Skills: Reusable skill references
- Knowledge: Domain expertise, best practices, constraints
- Interactions: Input/output formats, handoff patterns
- Memory Routing: Memory categorization and keywords
# Install Python 3.9+ (no additional dependencies required)
# Build single agent
./build-agent.py agents/engineer/backend/python-engineer.md
# Build all agents
./build-agent.py --all
# Validate all agents
./build-agent.py --validate
# Custom output directory
./build-agent.py --all --output-dir ~/my-agents- Determine category: universal, engineer, qa, ops, etc.
- Create agent file:
agents/{category}/{subcategory}/{agent-name}.md - Add YAML frontmatter: name, description, agent_id, etc.
- Write agent-specific content: Focus on unique instructions
- Build and validate:
./build-agent.py --validate
When updating shared instructions:
-
Edit appropriate BASE-AGENT.md:
- Root level: Universal changes
- Category level: Category-wide changes
- Subcategory level: Specific subcategory changes
-
Rebuild all affected agents:
./build-agent.py --all
-
Validate changes:
./build-agent.py --validate
See CHANGELOG.md for detailed version history.
See CONTRIBUTING.md for development guidelines.
Part of the Claude MPM project. See main repository for license details.
- Claude MPM: https://github.com/bobmatnyc/claude-mpm
- Documentation: https://docs.claude.com/en/docs/claude-code
- Community: Claude MPM GitHub Discussions
Repository Structure: Agent templates with BASE-AGENT.md inheritance for consistency and maintainability.