sickn33

cc-skill-project-guidelines-example

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# Install this skill:
npx skills add sickn33/antigravity-awesome-skills --skill "cc-skill-project-guidelines-example"

Install specific skill from multi-skill repository

# Description

Project Guidelines Skill (Example)

# SKILL.md


name: cc-skill-project-guidelines-example
description: Project Guidelines Skill (Example)
author: affaan-m
version: "1.0"


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 - 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:

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚                         Frontend                            β”‚
β”‚  Next.js 15 + TypeScript + TailwindCSS                     β”‚
β”‚  Deployed: Vercel / Cloud Run                              β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                              β”‚
                              β–Ό
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚                         Backend                             β”‚
β”‚  FastAPI + Python 3.11 + Pydantic                          β”‚
β”‚  Deployed: Cloud Run                                       β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                              β”‚
              β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”Όβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
              β–Ό               β–Ό               β–Ό
        β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”   β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”   β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
        β”‚ Supabase β”‚   β”‚  Claude  β”‚   β”‚  Redis   β”‚
        β”‚ Database β”‚   β”‚   API    β”‚   β”‚  Cache   β”‚
        β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜   β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜   β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

File Structure

project/
β”œβ”€β”€ frontend/
β”‚   └── src/
β”‚       β”œβ”€β”€ app/              # Next.js app router pages
β”‚       β”‚   β”œβ”€β”€ api/          # API routes
β”‚       β”‚   β”œβ”€β”€ (auth)/       # Auth-protected routes
β”‚       β”‚   └── workspace/    # Main app workspace
β”‚       β”œβ”€β”€ components/       # React components
β”‚       β”‚   β”œβ”€β”€ ui/           # Base UI components
β”‚       β”‚   β”œβ”€β”€ forms/        # Form components
β”‚       β”‚   └── layouts/      # Layout components
β”‚       β”œβ”€β”€ hooks/            # Custom React hooks
β”‚       β”œβ”€β”€ lib/              # Utilities
β”‚       β”œβ”€β”€ types/            # TypeScript definitions
β”‚       └── config/           # Configuration
β”‚
β”œβ”€β”€ backend/
β”‚   β”œβ”€β”€ routers/              # FastAPI route handlers
β”‚   β”œβ”€β”€ models.py             # Pydantic models
β”‚   β”œβ”€β”€ main.py               # FastAPI app entry
β”‚   β”œβ”€β”€ auth_system.py        # Authentication
β”‚   β”œβ”€β”€ database.py           # Database operations
β”‚   β”œβ”€β”€ services/             # Business logic
β”‚   └── tests/                # pytest tests
β”‚
β”œβ”€β”€ deploy/                   # Deployment configs
β”œβ”€β”€ docs/                     # Documentation
└── scripts/                  # Utility scripts

Code Patterns

API Response Format (FastAPI)

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)

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)

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)

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)

# 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:

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)

# Run tests
npm run test

# Run with coverage
npm run test -- --coverage

# Run E2E tests
npm run test:e2e

Test structure:

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

# 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

# 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

  • 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

# Supported AI Coding Agents

This skill is compatible with the SKILL.md standard and works with all major AI coding agents:

Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.