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openai/notion-spec-to-implementation

Notion 명세서를 구현 계획, 작업 및 진행 상황 추적으로 변환합니다. PRD/기능 명세서를 구현하고 이로부터 Notion 계획 및 작업을 생성할 때 사용하세요.

notion-spec-to-implementation란 무엇인가요?

이 스킬은 개발자가 Notion에 작성된 제품 요구 사항 문서(PRD)나 기능 명세서를 체계적인 구현 계획, 세부 작업 항목, 진행 상황 추적 구조로 변환할 수 있도록 지원합니다. 주로 Notion을 문서화 및 협업 플랫폼으로 사용하는 팀을 위해 설계되었으며, OpenAI의 에이전트(예: Codex)와 함께 작동합니다. 이 스킬은 입력된 명세서를 분석하여 일관된 작업 분할 구조(WBS)를 생성하고, 각 작업에 예상 소요 시간, 의존성, 우선순위를 할당하며, 진행 상황을 시각적으로 추적할 수 있는 Notion 데이터베이스 템플릿을 생성합니다. 결과적으로 아이디어에서 구현까지의 갭을 줄이고, 프로젝트 관리 오버헤드를 최소화하여 개발자가 실제 코딩에 집중할 수 있도록 돕습니다.

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

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이 에이전트 스킬이 미리 로드된 새 채팅을 엽니다.

문서

notion-spec-to-implementation은(는) 무엇을 하나요?

Notion 명세서를 구현 계획, 작업 및 진행 상황 추적으로 변환합니다. PRD/기능 명세서를 구현하고 이로부터 Notion 계획 및 작업을 생성할 때 사용하세요.

개요

이 스킬은 Notion에 작성된 제품 명세서(PRD, 기능 명세서 등)를 분석하여 체계적인 구현 계획으로 변환합니다. 각 작업은 명확한 정의, 소유자, 예상 시간, 의존성 및 진행 상태를 가지며, Notion 데이터베이스에 자동으로 생성됩니다.

사용 방법

  1. 변환하려는 Notion 명세서 페이지 링크 또는 내용을 제공합니다.
  2. 스킬이 명세서를 분석하고 작업 항목을 생성합니다.
  3. 생성된 작업 항목은 Notion 데이터베이스에 저장되며, 진행 상황을 추적할 수 있습니다.

지원 플랫폼

  • OpenAI Codex
  • Claude Code
  • Cursor

주요 기능

  • 자동 작업 분할: 명세서를 읽고 적절한 크기의 작업 단위로 분할합니다.
  • 의존성 분석: 작업 간 의존 관계를 식별하고 표시합니다.
  • 진행 상황 추적: 각 작업의 상태를 할 일, 진행 중, 완료로 관리합니다.
  • Notion 통합: 생성된 작업을 Notion 데이터베이스에 자동으로 동기화합니다.

설정

환경 변수를 통해 Notion API 키와 데이터베이스 ID를 설정할 수 있습니다.

export NOTION_API_KEY=your_notion_api_key
export NOTION_DATABASE_ID=your_database_id

명령어

명령어설명
/convert <링크>Notion 명세서 링크를 변환하여 작업 목록 생성
/status현재 프로젝트의 진행 상황 확인
/update <작업ID> <상태>특정 작업의 상태 업데이트

예시

  1. /convert https://www.notion.so/MyProject/PRD-v2-abc123
  2. 시스템이 명세서를 분석하여 10개의 작업 항목을 생성합니다.
  3. 각 작업은 Notion 데이터베이스에 자동으로 추가됩니다.
  4. /status 명령어로 전체 진행 상황을 확인할 수 있습니다.

참고 사항

  • 명세서는 명확한 목표와 범위를 포함해야 합니다.
  • 작업 생성 후에도 팀원이 직접 작업을 수정하거나 재배치할 수 있습니다.
  • 자세한 내용은 공식 문서를 참조하세요.

Individual skills in this repo

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

openai/aspnet-core

Build, review, refactor, or architect ASP.NET Core web applications using current official guidance for .NET web development. Use when working on Blazor Web Apps, Razor Pages, MVC, Minimal APIs, controller-based Web APIs, SignalR, gRPC, middleware, dependency injection, configuration, authentication, authorization, testing, performance, deployment, or ASP.NET Core upgrades.

openai/chatgpt-apps

Build, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow by invoking the openai-docs skill or OpenAI developer docs MCP tools before generating code.

openai/cli-creator

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.

openai/cloudflare-deploy

Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.

openai/develop-web-game

Use when Codex is building or iterating on a web game (HTML/JS) and needs a reliable development + testing loop: implement small changes, run a Playwright-based test script with short input bursts and intentional pauses, inspect screenshots/text, and review console errors with render_game_to_text.

openai/doc

Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts/render_docx.py` for visual checks.

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

Connects Figma design components to code components using Code Connect mapping tools. Use when user says "code connect", "connect this component to code", "map this component", "link component to code", "create code connect mapping", or wants to establish mappings between Figma designs and code implementations. For canvas writes via `use_figma`, use `figma-use`.

openai/figma-create-design-system-rules

Generates custom design system rules for the user's codebase. Use when user says "create design system rules", "generate rules for my project", "set up design rules", "customize design system guidelines", or wants to establish project-specific conventions for Figma-to-code workflows. Requires Figma MCP server connection.

openai/figma-create-new-file

Create a new blank Figma file. Use when the user wants to create a new Figma design or FigJam file, or when you need a new file before calling use_figma. Handles plan resolution via whoami if needed. Usage — /figma-create-new-file [editorType] [fileName] (e.g. /figma-create-new-file figjam My Whiteboard)

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

Build or update a professional-grade design system in Figma from a codebase. Use when the user wants to create variables/tokens, build component libraries, set up theming (light/dark modes), document foundations, or reconcile gaps between code and Figma. This skill teaches WHAT to build and in WHAT ORDER — it complements the `figma-use` skill which teaches HOW to call the Plugin API. Both skills should be loaded together.

openai/figma-implement-design

Translates Figma designs into production-ready application code with 1:1 visual fidelity. Use when implementing UI code from Figma files, when user mentions "implement design", "generate code", "implement component", provides Figma URLs, or asks to build components matching Figma specs. For Figma canvas writes via `use_figma`, use `figma-use`.

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

Help address review/issue comments on the open GitHub PR for the current branch using gh CLI; verify gh auth first and prompt the user to authenticate if not logged in.

openai/gh-fix-ci

Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL.

openai/hatch-pet

Create, repair, validate, visually QA, and package Codex-compatible animated pets and pet spritesheets from character art, generated images, company or prospect brand cues, or visual references. Use when a user wants a lightweight-worker Codex pet workflow, a non-pixel custom pet style, a prospect or company mascot pet, or a full 8x9 animated pet atlas with transparent unused cells, QA contact sheets, and pet.json packaging. This skill composes the installed $imagegen system skill for visual generation and uses bundled scripts for deterministic spritesheet assembly.

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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