Agent skill

project-guidelines-example

Example project-specific skill template based on a real production application.

View SKILL.md on GitHub Repository
Stars 132,726
Forks 19,206

Install this agent skill to your Project

npx add-skill https://github.com/affaan-m/everything-claude-code/tree/main/skills/project-guidelines-example

SKILL.md

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:

┌─────────────────────────────────────────────────────────────┐
│                         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

Recommended Agent Skills

Expand your agent's capabilities with these related and highly-rated skills.

affaan-m/everything-claude-code

python-testing

Python testing best practices using pytest including fixtures, parametrization, mocking, coverage analysis, async testing, and test organization. Use when writing or improving Python tests.

132,726 19,206
Explore
affaan-m/everything-claude-code

golang-patterns

Go-specific design patterns and best practices including functional options, small interfaces, dependency injection, concurrency patterns, error handling, and package organization. Use when working with Go code to apply idiomatic Go patterns.

132,726 19,206
Explore
affaan-m/everything-claude-code

e2e-testing

Playwright E2E testing patterns, Page Object Model, configuration, CI/CD integration, artifact management, and flaky test strategies.

132,726 19,206
Explore
affaan-m/everything-claude-code

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when AI agents perform most implementation work and humans enforce quality and risk controls.

132,726 19,206
Explore
affaan-m/everything-claude-code

api-design

REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs.

132,726 19,206
Explore
affaan-m/everything-claude-code

python-patterns

Python-specific design patterns and best practices including protocols, dataclasses, context managers, decorators, async/await, type hints, and package organization. Use when working with Python code to apply Pythonic patterns.

132,726 19,206
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results