SuperAPI AI Directory

project-guidelines-example

Coding & development

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Updated 10-15 08:39

About this skill

Project Guidelines Skill (Example)

This is an example of a project-specific skill. Use it as a template for your own project.

Based on a real production application:Zenith - AI-driven customer discovery platform.


When to Use

Reference this when working on the specific project this skill was designed for. Project skills include the following:

  • 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: API with Claude 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ページ
│       │   ├── api/          # APIルート
│       │   ├── (auth)/       # 認証保護されたルート
│       │   └── workspace/    # メインアプリワークスペース
│       ├── components/       # Reactコンポーネント
│       │   ├── ui/           # ベースUIコンポーネント
│       │   ├── forms/        # フォームコンポーネント
│       │   └── layouts/      # レイアウトコンポーネント
│       ├── hooks/            # カスタムReactフック
│       ├── lib/              # ユーティリティ
│       ├── types/            # TypeScript定義
│       └── config/           # 設定
│
├── backend/
│   ├── routers/              # FastAPIルートハンドラ
│   ├── models.py             # Pydanticモデル
│   ├── main.py               # FastAPIアプリエントリ
│   ├── auth_system.py        # 認証
│   ├── database.py           # データベース操作
│   ├── services/             # ビジネスロジック
│   └── tests/                # pytestテスト
│
├── deploy/                   # デプロイメント設定
├── docs/                     # ドキュメント
└── scripts/                  # ユーティリティスクリプト

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 Call (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-5",
        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)

# すべてのテストを実行
poetry run pytest tests/

# カバレッジ付きで実行
poetry run pytest tests/ --cov=. --cov-report=html

# 特定のテストファイルを実行
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)

# テストを実行
npm run test

# カバレッジ付きで実行
npm run test -- --coverage

# E2Eテストを実行
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 pass locally
  • npm run build succeeds (frontend)
  • poetry run pytest succeeds (backend)
  • No hardcoded secrets
  • Environment variables are documented
  • Database migrations are prepared

Deployment Commands

# フロントエンドのビルドとデプロイ
cd frontend && npm run build
gcloud run deploy frontend --source .

# バックエンドのビルドとデプロイ
cd backend
gcloud run deploy backend --source .

Environment Variables

# フロントエンド (.env.local)
NEXT_PUBLIC_API_URL=https://api.example.com
NEXT_PUBLIC_SUPABASE_URL=https://xxx.supabase.co
NEXT_PUBLIC_SUPABASE_ANON_KEY=eyJ...

# バックエンド (.env)
DATABASE_URL=postgresql://...
ANTHROPIC_API_KEY=sk-ant-...
SUPABASE_URL=https://xxx.supabase.co
SUPABASE_KEY=eyJ...

Important Rules

  1. No Emoji - Do not use emoji in code, comments, or documentation
  2. Immutability - Do not mutate objects or arrays
  3. TDD - Write tests before implementation
  4. 80% coverage - Minimum standard
  5. Many Small Files - Typically 200-400 lines, maximum 800 lines
  6. No console.log - Do not use in production code
  7. Proper Error Handling - Use try/catch
  8. Input Validation - Use 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