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openai/notion-spec-to-implementation

Notionの仕様書を実装計画、タスク、進捗管理に変換します。PRDや機能仕様書を実装する際や、それらからNotionの計画＋タスクを作成するときに使用します。

notion-spec-to-implementation とは？

このスキルは、Notionで管理された製品仕様書（PRD）や機能仕様を、具体的な実装計画とタスクに自動変換するためのAIエージェント機能です。開発者は、このスキルを使用することで、仕様書から直接実行可能なタスクリストや進捗管理用のNotionデータベースを生成できます。主にNotion APIを活用し、構造化されたドキュメントを解析して、実装順序や依存関係を含む詳細な作業計画を作成します。Claude Code、Cursor、Codexなどの主要なAIエージェントプラットフォームで動作し、プロジェクト管理の効率を劇的に向上させます。また、生成されたタスクはNotion上で自動的にリンクされ、進捗状況のリアルタイム追跡が可能になります。

対応~Claude Code✓Codex CLI~Cursor
npx skills add https://github.com/openai/skills/tree/main/skills/notion-spec-to-implementation

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ドキュメント

notion-spec-to-implementation は何をしますか？

Notionの仕様書を実装計画、タスク、進捗管理に変換します。PRDや機能仕様書を実装する際や、それらからNotionの計画＋タスクを作成するときに使用します。

概要

このスキルは、Notionに保存された製品要件ドキュメント（PRD）や機能仕様書を解析し、以下の成果物を自動生成します：

  • 実装計画: 段階的な実装ステップと優先順位付け
  • タスクリスト: 各ステップに対応する具体的なタスク（担当者、期限、依存関係を含む）
  • 進捗トラッキング: Notionデータベースによるリアルタイムの進捗管理

使用方法

前提条件

  • Notion APIトークン（NOTION_API_KEY 環境変数）
  • NotionデータベースID（NOTION_DATABASE_ID 環境変数）

クイックスタート

# 環境変数の設定
export NOTION_API_KEY="your_notion_api_key"
export NOTION_DATABASE_ID="your_database_id"

# スキルの呼び出し例（AIエージェント内で）
# 「このPRDを実装計画に変換して」

機能一覧

機能説明
仕様解析Notionページから構造化データを抽出
計画生成依存関係を考慮した実装計画の作成
タスク分解計画を実行可能なタスクに分割
進捗連携Notionデータベースと自動同期

動作の流れ

  1. 入力: Notion上のPRD/機能仕様のURLまたはページID
  2. 処理:
    • ドキュメントの構造解析（セクション、要件、受け入れ基準）
    • 依存関係の特定
    • 実装順序の決定
  3. 出力:
    • Notionデータベースにタスクを作成
    • 各タスクに説明、優先度、担当者を設定
    • 進捗状況のトラッキング用カスタムビューを生成

注意事項

  • このスキルはNotion APIの読み取り・書き込み権限を必要とします
  • 生成されるタスクは元の仕様書とリンクされます
  • 既存のNotionデータベース構造に影響を与えません

関連リソース

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

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Build a composable CLI for Codex from API docs, an OpenAPI spec, existing curl examples, an SDK, a web app, an admin tool, or a local script. Use when the user wants Codex to create a command-line tool that can run from any repo, expose composable read/write commands, return stable JSON, manage auth, and pair with a companion skill.

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openai/develop-web-game

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openai/doc

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openai/figma

Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.

openai/figma-code-connect-components

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openai/figma-create-design-system-rules

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openai/figma-create-new-file

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openai/figma-generate-design

Use this skill alongside figma-use when the task involves translating an application page, view, or multi-section layout into Figma. Triggers: 'write to Figma', 'create in Figma from code', 'push page to Figma', 'take this app/page and build it in Figma', 'create a screen', 'build a landing page in Figma', 'update the Figma screen to match code'. This is the preferred workflow skill whenever the user wants to build or update a full page, screen, or view in Figma from code or a description. Discovers design system components, variables, and styles via search_design_system, imports them, and assembles screens incrementally section-by-section using design system tokens instead of hardcoded values.

openai/figma-generate-library

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openai/figma-implement-design

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openai/figma-use

**MANDATORY prerequisite** — you MUST invoke this skill BEFORE every `use_figma` tool call. NEVER call `use_figma` directly without loading this skill first. Skipping it causes common, hard-to-debug failures. Trigger whenever the user wants to perform a write action or a unique read action that requires JavaScript execution in the Figma file context — e.g. create/edit/delete nodes, set up variables or tokens, build components and variants, modify auto-layout or fills, bind variables to properties, or inspect file structure programmatically.

openai/frontend-skill

Use when the task asks for a visually strong landing page, website, app, prototype, demo, or game UI. This skill enforces restrained composition, image-led hierarchy, cohesive content structure, and tasteful motion while avoiding generic cards, weak branding, and UI clutter.

openai/gh-address-comments

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openai/gh-fix-ci

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openai/hatch-pet

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openai/imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas.

openai/jupyter-notebook

Use when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and run the helper script `new_notebook.py` to generate a clean starting notebook.

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