Agentic Code

Your AI (LLM), guided by built-in workflows. Just tell it what you want.

AI builds a Slack bot with tests & docs — in 30s

What You Get

You: "Build a Slack bot with Gemini API"
AI:  ✓ Reads AGENTS.md
     ✓ Analyzes requirements
     ✓ Plans architecture
     ✓ Writes tests first (NEW in v0.2)
     ✓ Implements with best practices
     ✓ Verifies everything works

No configuration. No learning curve. Just results.

Claude Code users building TypeScript? Prefer a Claude-first stack with advanced sub-agents and rules: AI Coding Project Boilerplate.

Quick Start (30 seconds)

npx github:shinpr/agentic-code my-project && cd my-project
# 🚀 Ready. Just tell it what to build.

That's it. Works with any AI tool - Codex, Cursor, Aider, GitHub Copilot, or anything AGENTS.md compatible.

Why This Exists

Every AI coding tool has the same problems:

• Forgets your project structure after 10 messages
• Deletes tests when adding features
• Ignores architectural decisions
• Skips quality checks

We built the solution into the framework. AGENTS.md guides your AI through professional workflows automatically.

What Makes It Different

🎯 Zero Configuration

Pre-built workflows. No setup needed.

🌐 Universal Compatibility

Any programming language. Any AI tool that reads AGENTS.md.

✅ Test-First by Default (NEW in v0.2)

Generates test skeletons before code.

📈 Smart Scaling

• Simple task → Direct execution
• Complex feature → Full workflow with approvals

How It Actually Works

1. AGENTS.md tells your AI the process - Like a README but for AI agents
2. Progressive rule loading - Only loads what's needed, when needed
3. Quality gates - Automatic checkpoints ensure consistent output
4. You stay in control - Approval points for major decisions

.agents/
├── tasks/                    # What to build
│   ├── task-analysis.md     # Entry point - AI starts here
│   └── ...                  # Design, test, implement, QA tasks
├── workflows/               # How to build it
└── rules/                   # Quality standards

Real Examples

Simple Task

You: "Add API endpoint for user search"
# AI: Reads existing code → Plans changes → Tests → Implements → Done

Complex Feature

You: "Build user authentication system"
# AI: Requirements → Design doc → Your approval → Test skeletons →
#     Implementation → Quality checks → Done

Installation Options

For New Projects

# General purpose (any language)
npx github:shinpr/agentic-code my-project

# With TypeScript optimizations
npx github:shinpr/agentic-code my-project --lang=typescript

For Existing Projects

# Copy the framework files
cp -r path/to/agentic-code/AGENTS.md .
cp -r path/to/agentic-code/.agents .

# Set up language rules (choose one)
cd .agents/rules/language
ln -s general/rules.md rules.md
ln -s general/testing.md testing.md

Common Questions

Q: Do I need to learn a new syntax? Nope. Just describe what you want in plain language. The framework handles the rest.

Q: What if my AI doesn't support AGENTS.md? Check if your tool is AGENTS.md compatible. If yes, just tell it to read the AGENTS.md file first.

Q: Can I customize the workflows? Absolutely! Everything in .agents/ is customizable. But honestly, the defaults work great.

Q: What about my existing codebase? Works perfectly. Your AI analyzes the code and follows your existing patterns.

The Technical Stuff

The framework has three pillars:

1. Tasks - Define WHAT to build
2. Workflows - Define HOW to build it
3. Rules - Define quality STANDARDS

Advanced features for the curious...

Progressive Rule Loading

Rules load based on task analysis:

• Small (1-2 files) → Direct execution with minimal rules
• Medium/Large (3+ files) → Structured workflow with design docs
• Each task definition specifies its required rules

Quality Gates

Automatic checkpoints ensure:

• Tests pass before proceeding
• Code meets standards
• Documentation stays updated

Special Features

• Metacognition - AI self-assessment and error recovery
• Plan Injection - Enforces all required steps are in work plan
• Test Generation - Test skeletons from acceptance criteria
• 1-Commit Principle - Each task = one atomic commit

Start Building

npx github:shinpr/agentic-code my-awesome-project
cd my-awesome-project
# Tell your AI what to build

No more chaotic AI coding sessions. Just reliable, professional development.

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Contributing

Found a bug? Want to add language-specific rules? PRs welcome!

• 🐛 Report issues
• 🔧 Submit PRs
• 📚 Improve docs

License

MIT - Use it however you want.

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Built on the AGENTS.md standard — an open community specification for AI coding agents.

Ready to code properly with AI? npx github:shinpr/agentic-code my-project