Tool/everything-claude-code/docs/zh-TW/skills/project-guidelines-example/SKILL.md
# 專案指南技能(範例) 這是專案特定技能的範例。使用此作為你自己專案的範本。 基於真實生產應用程式:[Zenith](https://zenith.chat) - AI 驅動的客戶探索平台。 --- ## 何時使用 在處理專案特定設計時參考此技能。專案技能包含: - 架構概覽 - 檔案結構 - 程式碼模式 - 測試要求 - 部署工作流程 --- ## 架構概覽 **技術堆疊:** - **前端**:Next.js 15(App Router)、TypeScript、React - **後端**:FastAPI(Python)、Pydantic 模型 - **資料庫**:Supabase(PostgreSQL) - **AI**:Claude API 帶工具呼叫和結構化輸出 - **部署**:Google Cloud Run - **測試**:Playwright(E2E)、pytest(後端)、React Testing Library **服務:** ``` ┌────────────────────────────────────────────────────
npx skillsauth add lyxjack/toolbox Tool/everything-claude-code/docs/zh-TW/skills/project-guidelines-exampleInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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這是專案特定技能的範例。使用此作為你自己專案的範本。
基於真實生產應用程式:Zenith - AI 驅動的客戶探索平台。
在處理專案特定設計時參考此技能。專案技能包含:
技術堆疊:
服務:
┌─────────────────────────────────────────────────────────────┐
│ 前端 │
│ Next.js 15 + TypeScript + TailwindCSS │
│ 部署:Vercel / Cloud Run │
└─────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ 後端 │
│ FastAPI + Python 3.11 + Pydantic │
│ 部署:Cloud Run │
└─────────────────────────────────────────────────────────────┘
│
┌───────────────┼───────────────┐
▼ ▼ ▼
┌──────────┐ ┌──────────┐ ┌──────────┐
│ Supabase │ │ Claude │ │ Redis │
│ Database │ │ API │ │ Cache │
└──────────┘ └──────────┘ └──────────┘
project/
├── frontend/
│ └── src/
│ ├── app/ # Next.js app router 頁面
│ │ ├── api/ # API 路由
│ │ ├── (auth)/ # 需認證路由
│ │ └── workspace/ # 主應用程式工作區
│ ├── components/ # React 元件
│ │ ├── ui/ # 基礎 UI 元件
│ │ ├── forms/ # 表單元件
│ │ └── layouts/ # 版面配置元件
│ ├── hooks/ # 自訂 React hooks
│ ├── lib/ # 工具
│ ├── types/ # TypeScript 定義
│ └── config/ # 設定
│
├── backend/
│ ├── routers/ # FastAPI 路由處理器
│ ├── models.py # Pydantic 模型
│ ├── main.py # FastAPI app 進入點
│ ├── auth_system.py # 認證
│ ├── database.py # 資料庫操作
│ ├── services/ # 業務邏輯
│ └── tests/ # pytest 測試
│
├── deploy/ # 部署設定
├── docs/ # 文件
└── scripts/ # 工具腳本
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)
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) }
}
}
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"}
)
# 提取工具使用結果
tool_use = next(
block for block in response.content
if block.type == "tool_use"
)
return AnalysisResult(**tool_use.input)
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 }
}
# 執行所有測試
poetry run pytest tests/
# 執行帶覆蓋率的測試
poetry run pytest tests/ --cov=. --cov-report=html
# 執行特定測試檔案
poetry run pytest tests/test_auth.py -v
測試結構:
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"
# 執行測試
npm run test
# 執行帶覆蓋率的測試
npm run test -- --coverage
# 執行 E2E 測試
npm run test:e2e
測試結構:
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()
})
})
npm run build 成功(前端)poetry run pytest 通過(後端)# 建置和部署前端
cd frontend && npm run build
gcloud run deploy frontend --source .
# 建置和部署後端
cd backend
gcloud run deploy backend --source .
# 前端(.env.local)
NEXT_PUBLIC_API_URL=https://api.example.com
NEXT_PUBLIC_SUPABASE_URL=https://xxx.supabase.co
NEXT_PUBLIC_SUPABASE_ANON_KEY=eyJ...
# 後端(.env)
DATABASE_URL=postgresql://...
ANTHROPIC_API_KEY=sk-ant-...
SUPABASE_URL=https://xxx.supabase.co
SUPABASE_KEY=eyJ...
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