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openai/notion-meeting-intelligence

利用 Notion 上下文和 Codex 研究准备会议材料;适用于收集背景信息、起草议程/预读材料以及根据与会者定制材料时使用。

notion-meeting-intelligence 是什么?

此技能通过整合 Notion 中的项目上下文和 Codex 的研究能力,帮助用户高效准备会议材料。用户无需手动翻阅多个 Notion 文档,即可快速获取会议相关的背景信息、议程草案和预读材料,并能根据与会者的角色和关注点自动定制内容。该技能支持在 Codex 平台上运行,利用 AI 辅助的上下文理解和信息检索来生成结构化的会议材料。典型工作流程包括:从 Notion 提取项目状态、过往会议记录和关键决策;使用 Codex 进行补充研究;然后输出格式化的会议议程或简报。它特别适合需要频繁安排内部或客户会议的产品经理、团队负责人和项目经理,通过减少准备时间并提高材料的针对性,从而提升会议效率。

兼容平台~Claude Code✓Codex CLI~Cursor
npx skills add https://github.com/openai/skills/tree/main/skills/notion-meeting-intelligence

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notion-meeting-intelligence 是做什么的?

利用 Notion 上下文和 Codex 研究准备会议材料;适用于收集背景信息、起草议程/预读材料以及根据与会者定制材料时使用。

概述

该技能使您能够通过 Notion 中存储的项目上下文和 Codex 的研究能力来高效准备会议材料。它自动化了从 Notion 中提取相关会议上下文的过程,并辅以 Codex 的研究结果,从而创建有针对性的议程和预读材料。

功能

  • 上下文收集:自动从 Notion 页面提取关键信息,包括项目状态、行动项和关键决策。
  • 议程起草:基于提取的上下文生成结构化的会议议程草案。
  • 预读材料:汇编相关的预读材料,确保与会者在会前掌握足够信息。
  • 与会者定制:根据特定与会者的角色和兴趣点调整材料。
  • Codex 研究:利用 Codex 进行补充研究,填补信息空白或提供最新数据。

使用方法

要使用此技能,请按照以下步骤操作:

  1. 准备工作:确保您在 Notion 中有相关的会议记录和项目页面。
  2. 调用技能:使用提示触发技能,例如“为 [项目名称] 准备下周的会议材料,与会者包括 [名单]”。
  3. 审查输出:技能将生成会议议程、预读材料和建议的讨论要点。
  4. 定制:根据需要手动调整生成的材料。

支持的平台

  • Codex:主要平台,用于与 Notion 集成并执行研究。
  • 其他平台:理论上可扩展到其他 AI 助手平台,如 Claude Code 或 Cursor。

示例提示

  • "为我们的每周同步会议准备议程,从最近的 Notion 更新中提取内容。"
  • "根据我们项目的最新状态,为与客户的会议起草预读材料。"
  • "为包含产品经理和工程师在内的团队会议定制材料,聚焦于当前冲刺的进展。"

配置

技能可能需要配置以下内容:

  • Notion API 密钥:用于访问 Notion 数据库。
  • Codex 访问权限:用于启用研究功能。
  • 页面路径:指向相关 Notion 页面的 URL 或标识符。

限制

  • 技能的性能取决于 Notion 中数据的质量和结构。
  • 可能无法正确处理复杂的嵌套 Notion 页面或关系数据库。
  • Codex 研究结果应人工验证。

反馈

如有问题或建议,请联系开发者或提交 GitHub Issue。

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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