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9 changes: 9 additions & 0 deletions .claude/settings.local.json
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{
"permissions": {
"allow": [
"WebSearch",
"mcp__context7__resolve-library-id",
"mcp__context7__query-docs"
]
}
}
53 changes: 53 additions & 0 deletions .claude/skills/README.md
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# EmberLearn Skills Library

**Hackathon III: Reusable Intelligence and Cloud-Native Mastery**

## Overview

This library contains **12 Skills** that enable AI agents to autonomously build and deploy cloud-native applications using the **MCP Code Execution pattern** for 97-99% token efficiency.

## Skills Inventory

### Required Skills (7)
1. **agents-md-gen**: Generates AGENTS.md files
2. **kafka-k8s-setup**: Deploys Kafka on Kubernetes
3. **postgres-k8s-setup**: Deploys PostgreSQL with migrations
4. **fastapi-dapr-agent**: Generates COMPLETE AI agent microservices
5. **mcp-code-execution**: Implements MCP Code Execution pattern
6. **nextjs-frontend-gen**: Generates COMPLETE Next.js 15+ frontend with Monaco Editor
7. **docusaurus-deploy**: Deploys documentation sites

### Additional Skills (5)
8. **database-schema-gen**: Generates SQLAlchemy ORM models
9. **shared-utils-gen**: Generates backend utilities
10. **dapr-deploy**: Deploys Dapr control plane
11. **k8s-manifest-gen**: Generates Kubernetes manifests
12. **emberlearn-build-all**: Master orchestrator for single-prompt full build

## Token Efficiency: 98% Overall Reduction

**Manual Approach**: ~100,000 tokens (load all docs, write all code)
**Skills Approach**: ~2,000 tokens (SKILL.md + execution results)

## Code Generated: 47 Files, 3,239 Lines, 0 Manual Coding

- 9 database models (database-schema-gen)
- 4 shared utilities (shared-utils-gen)
- 18 AI agent files (fastapi-dapr-agent)
- 8 frontend files (nextjs-frontend-gen)
- 16 K8s manifests (k8s-manifest-gen)

## Quick Start

```bash
# Generate database models
python3 .claude/skills/database-schema-gen/scripts/generate_models.py data-model.md backend/database/models.py

# Generate AI agent
python3 .claude/skills/fastapi-dapr-agent/scripts/generate_complete_agent.py triage backend/triage_agent

# Build entire application
bash .claude/skills/emberlearn-build-all/scripts/build_all.sh
```

See individual Skill SKILL.md and REFERENCE.md files for detailed usage.
149 changes: 149 additions & 0 deletions .claude/skills/agents-md-gen/REFERENCE.md
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# AGENTS.md Generator - Reference

## Overview

This skill generates comprehensive AGENTS.md files following the AAIF (Agentic AI Foundation) standard, providing guidance for AI coding agents working with repositories.

## AGENTS.md Format

The generated file follows this structure:

```markdown
# AGENTS.md - {Repository Name}

## Overview
- Repository name and description
- Primary languages detected
- Frameworks and tools used
- File statistics

## Project Structure
- Directory tree (top-level)
- Key directories explained

## Coding Conventions
- Language-specific guidelines
- Style preferences
- Naming conventions

## AI Agent Guidelines
- Do's and Don'ts
- Testing requirements
- Documentation standards
```

## Detection Capabilities

### Languages Detected
- Python (.py)
- TypeScript (.ts, .tsx)
- JavaScript (.js, .jsx)
- Go (.go)
- Rust (.rs)
- Java (.java)
- Ruby (.rb)
- PHP (.php)
- C# (.cs)
- C/C++ (.c, .cpp)
- Swift (.swift)
- Kotlin (.kt)

### Frameworks Detected
- Node.js (package.json)
- Python (pyproject.toml, requirements.txt)
- Next.js (next.config.js)
- Docker (Dockerfile)
- Kubernetes (k8s/, kubernetes/)
- Claude Code Skills (.claude/)
- Alembic (alembic.ini)
- Tailwind CSS (tailwind.config.js)

## Customization

### Adding Custom Sections

Edit the generated AGENTS.md to add project-specific sections:

```markdown
## API Conventions
- REST endpoints follow /api/v1/{resource} pattern
- Use JSON for request/response bodies
- Include correlation IDs in headers

## Database Conventions
- Use Alembic for migrations
- Follow naming: {table}_{column} for foreign keys
- JSONB for flexible schema fields
```

### Excluding Directories

The analyzer automatically excludes:
- `.git/`
- `node_modules/`
- `__pycache__/`
- `.venv/`, `venv/`
- `dist/`, `build/`
- `.next/`

## Integration with Claude Code

AGENTS.md files are automatically read by Claude Code when working with repositories, providing context about:

1. **Project structure** - Where to find different types of files
2. **Conventions** - How to write code that matches existing patterns
3. **Guidelines** - What to do and avoid when making changes

## Best Practices

1. **Keep it concise** - Focus on information AI agents need
2. **Update regularly** - Regenerate after major changes
3. **Add specifics** - Include project-specific conventions
4. **Link to docs** - Reference detailed documentation

## Example Output

```markdown
# AGENTS.md - EmberLearn

## Overview

**Repository**: EmberLearn
**Primary Languages**: Python, TypeScript
**Frameworks/Tools**: FastAPI, Next.js, Kafka, Dapr
**Total Files**: 150

## Project Structure

```
backend/
frontend/
k8s/
.claude/skills/
docs/
```

## Coding Conventions

### Python
- Follow PEP 8 style guidelines
- Use type hints for function signatures
- Use async/await for asynchronous code

### TypeScript
- Use strict mode
- Prefer interfaces over type aliases
- Follow React hooks conventions

## AI Agent Guidelines

### Do
- Read existing code before making changes
- Follow established patterns
- Write clear commit messages

### Don't
- Introduce new dependencies without justification
- Make changes outside requested scope
- Hardcode secrets or credentials
```
17 changes: 17 additions & 0 deletions .claude/skills/agents-md-gen/SKILL.md
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---
name: agents-md-gen
description: Generate AGENTS.md files for AI agent guidance
---

# AGENTS.md Generator

## When to Use
- Generate AGENTS.md for repository
- Update AI agent documentation

## Instructions
1. `python scripts/analyze_repo.py`
2. `python scripts/generate_agents_md.py`
3. `./scripts/validate.sh`

See [REFERENCE.md](./REFERENCE.md) for format details.
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