docs/zh-CN/skills/project-guidelines-example/SKILL.md
基于真实生产应用的示例项目特定技能模板。
npx skillsauth add ysyecust/everything-claude-code project-guidelines-exampleInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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这是一个项目特定技能的示例。将其用作您自己项目的模板。
基于一个真实的生产应用程序:Zenith - 由 AI 驱动的客户发现平台。
在为其设计的特定项目上工作时,请参考此技能。项目技能包含:
技术栈:
服务:
┌─────────────────────────────────────────────────────────────┐
│ 前端 │
│ Next.js 15 + TypeScript + TailwindCSS │
│ 部署平台:Vercel / Cloud Run │
└─────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────┐
│ 后端 │
│ FastAPI + Python 3.11 + Pydantic │
│ 部署平台:Cloud Run │
└─────────────────────────────────────────────────────────────┘
│
┌───────────────┼───────────────┐
▼ ▼ ▼
┌──────────┐ ┌──────────┐ ┌──────────┐
│ Supabase │ │ Claude │ │ Redis │
│ 数据库 │ │ API │ │ 缓存 │
└──────────┘ └──────────┘ └──────────┘
project/
├── frontend/
│ └── src/
│ ├── app/ # Next.js 应用路由页面
│ │ ├── api/ # API 路由
│ │ ├── (auth)/ # 受身份验证保护的路由
│ │ └── workspace/ # 主应用工作区
│ ├── components/ # React 组件
│ │ ├── ui/ # 基础 UI 组件
│ │ ├── forms/ # 表单组件
│ │ └── layouts/ # 布局组件
│ ├── hooks/ # 自定义 React 钩子
│ ├── lib/ # 工具库
│ ├── types/ # TypeScript 类型定义
│ └── config/ # 配置文件
│
├── backend/
│ ├── routers/ # FastAPI 路由处理器
│ ├── models.py # Pydantic 模型
│ ├── main.py # FastAPI 应用入口
│ ├── auth_system.py # 身份验证模块
│ ├── database.py # 数据库操作
│ ├── services/ # 业务逻辑层
│ └── tests/ # pytest 测试
│
├── deploy/ # 部署配置
├── docs/ # 文档
└── scripts/ # 工具脚本
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"}
)
# Extract tool use result
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 }
}
# 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
测试结构:
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"
# Run tests
npm run test
# Run with coverage
npm run test -- --coverage
# Run E2E tests
npm run test:e2e
测试结构:
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 通过 (后端)# 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 .
# 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...
coding-standards.md - 通用编码最佳实践backend-patterns.md - API 和数据库模式frontend-patterns.md - React 和 Next.js 模式tdd-workflow/ - 测试驱动开发方法论documentation
将签证申请文件(图片)翻译成英文,并创建包含原文和译文的双语PDF
content-media
视频与音频的查看、理解与行动。查看:从本地文件、URL、RTSP/直播源或实时录制桌面获取内容;返回实时上下文和可播放流链接。理解:提取帧,构建视觉/语义/时间索引,并通过时间戳和自动剪辑搜索片段。行动:转码和标准化(编解码器、帧率、分辨率、宽高比),执行时间线编辑(字幕、文本/图像叠加、品牌化、音频叠加、配音、翻译),生成媒体资源(图像、音频、视频),并为直播流或桌面捕获的事件创建实时警报。
data-ai
AI辅助的视频编辑工作流程,用于剪辑、构建和增强实拍素材。涵盖从原始拍摄到FFmpeg、Remotion、ElevenLabs、fal.ai,再到Descript或CapCut最终润色的完整流程。适用于用户想要编辑视频、剪辑素材、制作vlog或构建视频内容的情况。
development
Claude Code 会话的全面验证系统。