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openai/notion-연구-문서화

Notion 전반을 조사하여 구조화된 문서로 종합합니다. 여러 Notion 소스에서 정보를 수집하여 인용이 포함된 브리핑, 비교, 또는 보고서를 작성할 때 사용합니다.

notion-연구-문서화란 무엇인가요?

이 스킬은 AI 에이전트가 Notion 작업 공간 전반을 검색하고, 여러 소스에서 정보를 수집한 후 구조화된 문서(예: 브리핑, 비교 보고서, 요약 등)로 종합할 수 있도록 지원합니다. 특히 인용을 포함한 형태로 결과물을 생성하므로, 정보의 출처를 명확히 추적해야 하는 연구 및 분석 작업에 매우 유용합니다. Notion의 데이터베이스, 페이지, 문서 등 다양한 소스를 대상으로 작동하며, 사용자는 자연어로 질의하거나 분석 대상을 지정할 수 있습니다. 이 스킬은 주로 Claude Code, Cursor, Codex와 같은 AI 코딩 에이전트에서 사용되며, Notion API를 통해 데이터에 접근하고, 검색 결과를 바탕으로 일관된 문서를 생성하는 방식으로 작동합니다. 개발자나 지식 근로자가 프로젝트 리서치, 기술 문서 작성, 의사 결정 지원 자료를 빠르게 만들 때 특히 효과적입니다.

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

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OpenAIChatGPTClaudeClaudeGeminiGeminiGrokGrokPerplexityPerplexityDeepSeekDeepSeek

문서

notion-연구-문서화은(는) 무엇을 하나요?

Notion 전반을 조사하여 구조화된 문서로 종합합니다. 여러 Notion 소스에서 정보를 수집하여 인용이 포함된 브리핑, 비교, 또는 보고서를 작성할 때 사용합니다.

설명

이 스킬은 AI 에이전트가 Notion 작업 공간에 저장된 정보를 검색하고 분석하여 구조화된 문서를 생성할 수 있도록 합니다. 여러 페이지, 데이터베이스, 또는 문서에서 관련 정보를 수집하고, 이를 일관된 형식의 보고서나 브리핑으로 종합합니다. 각 정보의 출처는 자동으로 인용되어 투명성을 보장합니다.

사용 방법

전제 조건

  • Notion API 키 또는 통합 설정이 필요합니다.
  • AI 에이전트(예: Claude Code, Cursor, Codex)가 설치 및 구성되어 있어야 합니다.

기본 사용법

  1. 조사하고자 하는 주제를 자연어로 입력합니다.
  2. AI 에이전트가 Notion 내 관련 문서를 검색합니다.
  3. 검색 결과를 바탕으로 구조화된 문서를 생성합니다.
  4. 결과물은 인용을 포함하며, 필요에 따라 수정 및 보완할 수 있습니다.

예시

  • "최근 프로젝트 진행 상황에 대한 브리핑 작성해줘"
  • "제품 A와 제품 B를 비교하는 보고서를 만들어줘"
  • "고객 피드백 데이터베이스에서 주요 이슈를 요약해줘"

참고 사항

  • 정확한 인용을 위해 대상 문서의 URL이나 ID를 명시적으로 제공할 수 있습니다.
  • 결과물의 형식(개요, 표, 목록 등)을 지정할 수 있습니다.
  • 대용량 데이터 세트를 처리할 때는 명확한 검색 범위를 지정하는 것이 좋습니다.

지원 플랫폼

  • Claude Code
  • Cursor
  • Codex
  • 기타 호환 가능한 AI 에이전트

기술적 세부 사항

  • Notion API를 사용하여 데이터에 접근합니다.
  • 검색 쿼리는 자연어 처리(NLP)를 통해 최적화됩니다.
  • 생성된 문서는 마크다운, HTML, 또는 일반 텍스트 형식으로 출력 가능합니다.

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.

관련 스킬

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

community

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

community

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

community

affaan-m/everything-claude-code

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

community

forrestchang/andrej-karpathy-skills

Agent skill repository discovered by 10x-chat research.

community

langgenius/backend-code-review

Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.

community
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