Create project guideline examples to align team workflows and documentation.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "project-guidelines-example" skill from askskill: 1. Download https://raw.githubusercontent.com/affaan-m/ECC/main/docs/ja-JP/skills/project-guidelines-example/SKILL.md 2. Save it as ~/.claude/skills/project-guidelines-example/SKILL.md 3. Reload skills and tell me it's ready
Draft an example set of project collaboration guidelines for a 10-person software team, including branch naming, code review, QA handoff, documentation updates, and meeting cadence. Output it in clear Markdown.
A structured example document of project guidelines that can serve as an initial team policy.
Generate a project guideline template for new team members, including project goals, roles, common tools, submission rules, communication channels, and key reminders, in a concise and friendly tone.
A newcomer-friendly project guideline template that helps people quickly understand how the team works.
Here is our current draft of project guidelines. Rewrite it into a clearer and more actionable version, add missing sections, and point out any ambiguous parts: [paste draft]
An improved project guideline document plus a list of ambiguous points that need clarification.
これはプロジェクト固有のスキルの例です。自分のプロジェクトのテンプレートとして使用してください。
実際の本番アプリケーションに基づいています:Zenith - AI駆動の顧客発見プラットフォーム。
このスキルが設計された特定のプロジェクトで作業する際に参照してください。プロジェクトスキルには以下が含まれます:
技術スタック:
サービス:
┌─────────────────────────────────────────────────────────────┐
│ 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 │
└──────────┘ └──────────┘ └──────────┘
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
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
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