# Agent Skill Architect MVP

## Vision

A tool that enables anyone to design production-ready AI agent architectures by visually selecting, composing, and validating skills from Skills Tree.

## Problem Statement

Building AI agents requires:
1. **Discovery** - Finding the right skills for your use case
2. **Composition** - Understanding how skills work together
3. **Validation** - Ensuring your architecture is production-ready
4. **Documentation** - Generating implementation specs

Today, these steps are manual, error-prone, and require deep expertise.

## MVP Solution

### Core Features

#### 1. Interactive Skill Selector
- **Input**: Use case description (e.g., "customer support bot", "code review agent")
- **Output**: Recommended skills across categories
- **UI**: Filterable tree view of all 361 skills
- **Validation**: Highlights battle-tested (51) vs. stub (308) skills

#### 2. Architecture Canvas
- **Drag & Drop**: Compose skills into agent workflows
- **Dependency Mapping**: Auto-detect skill dependencies
- **Risk Scoring**: Show which skills are production-ready
- **Export**: Generate JSON blueprint

#### 3. Blueprint Generator
- **Input**: Selected skills + architecture canvas
- **Output**: 
  - `agent-blueprint.json` - Machine-readable spec
  - `IMPLEMENTATION.md` - Human-readable guide
  - `dependencies.json` - Required packages/APIs
  - `test-suite.md` - Validation checklist

#### 4. Validation Engine
- Check for missing critical skills (e.g., error handling, monitoring)
- Flag stub skills that need production examples
- Suggest alternative battle-tested skills
- Calculate architecture maturity score (0-100)

## Technical Approach

### Phase 1: Static Site (Week 1-2)
- Build with Next.js/React
- Data source: `skills/**/*.json` + `meta/graph.json`
- Host on Vercel/GitHub Pages
- No backend required

### Phase 2: Enhanced UX (Week 3-4)
- Add visual canvas (e.g., React Flow)
- Implement drag-and-drop composition
- Real-time validation feedback
- Export to multiple formats

### Phase 3: Intelligence (Month 2)
- LLM-powered skill recommendations
- Auto-generate architectures from prompts
- Learn from community blueprints
- Integration with existing tools (LangChain, AutoGen, etc.)

## Success Metrics

1. **Adoption**: 100+ blueprints generated in first month
2. **Quality**: 80%+ of blueprints use battle-tested skills
3. **Contribution**: 20+ PRs to convert stubs → production skills
4. **Community**: Featured in 3+ AI engineering newsletters

## MVP Scope (Ship in 2 Weeks)

**IN SCOPE:**
- ✅ Browse all 361 skills with search/filter
- ✅ Select skills for your agent
- ✅ See skill dependencies and relationships
- ✅ Export as JSON blueprint
- ✅ Basic validation (missing critical skills)

**OUT OF SCOPE (v2):**
- ❌ Visual canvas editor
- ❌ LLM-powered recommendations
- ❌ User accounts / saved blueprints
- ❌ Collaboration features

## File Structure

```
meta/blueprints/
├── README.md              # How to use blueprints
├── template.json          # Blueprint schema
├── examples/
│   ├── customer-support-agent.json
│   ├── code-review-agent.json
│   ├── research-agent.json
│   └── data-analysis-agent.json
└── schemas/
    └── blueprint-v1.schema.json
```

## Next Steps

1. **Create `meta/blueprints/` directory** with examples (Action 3)
2. **Build MVP tool** in `tools/architect/` (T-05 from ROADMAP_V2)
3. **Document** in README.md under "Build with Skills Tree"
4. **Launch** on Product Hunt / Hacker News

## Alignment

- **T-04**: Strategic Identity (AI Engineering OS)
- **T-05**: Agent Skill Architect (this document)
- **Wave 0**: Foundation for product capabilities
- **80/20 Rule**: Pure product value, zero marketing fluff
