Example project-specific skill template based on a real production application — use as a starting point for your own project skills.
Scanned 6/4/2026
Install via CLI
openskills install lidge-jun/cli-jaw-skills---
name: project-guidelines-example
description: Example project-specific skill template based on a real production application — use as a starting point for your own project skills.
---
# Project Guidelines (Example Template)
Template for creating project-specific skills. Adapt the sections below to your own project.
Based on a real production application: [Zenith](https://zenith.chat) — AI-powered customer discovery platform.
## When to Use
Reference a project skill when working on its specific project. A project skill typically contains:
- Architecture overview and file structure
- Code patterns and conventions
- Testing requirements
- Deployment workflow
---
## Architecture Overview
**Tech Stack:**
- **Frontend**: Next.js 15 (App Router), TypeScript, React
- **Backend**: FastAPI (Python), Pydantic models
- **Database**: Supabase (PostgreSQL)
- **AI**: Claude API with tool calling and structured output
- **Deployment**: Google Cloud Run
- **Testing**: Playwright (E2E), pytest (backend), React Testing Library
**Services:**
```
Frontend (Next.js 15 + TypeScript + TailwindCSS)
│
▼
Backend (FastAPI + Python 3.11 + Pydantic)
│
├── Supabase (Database)
├── Claude API
└── Redis (Cache)
```
---
## File Structure
```
project/
├── frontend/src/
│ ├── app/ # Next.js app router pages
│ ├── components/ # React components (ui/, forms/, layouts/)
│ ├── hooks/ # Custom React hooks
│ ├── lib/ # Utilities
│ ├── types/ # TypeScript definitions
│ └── config/ # Configuration
│
├── backend/
│ ├── routers/ # FastAPI route handlers
│ ├── models.py # Pydantic models
│ ├── main.py # FastAPI app entry
│ ├── services/ # Business logic
│ └── tests/ # pytest tests
│
├── deploy/ # Deployment configs
└── scripts/ # Utility scripts
```
---
## Code Patterns
### API Response Format (FastAPI)
```python
class ApiResponse(BaseModel, Generic[T]):
success: bool
data: Optional[T] = None
error: Optional[str] = None
@classmethod
def ok(cls, data: T) -> "ApiResponse[T]":
return cls(success=True, data=data)
@classmethod
def fail(cls, error: str) -> "ApiResponse[T]":
return cls(success=False, error=error)
```
### Frontend API Calls (TypeScript)
```typescript
async function fetchApi<T>(
endpoint: string,
options?: RequestInit
): Promise<ApiResponse<T>> {
const response = await fetch(`/api${endpoint}`, {
...options,
headers: { 'Content-Type': 'application/json', ...options?.headers },
})
if (!response.ok) return { success: false, error: `HTTP ${response.status}` }
return await response.json()
}
```
---
## Testing Requirements
### Backend (pytest)
```bash
pytest tests/ # all tests
pytest tests/ --cov=. --cov-report=html # with coverage
pytest tests/test_auth.py -v # specific file
```
### Frontend
```bash
npm run test # unit tests
npm run test -- --coverage # with coverage
npm run test:e2e # Playwright E2E
```
---
## Deployment
### Pre-Deployment Checklist
- [ ] All tests passing locally
- [ ] Build succeeds (frontend + backend)
- [ ] No hardcoded secrets
- [ ] Environment variables documented
- [ ] Database migrations ready
### Deploy Commands
```bash
cd frontend && npm run build && gcloud run deploy frontend --source .
cd backend && gcloud run deploy backend --source .
```
---
## Project Rules
1. Immutability — prefer returning new instances over mutation
2. TDD — write tests before implementation
3. 80% coverage minimum
4. Many small files — 200–400 lines typical, 800 max
5. Remove debug logging before merging
6. Proper error handling with try/catch
7. Input validation with Pydantic/Zod
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