home / skills / affaan-m / everything-claude-code / project-guidelines-example
This skill provides project-guidelines context and patterns to accelerate consistent architecture, testing, and deployment across a specific codebase.
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---
name: project-guidelines-example
description: "Example project-specific skill template based on a real production application."
---
# Project Guidelines Skill (Example)
This is an example of a project-specific skill. Use this as a template for your own projects.
Based on a real production application: [Zenith](https://zenith.chat) - AI-powered customer discovery platform.
## When to Use
Reference this skill when working on the specific project it's designed for. Project skills contain:
- Architecture overview
- File structure
- Code patterns
- 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 │
│ Deployed: Vercel / Cloud Run │
└─────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ Backend │
│ FastAPI + Python 3.11 + Pydantic │
│ Deployed: Cloud Run │
└─────────────────────────────────────────────────────────────┘
│
┌───────────────┼───────────────┐
▼ ▼ ▼
┌──────────┐ ┌──────────┐ ┌──────────┐
│ Supabase │ │ Claude │ │ Redis │
│ Database │ │ API │ │ Cache │
└──────────┘ └──────────┘ └──────────┘
```
---
## File Structure
```
project/
├── frontend/
│ └── src/
│ ├── app/ # Next.js app router pages
│ │ ├── api/ # API routes
│ │ ├── (auth)/ # Auth-protected routes
│ │ └── workspace/ # Main app workspace
│ ├── components/ # React components
│ │ ├── ui/ # Base UI components
│ │ ├── forms/ # Form components
│ │ └── layouts/ # Layout components
│ ├── 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
│ ├── auth_system.py # Authentication
│ ├── database.py # Database operations
│ ├── services/ # Business logic
│ └── tests/ # pytest tests
│
├── deploy/ # Deployment configs
├── docs/ # Documentation
└── scripts/ # Utility scripts
```
---
## Code Patterns
### API Response Format (FastAPI)
```python
from pydantic import BaseModel
from typing import Generic, TypeVar, Optional
T = TypeVar('T')
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
interface ApiResponse<T> {
success: boolean
data?: T
error?: string
}
async function fetchApi<T>(
endpoint: string,
options?: RequestInit
): Promise<ApiResponse<T>> {
try {
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()
} catch (error) {
return { success: false, error: String(error) }
}
}
```
### Claude AI Integration (Structured Output)
```python
from anthropic import Anthropic
from pydantic import BaseModel
class AnalysisResult(BaseModel):
summary: str
key_points: list[str]
confidence: float
async def analyze_with_claude(content: str) -> AnalysisResult:
client = Anthropic()
response = client.messages.create(
model="claude-sonnet-4-5-20250514",
max_tokens=1024,
messages=[{"role": "user", "content": content}],
tools=[{
"name": "provide_analysis",
"description": "Provide structured analysis",
"input_schema": AnalysisResult.model_json_schema()
}],
tool_choice={"type": "tool", "name": "provide_analysis"}
)
# Extract tool use result
tool_use = next(
block for block in response.content
if block.type == "tool_use"
)
return AnalysisResult(**tool_use.input)
```
### Custom Hooks (React)
```typescript
import { useState, useCallback } from 'react'
interface UseApiState<T> {
data: T | null
loading: boolean
error: string | null
}
export function useApi<T>(
fetchFn: () => Promise<ApiResponse<T>>
) {
const [state, setState] = useState<UseApiState<T>>({
data: null,
loading: false,
error: null,
})
const execute = useCallback(async () => {
setState(prev => ({ ...prev, loading: true, error: null }))
const result = await fetchFn()
if (result.success) {
setState({ data: result.data!, loading: false, error: null })
} else {
setState({ data: null, loading: false, error: result.error! })
}
}, [fetchFn])
return { ...state, execute }
}
```
---
## Testing Requirements
### Backend (pytest)
```bash
# Run all tests
poetry run pytest tests/
# Run with coverage
poetry run pytest tests/ --cov=. --cov-report=html
# Run specific test file
poetry run pytest tests/test_auth.py -v
```
**Test structure:**
```python
import pytest
from httpx import AsyncClient
from main import app
@pytest.fixture
async def client():
async with AsyncClient(app=app, base_url="http://test") as ac:
yield ac
@pytest.mark.asyncio
async def test_health_check(client: AsyncClient):
response = await client.get("/health")
assert response.status_code == 200
assert response.json()["status"] == "healthy"
```
### Frontend (React Testing Library)
```bash
# Run tests
npm run test
# Run with coverage
npm run test -- --coverage
# Run E2E tests
npm run test:e2e
```
**Test structure:**
```typescript
import { render, screen, fireEvent } from '@testing-library/react'
import { WorkspacePanel } from './WorkspacePanel'
describe('WorkspacePanel', () => {
it('renders workspace correctly', () => {
render(<WorkspacePanel />)
expect(screen.getByRole('main')).toBeInTheDocument()
})
it('handles session creation', async () => {
render(<WorkspacePanel />)
fireEvent.click(screen.getByText('New Session'))
expect(await screen.findByText('Session created')).toBeInTheDocument()
})
})
```
---
## Deployment Workflow
### Pre-Deployment Checklist
- [ ] All tests passing locally
- [ ] `npm run build` succeeds (frontend)
- [ ] `poetry run pytest` passes (backend)
- [ ] No hardcoded secrets
- [ ] Environment variables documented
- [ ] Database migrations ready
### Deployment Commands
```bash
# Build and deploy frontend
cd frontend && npm run build
gcloud run deploy frontend --source .
# Build and deploy backend
cd backend
gcloud run deploy backend --source .
```
### Environment Variables
```bash
# Frontend (.env.local)
NEXT_PUBLIC_API_URL=https://api.example.com
NEXT_PUBLIC_SUPABASE_URL=https://xxx.supabase.co
NEXT_PUBLIC_SUPABASE_ANON_KEY=eyJ...
# Backend (.env)
DATABASE_URL=postgresql://...
ANTHROPIC_API_KEY=sk-ant-...
SUPABASE_URL=https://xxx.supabase.co
SUPABASE_KEY=eyJ...
```
---
## Critical Rules
1. **No emojis** in code, comments, or documentation
2. **Immutability** - never mutate objects or arrays
3. **TDD** - write tests before implementation
4. **80% coverage** minimum
5. **Many small files** - 200-400 lines typical, 800 max
6. **No console.log** in production code
7. **Proper error handling** with try/catch
8. **Input validation** with Pydantic/Zod
---
## Related Skills
- `coding-standards.md` - General coding best practices
- `backend-patterns.md` - API and database patterns
- `frontend-patterns.md` - React and Next.js patterns
- `tdd-workflow/` - Test-driven development methodology
This skill is a project-specific guideline template modeled on a production application. It captures architecture, file layout, code patterns, testing, deployment steps, and critical rules to keep a codebase consistent and deployable. Use it as a concrete blueprint to onboard engineers and standardize implementation choices across frontend, backend, and AI integration.
The skill documents what to inspect and enforce: tech stack choices, folder structure, API response contracts, custom hooks, and Claude/Anthropic integration patterns. It outlines test suites and commands for running frontend and backend tests, plus a pre-deployment checklist and commands for building and deploying services. It also lists critical team rules and environment variable expectations to prevent common operational errors.
What tests must pass before deployment?
All unit and integration tests for backend (pytest) and frontend tests (React Testing Library and E2E) must pass; aim for 80% coverage.
How should AI responses be validated?
Use a typed output schema (Pydantic) for Claude tool responses and validate tool_use blocks before consuming results.
Where do I store secrets and environment variables?
Never hardcode secrets. Store secrets in your deployment platform secrets manager and document required variables in README or docs; use .env only locally.