Skip to content

Repository files navigation

Agentic Engineering

Agentic Engineering Logo

12 specialized AI agents + 3 configurable skills for software development.

Works with Claude Code and OpenCode. Based on Jungian cognitive functions for optimal team dynamics.

License: Unlicense Claude Code OpenCode


🧠 The Philosophy: The Worker-Governance Pattern

Agentic Pattern: The Worker-Governance Pattern

"Equal Halves make the whole, neither side takes control."

This agent system is built on Carl Jung's cognitive functions to create a psychologically balanced team:

πŸ”§ WORKER AGENTS (6)

Cognitive Function: Sensing

  • πŸ”΅ Practical Execution
  • πŸ”΅ Detail-Oriented
  • πŸ”΅ Present-Focused
  • πŸ”΅ Implementation

Role: Build features, fix bugs, execute tasks

πŸ›οΈ GOVERNANCE AGENTS (6)

Cognitive Functions: Mixed

  • πŸ’œ Strategic Direction (Intuition)
  • πŸ”΄ Quality Validation (Thinking)
  • 🩷 User Empathy (Feeling)

Role: Guide vision, ensure quality, validate work

The Balance:

6 Workers (Sensing)    +    6 Governance (Intuition + Thinking + Feeling)    =    12 Agents
   βš™οΈ Execution               🎯 Direction & Quality                            🎯 Complete Team

This balance ensures:

  • βœ… Vision without losing touch with reality
  • βœ… Quality without perfectionism paralysis
  • βœ… Execution with strategic direction
  • βœ… Empathy balanced with objectivity
  • βœ… Neither side dominates - equal collaboration

πŸ“– See TEAM_ARCHITECTURE.md for detailed team dynamics and collaboration patterns


Screenshot 2025-11-22 at 9 13 09β€―PM

🎯 The Pattern in Action

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚                                                                         β”‚
β”‚     WORKERS (6)                 BALANCE                GOVERNANCE (6)   β”‚
β”‚  ═══════════════                                         ═══════════════│
β”‚                                                                         β”‚
β”‚  πŸ”΅ Backend Specialist       ←─────────────→       πŸ’œ System Architect   β”‚
β”‚  🟒 Frontend Specialist      ←─────────────→       🩷 UX Designer        β”‚
β”‚  🟀 Database Designer        ←─────────────→       🩡 Product Owner      β”‚
β”‚  🩡 DevOps Engineer          ←─────────────→       πŸ”΄ Code Reviewer      β”‚
β”‚  🟣 Full-Stack Developer     ←─────────────→       πŸ”΄ Security Auditor   β”‚
β”‚  🟠 Debugger                 ←─────────────→       🟑 Test Writer        β”‚
β”‚                                                                         β”‚
β”‚            EXECUTION                                    DIRECTION       β”‚
β”‚            Implementation                               Validation      β”‚
β”‚            Practical                                    Strategic       β”‚
β”‚                                                                         β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

Neither side takes control. Equal halves make the whole.


πŸš€ Quick Start

One-Line Install

curl -sSL https://raw.githubusercontent.com/ciign/agentic-engineering/main/setup-agents.sh | bash

The script will:

  • πŸ€– Ask you to choose: Claude Code or OpenCode
  • πŸ“ Ask for installation location: Project or Global
  • βœ… Create all 12 agents with the correct format for your tool
  • βœ… Create 3 skills (/react, /docker, /python) with per-skill config templates
  • βœ… Back up any existing agent configuration

Manual Installation

# Clone the repository
git clone https://github.com/ciign/agentic-engineering.git
cd agentic-engineering

# Run the setup script
./setup-agents.sh

# Start your AI coding tool
claude    # for Claude Code
opencode  # for OpenCode

πŸ‘₯ The Team: 6 + 6 Balance

πŸ”§ Worker Agents (Sensing - Execution)

These agents build features through practical, detail-oriented implementation:

Agent Color Focus Cognitive Function
backend-specialist πŸ”΅ Blue Server-side APIs, databases, performance Sensing
frontend-specialist 🟒 Green UI implementation, accessibility, client-side Sensing
database-designer 🟀 Brown Schema design, query optimization, data modeling Sensing
devops-engineer 🩡 Cyan CI/CD, infrastructure, deployment, monitoring Sensing
full-stack-developer 🟣 Purple End-to-end features across all layers Sensing
debugger 🟠 Orange Bug diagnosis, root cause analysis, fixes Sensing

πŸ›οΈ Governance Agents (Direction & Quality)

These agents guide and validate work:

Vision & Strategy (Intuition)

Agent Color Focus Cognitive Function
product-owner 🩡 Teal Requirements, priorities, business value Intuition + Feeling
system-architect πŸ’œ Magenta Technical architecture, patterns, scalability Intuition

Quality Assurance (Thinking)

Agent Color Focus Cognitive Function
code-reviewer πŸ”΄ Red Code quality, maintainability, standards Thinking
security-auditor πŸ”΄ Red Vulnerabilities, compliance, security Thinking
test-writer 🟑 Yellow Testing strategy, coverage, validation Thinking

User Empathy (Feeling)

Agent Color Focus Cognitive Function
ux-designer 🩷 Pink User research, accessibility, experience Feeling

⚑ Skills (Slash Commands)

Skills are project-aware slash commands that know your specific setup. Each skill reads a config.md file with your project's paths, tools, and conventions.

Available Skills

Skill Invocation Description
React /react [command] React/Next.js development β€” components, hooks, dev server, builds
Docker /docker [command] Docker operations β€” build, run, compose, logs, cleanup
Python /python [command] Python development β€” uv, pipenv, pip, pytest, frameworks

Per-Skill Configuration

Each skill has a config.md template you edit to match your project:

skills/
β”œβ”€β”€ react/
β”‚   β”œβ”€β”€ SKILL.md        # Skill instructions (don't edit)
β”‚   └── config.md       # YOUR project config (edit this)
β”œβ”€β”€ docker/
β”‚   β”œβ”€β”€ SKILL.md
β”‚   └── config.md       # Your Dockerfiles, services, ports
└── python/
    β”œβ”€β”€ SKILL.md
    └── config.md       # Your framework, package manager, commands

Example β€” docker/config.md:

## Dockerfiles
- Primary: `./Dockerfile`
- Dev: `./Dockerfile.dev`

## Services
| Service | Port | Description |
|---------|------|-------------|
| app     | 3000 | Main application |
| db      | 5432 | PostgreSQL database |

## Common Commands
- Start dev: `docker compose -f docker-compose.yml -f docker-compose.dev.yml up -d`
- Rebuild: `docker compose build --no-cache app`

Example β€” python/config.md:

## Project
- Package manager: `uv`   <!-- uv, pipenv, pip, poetry, pdm -->
- Framework: `FastAPI`

## Commands
- Run: `uv run uvicorn src.main:app --reload`
- Test: `uv run pytest -v`
- Add dependency: `uv add <package>`

The Python skill supports uv (default), pipenv, and pip. Change the Package manager line in config.md and the skill adapts.

Skill Usage Examples

# React
/react component UserProfile    # Generate a TypeScript component
/react dev                      # Start dev server
/react hook useAuth             # Create a custom hook

# Docker
/docker up                      # Start services (uses your compose config)
/docker build myapp:latest      # Build image
/docker logs app                # View logs for your app service
/docker init node               # Generate a Dockerfile for Node.js

# Python
/python init                    # Scaffold project with pyproject.toml
/python test                    # Run tests
/python fastapi                 # Generate FastAPI project structure
/python uv add requests         # Add a dependency with uv

πŸ’‘ How to Use the Agents

Understanding Agent Types & Agent Philosophy

Screenshot 2025-11-22 at 9 13 09β€―PM

Worker Agents β†’ Execute tasks, build features, fix bugs

@backend-specialist implement user authentication API
@frontend-specialist create a responsive dashboard
@debugger fix this race condition

Governance Agents β†’ Define direction, ensure quality, validate work

@product-owner what features should we prioritize for MVP?
@system-architect should we use microservices or monolith?
@code-reviewer review this authentication implementation
@ux-designer is this checkout flow intuitive?

Complete Workflow Examples

πŸ†• Building a New Feature

# 1. Define what to build (Vision)
@product-owner I want to add real-time notifications
# β†’ Defines requirements, user stories, acceptance criteria

# 2. Design the experience (Empathy)
@ux-designer design the notification UI/UX
# β†’ Creates user flows, interaction patterns

# 3. Design the architecture (Vision)
@system-architect design the real-time notification system
# β†’ Defines technical approach (WebSockets, polling, etc.)

# 4. Build it (Execution)
@backend-specialist implement WebSocket notification service
@frontend-specialist implement notification UI components
# β†’ Worker agents build the feature

# 5. Validate quality (Quality)
@code-reviewer review the notification implementation
@security-auditor check for security issues
@test-writer add comprehensive tests
# β†’ Governance agents ensure quality

πŸ› Debugging & Fixing Issues

# 1. Diagnose and fix (Execution)
@debugger users report intermittent login failures
# β†’ Investigates, identifies root cause, implements fix

# 2. Validate the fix (Quality)
@test-writer add regression tests for the login fix
@code-reviewer review the debugging fix
# β†’ Ensures fix is correct and won't regress

πŸ—οΈ Starting a New Project

# 1. Define vision and requirements (Vision + Empathy)
@product-owner define MVP scope for task management app
@ux-designer research task management user needs

# 2. Design architecture (Vision)
@system-architect design scalable architecture for task app
@database-designer design data model for tasks and users

# 3. Scaffold with skills
/python init                           # Scaffold Python project with uv
/python fastapi                        # Generate FastAPI structure
/react init vite                       # Init React frontend with Vite

# 4. Execute implementation (Execution)
@full-stack-developer implement core task CRUD features
@devops-engineer set up CI/CD pipeline

# 5. Containerize and deploy
/docker init node                      # Generate production Dockerfile
/docker up                             # Start services locally

# 6. Ensure quality (Quality)
@security-auditor review authentication and authorization
@test-writer create comprehensive test suite
@code-reviewer final review before deployment

πŸš€ Deploying to Production

# 1. Prepare infrastructure (Execution)
@devops-engineer set up production infrastructure on AWS
/docker build myapp:prod               # Build production image

# 2. Security audit (Quality)
@security-auditor perform pre-deployment security review

# 3. Architecture validation (Vision)
@system-architect review production architecture for scalability

# 4. Final checks
@code-reviewer verify deployment configuration

Agent + Skills Collaboration Patterns

Product Development Flow:

product-owner β†’ ux-designer β†’ system-architect β†’ skills + workers β†’ governance agents
(what to build) (how users use it) (how to build it) (scaffold & build) (validate it)

Build with Skills:

/python init β†’ @backend-specialist β†’ /docker init β†’ @devops-engineer β†’ @code-reviewer
(scaffold)    (implement logic)      (containerize)  (deploy)           (validate)

Quality Assurance:

worker agents β†’ code-reviewer β†’ security-auditor β†’ test-writer
(submit work)   (code quality)   (security)       (testing)

πŸ“ Project Structure

After running the setup script:

Claude Code:

your-project/
β”œβ”€β”€ .claude/
β”‚   β”œβ”€β”€ agents/
β”‚   β”‚   β”œβ”€β”€ backend-specialist.md
β”‚   β”‚   β”œβ”€β”€ frontend-specialist.md
β”‚   β”‚   β”œβ”€β”€ database-designer.md
β”‚   β”‚   β”œβ”€β”€ devops-engineer.md
β”‚   β”‚   β”œβ”€β”€ full-stack-developer.md
β”‚   β”‚   β”œβ”€β”€ debugger.md
β”‚   β”‚   β”œβ”€β”€ product-owner.md
β”‚   β”‚   β”œβ”€β”€ ux-designer.md
β”‚   β”‚   β”œβ”€β”€ system-architect.md
β”‚   β”‚   β”œβ”€β”€ code-reviewer.md
β”‚   β”‚   β”œβ”€β”€ security-auditor.md
β”‚   β”‚   └── test-writer.md
β”‚   └── skills/
β”‚       β”œβ”€β”€ react/
β”‚       β”‚   β”œβ”€β”€ SKILL.md
β”‚       β”‚   └── config.md        ← edit this for your project
β”‚       β”œβ”€β”€ docker/
β”‚       β”‚   β”œβ”€β”€ SKILL.md
β”‚       β”‚   └── config.md        ← edit this for your project
β”‚       └── python/
β”‚           β”œβ”€β”€ SKILL.md
β”‚           └── config.md        ← edit this for your project
└── [your project files]

OpenCode:

your-project/
β”œβ”€β”€ .opencode/
β”‚   β”œβ”€β”€ agents/
β”‚   β”‚   └── [same 12 agents with OpenCode format]
β”‚   └── skills/
β”‚       β”œβ”€β”€ react/
β”‚       β”‚   β”œβ”€β”€ SKILL.md
β”‚       β”‚   └── config.md        ← edit this for your project
β”‚       β”œβ”€β”€ docker/
β”‚       β”‚   β”œβ”€β”€ SKILL.md
β”‚       β”‚   └── config.md        ← edit this for your project
β”‚       └── python/
β”‚           β”œβ”€β”€ SKILL.md
β”‚           └── config.md        ← edit this for your project
└── [your project files]

🎯 When to Use What

"What should we build?"

  • @product-owner - Requirements, priorities, business value
  • @ux-designer - User needs, experience design

"How should we structure it?"

  • @system-architect - Architecture, patterns, scalability
  • @database-designer - Data models, schema design

"Scaffold & set up"

  • /python init - Scaffold Python project (uv, FastAPI, Django, Flask)
  • /react init - Scaffold React/Next.js project
  • /docker init - Generate Dockerfile for any language

"Build the feature"

  • @backend-specialist - APIs, business logic, server-side
  • @frontend-specialist - UI, components, client-side
  • @full-stack-developer - Complete features end-to-end
  • @database-designer - Schemas, queries, migrations
  • @devops-engineer - Infrastructure, deployment
  • /react component Name - Generate React components
  • /python uv add package - Manage Python dependencies

"Run & deploy"

  • /docker up - Start services
  • /docker build - Build images
  • @devops-engineer - CI/CD, cloud deployment

"Fix the bug"

  • @debugger - Diagnose and fix issues
  • /docker logs - Check container logs

"Is it good quality?"

  • @code-reviewer - Code quality, maintainability
  • @security-auditor - Security vulnerabilities
  • @test-writer - Test coverage, validation
  • @ux-designer - Usability, accessibility

πŸŽ“ Agent Capabilities Deep Dive

Worker Agents (Sensing)

Each worker agent embodies practical, detail-oriented execution:

backend-specialist

  • API design (REST, GraphQL, gRPC, WebSockets)
  • Database optimization and query tuning
  • Authentication, authorization, session management
  • Caching strategies, message queues
  • Performance profiling and optimization

frontend-specialist

  • Modern frameworks (React, Vue, Angular, Svelte)
  • Responsive design, mobile-first approach
  • Accessibility (WCAG AA/AAA compliance)
  • Performance optimization (lazy loading, code splitting)
  • State management patterns

database-designer

  • Schema design and normalization
  • Index optimization strategies
  • Query performance tuning
  • Migration planning (zero-downtime)
  • Scaling strategies (sharding, partitioning)

devops-engineer

  • CI/CD pipelines (GitHub Actions, GitLab CI)
  • Infrastructure as Code (Terraform, CloudFormation)
  • Container orchestration (Docker, Kubernetes)
  • Monitoring and observability (Prometheus, Grafana)
  • Security best practices for infrastructure

full-stack-developer

  • End-to-end feature implementation
  • Cross-layer integration (UI β†’ API β†’ DB)
  • Holistic problem-solving
  • Full ownership of features

debugger

  • Systematic debugging methodology
  • Root cause analysis
  • Performance profiling
  • Log analysis and tracing
  • Bug prevention strategies

Governance Agents

product-owner (Intuition + Feeling)

  • Product vision and strategy
  • Requirements gathering (user stories, acceptance criteria)
  • Backlog prioritization (RICE, MoSCoW, Value/Effort)
  • Stakeholder alignment
  • Metrics and OKRs

ux-designer (Feeling)

  • User research and personas
  • Information architecture
  • Interaction design and prototyping
  • Accessibility and inclusive design
  • Usability testing

system-architect (Intuition)

  • Scalable system design
  • Architectural patterns (microservices, event-driven, etc.)
  • Technology selection and tradeoffs
  • Performance and reliability planning
  • Architectural Decision Records (ADRs)

code-reviewer (Thinking)

  • Code correctness and logic
  • Security vulnerability detection
  • Performance analysis
  • Maintainability assessment
  • Constructive feedback

security-auditor (Thinking)

  • OWASP Top 10 vulnerability detection
  • Threat modeling
  • Security best practices (authentication, encryption, etc.)
  • Compliance (GDPR, SOC2, HIPAA)
  • Penetration testing mindset

test-writer (Thinking)

  • Test strategy (unit, integration, E2E)
  • Test-driven development (TDD)
  • Coverage analysis
  • Test maintainability
  • Continuous testing practices

πŸ› οΈ Requirements

πŸ“– Additional Resources

πŸ“š Interactive Learning Deck

Learn the Agentic Engineering approach with our interactive presentation:

cd learn
npm install
npm run dev

The deck covers:

  • The Worker-Governance Pattern
  • All 12 agents and their roles
  • Step-by-step workflow examples
  • Live code demonstrations

Navigate with arrow keys or click the dots to jump between slides.

🎨 Design Philosophy

This agent system is designed around psychological balance:

  1. Sensing (6 workers) β†’ Practical execution, present-focused, detail-oriented
  2. Intuition (2 governance) β†’ Vision, patterns, future-oriented, strategic
  3. Thinking (3 governance) β†’ Logical analysis, objective validation, standards
  4. Feeling (1 governance) β†’ Empathy, values, user needs, human-centered

This creates:

  • Balance between vision and execution
  • Balance between quality and velocity
  • Balance between user needs and technical constraints
  • Balance between innovation and stability

🀝 Contributing

Contributions are welcome! When proposing new agents, consider:

  1. Team balance - Would this agent maintain the 6/6 worker/governance balance?
  2. Cognitive function - What Jungian function does it embody?
  3. Unique value - What unique expertise does it provide?
  4. Collaboration - How does it work with existing agents?

How to Contribute

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/new-capability)
  3. Update agents in .claude-template/agents/
  4. Test thoroughly
  5. Update documentation (README, TEAM_ARCHITECTURE.md)
  6. Submit a Pull Request

Ideas for Enhancements

  • New skills β€” Terraform, Kubernetes, AWS CLI, database migrations
  • Industry-specific agents (FinTech, Healthcare, E-commerce)
  • Language-specific specialists (Go, Rust, TypeScript, Java)
  • Platform-specific agents (Mobile, Desktop, Embedded)
  • Advanced capabilities (AI/ML, Data Engineering, Performance Optimization)

πŸ“„ License

This project is released into the public domain under The Unlicense.

You can:

  • βœ… Use commercially
  • βœ… Modify freely
  • βœ… Distribute
  • βœ… Use privately
  • ❌ No attribution required
  • ❌ No warranty provided

See the LICENSE file for details or visit unlicense.org.

πŸ™ Acknowledgments

  • Built for use with Claude Code and OpenCode
  • Based on Carl Jung's theory of cognitive functions
  • Inspired by best practices from high-performing software teams
  • Community contributions and feedback

πŸ“ž Support

🌟 Star History

If you find this useful, please give it a star! ⭐

Stars help others discover this project and motivate continued development.


Made with ❀️ for the developer community

Experience the power of a psychologically-balanced AI engineering team! πŸš€

About

Setting up your SDLC using agentic engineering

Resources

Stars

25 stars

Watchers

2 watching

Forks

Releases

Packages

Contributors

Languages