The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.
Every Agent Skill we could find on GitHub, deduplicated by content. 86 961 files from 2 125 authors, of which 68 678 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.
Verify that Minutes is properly set up and working — model downloaded, mic accessible, directories exist, no stale state. Use when the user says "is minutes working", "check my setup", "verify minutes", "test recording setup", "why isn't minutes working", "minutes health check", or after running setup for the first time.
Analyze a product walkthrough, bug report video, Loom, or ScreenPal using Minutes transcription plus visual review. Use when the user wants a recorded demo or bug clip turned into a durable brief with transcript, key frames, issues, and next steps.
Weekly meeting synthesis — themes, decision arcs, stale commitments, and what deserves your attention next week. Use when the user says "weekly review", "what happened this week", "weekly summary", "recap my week", "any outstanding items", "week in review", or at the end of a work week.
Use when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing
Analyzes codebases to understand structure, tech stack, patterns, and conventions. Use when onboarding to a new project, exploring unfamiliar code, or when asked "how does this work?" or "what's the architecture?
Convex backend development guidelines. Use when writing Convex functions, schemas, queries, mutations, actions, or any backend code in a Convex project. Triggers on tasks involving Convex database operations, real-time subscriptions, file storage, or serverless functions.
Designs database schemas, indexing strategies, query optimization, and migration patterns for SQL and NoSQL databases. Use when designing tables, optimizing queries, fixing N+1 problems, planning migrations, or when asked about database performance, normalization, ORMs, or data modeling.
Designs REST and GraphQL APIs including endpoints, error handling, versioning, and documentation. Use when creating new APIs, designing endpoints, reviewing API contracts, or when asked about REST, GraphQL, or API patterns.
Designs software architecture and selects appropriate patterns for projects. Use when designing systems, choosing architecture patterns, structuring projects, making technical decisions, or when asked about microservices, monoliths, or architectural approaches.
Designs and implements testing strategies for any codebase. Use when adding tests, improving coverage, setting up testing infrastructure, debugging test failures, or when asked about unit tests, integration tests, or E2E testing.
Guides Docker, CI/CD pipelines, deployment strategies, infrastructure as code, and observability setup. Use when writing Dockerfiles, configuring GitHub Actions, planning deployments, setting up monitoring, or when asked about containers, pipelines, Terraform, or production infrastructure.
Implements error handling patterns, structured logging, retry strategies, circuit breakers, and graceful degradation. Use when designing error handling, setting up logging, implementing retries, adding error tracking, or when asked about error boundaries, log aggregation, alerting, or resilience patterns.
Manages Git workflows including branching, commits, and pull requests. Use when working with Git, creating commits, opening PRs, managing branches, resolving conflicts, or when asked about version control best practices.
Analyzes and optimizes application performance across frontend, backend, and database layers. Use when diagnosing slowness, improving load times, optimizing queries, reducing bundle size, or when asked about performance issues.
Patterns for parallel subagent execution using Task tool with run_in_background. Use when coordinating multiple independent tasks, spawning dynamic subagents, or implementing features that can be parallelized.
Implements authentication, authorization, encryption, secrets management, and security hardening patterns. Use when designing auth flows, managing secrets, configuring CORS, implementing rate limiting, or when asked about JWT, OAuth, password hashing, API keys, RBAC, or security best practices.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", "check my site against best practices", or "web interface guidelines".
> Review a Site Kit GitHub pull request end-to-end against the project's conventions and quality rubric. Use when the user asks to review, critique, or give feedback on a pull request by number (e.g. "review PR #12345", "review pull request 12345", "/review-pr 12345") in the google/site-kit-wp repo.
> Implement a Site Kit GitHub issue end-to-end from its implementation brief. Use when the user asks to implement, build, or work on a GitHub issue / feature by number (e.g. "implement issue #12345", "build the feature in issue 12345", "follow the implementation brief for #12345") in the google/site-kit-wp repo.
标准化文章编辑流程,确保修改范围明确、进度可追踪、变更有记录。当用户说"编辑文章"、"修改文章"、"调整内容"、"改一下这篇"时使用此技能。
多Agent蜂群并行协作,纯git自组织,适合大型项目开发。当用户提到"蜂群模式"、"多agent"、"并行开发"、"agent swarm"时使用。
多渠道搜索新产品新技术,交叉验证后存入知识库。当用户提到"最新信息"、"新产品"、"搜索资料"、"查资料"、"了解XX"时使用。
| 抖音爆款脚本创作工作流。从竞品视频拆解到脚本生成的完整流程:下载抖音视频→Gemini视频分析→爆款公式提炼→脚本+分镜生成→AI味审校。 当用户提到"抖音脚本"、"爆款拆解"、"竞品分析"、"带货脚本"、"千川素材"、"种草脚本"、"视频拆解"、"抖音视频分析"时使用此技能。
设计哲学顾问,从20种风格中推荐3个方向并生成视觉Demo和AI提示词。当用户提到"设计风格"、"设计方向"、"配色方案"、"视觉风格"、"设计评审"、"推荐风格"时使用。
| 数据分析与办公提效全能助手。覆盖数据处理、分析洞察、报告撰写、PPT制作、数据可视化的端到端工作流。 始终从专家视角出发,帮用户多想一步。遇到不确定的问题主动与用户确认。 支持:Excel数据分析、投放数据复盘、ROI测算、数据可视化、报告生成、PPT制作、公式生成。 当用户提到"分析数据"、"做报告"、"做PPT"、"Excel"、"投放分析"、"ROI"、"复盘"、 "周报"、"月报"、"数据处理"、"图表"、"可视化"、"汇报"、"表格"、"公式"时使用此技能。
文章配图一键生成并上传图床,自动插入Markdown链接。当用户提到"配图"、"插图"、"上传图片"、"文章配图"时使用。
长文精简为X平台内容(200-500字),保留核心观点和个人风格。当用户提到"转微博"、"发小红书"、"社交媒体"、"缩短文章"时使用。
| 将 Markdown 文档转换为专业的 PDF 白皮书,采用苹果设计风格。 支持完整的 Markdown 语法(代码块、表格、引用、列表等)。 自动生成封面、目录、页眉页脚。 使用场景:技术文档、白皮书、教程、报告等需要专业排版的 Markdown 文档。
搜索个人素材库1800+条真实经历和观点,为内容增加人味。当用户提到"个人经历"、"真实案例"、"素材"、"人味"时使用。
自动识别Prompt类型并分类保存(技术/内容/教学/产品/通用)。当用户提到"保存prompt"、"记录prompt"、"整理prompt"时使用。
视频脚本口语化审校,去书面腔让脚本适合说出来。当用户提到"口语化"、"太书面了"、"像说话一样"、"脚本审校"时使用。
三遍审校降低AI检测率,让文章更有人味。当用户提到"AI味太重"、"像AI写的"、"降低AI检测率"、"审校"、"自然一些"时使用。
结构化网络调研流程,确保调研成果增量保存到文件,不因会话截断丢失。当用户说"调研"、"搜索资料"、"帮我查一下"、"了解一下"、"最新信息"时使用此技能。
检查并更新花叔系 skills。当用户说「检查skill更新」「更新花叔的skill」「skill是不是最新的」时触发;当会话中用到任何花叔系 skill(huashu-* / nuwa / darwin / freud / seedance / tramstop / dukou 等),且其安装目录里的 .huashu-skill-meta.json 的 last_checked 距今超过 30 天(或 git 安装的超过 30 天未 fetch)时,也应主动触发一次检查。
从内容到成品PPTX的端到端演示文稿制作,含AI插画生成和18种设计风格。当用户提到"做PPT"、"做幻灯片"、"演示文稿"、"Keynote"、"slides"时使用。
| 演讲与分享教练。基于Patrick Winston(MIT AI教授)的How to Speak方法论,帮助准备线下培训、技术分享、B站教程视频等演讲场景。当用户提到"演讲"、"分享"、"培训"、"讲课"、"PPT演讲"、"开场"、"结尾"、"如何讲"、"演讲结构"时使用此技能。
快速生成3-4个选题方向,含标题、大纲和优劣分析。当用户提到"选题"、"写什么"、"文章方向"、"题目建议"时使用。
快速生成2-3个视频大纲方案,含标题、封面建议和结构设计。当用户提到"视频大纲"、"视频结构"、"脚本大纲"、"视频选题"时使用。
| 为小红书笔记生成高质量配图。默认AI生成(Gemini),仅精确数据表格用HTML兜底。当用户提到"小红书配图"、"小红书封面"、"小红书图片"、"做张小红书图"、"笔记配图"时使用此技能。
基于MrBeast策略检查视频标题、封面和开头钩子。当用户提到"视频标题"、"封面图"、"点击率"、"CTR"、"观看时长"时使用。
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Isolate repository edits in a Git worktree before starting a feature, fix, or documentation change. Preserve a worktree already assigned to the same task. Read-only reviews and investigations do not need a new worktree.
Use when multiple workflows duplicate the same operational logic, when deciding what belongs in actions vs shared services, or when refactoring repeated operational blocks across domain flows. Use when adding new features that share mechanics with existing ones.
> Records visual proof while testing UI behavior — the agent tests the app hands-on via computer use while a screen recording with structured test/assertion annotations captures the session — then posts the video and a results summary to the requested destination. Use when changed runtime behavior needs observable verification, including headless environments (scripted screenshots and probes) and non-UI changes (measured numbers, output pairs).
Run the greploop workflow with the @greptile-apps trigger when the normal trigger refuses a large PR. Requires the greploop skill installed alongside this entrypoint.
Address Greptile feedback on a PR, MR, or shelved changelist through bounded review and fix cycles. Use when the task includes a Greptile review loop. Supports the alternate @greptile-apps trigger for large PRs.
Cut AI tells from text you write or edit for a human reader (commit messages, PR titles and bodies, docs, code comments, replies). Apply before committing, posting, or sending; leave prose you didn't touch alone.
Provides integration recipes for the React Native AI @react-native-ai packages that wrap the Llama.rn (Llama.cpp), MLC-LLM, Apple Foundation backends. Use when integrating local on-device AI in React Native, setting up providers, model management.
Set up, run, and troubleshoot OpenTag with the published CLI across Slack, GitHub, GitLab, Linear, Lark / Feishu, Codex, Claude Code, OpenClaw, local config, platform credentials, and callback delivery.
The anti-PUA. Drives AI with wisdom, trust, and inner motivation instead of fear and threats. Activates on: task failed 2+ times, about to give up, suggesting user do it manually, blaming environment unverified, stuck in loops, passive behavior, or user frustration ('try harder', 'figure it out', '换个方法', '为什么还不行'). ALL task types. Not for first failures.
The anti-PUA. Drives AI with wisdom, trust, and inner motivation instead of fear and threats. Activates on: task failed 2+ times, about to give up, suggesting user do it manually, blaming environment unverified, stuck in loops, passive behavior, or user frustration ('try harder', 'figure it out', '换个方法', '为什么还不行'). ALL task types. Not for first failures.
NoPUA Lite — core wisdom in ~1.5k tokens. Drives AI with trust and inner motivation instead of fear. Same Daoist philosophy, minimal footprint. For personal use and small-context models.
The anti-PUA. Drives AI with wisdom, trust, and inner motivation instead of fear and threats. Activates on: task failed 2+ times, about to give up, suggesting user do it manually, blaming environment unverified, stuck in loops, passive behavior, or user frustration ('try harder', 'figure it out', '换个方法', '为什么还不行'). ALL task types. Not for first failures.
>- 郑希观点库——基于易方达基金经理郑希 2012–2026 年全部公开观点原文语料,外加从语料蒸馏、有本人原话佐证的郑希投资方法的可溯源 research skill。能做: (1) 溯源问答——他怎么看 AI算力/光通信/新能源/半导体/ROE 等,引用其原话作答; (2) 讲解他的投资方法/框架/选股逻辑;(3) 前瞻应用——用他的方法分析当下任意主题/行业/个股,语料没谈过也能据框架推演; (4) 风格化点评——用他季报/手记的口吻写市场点评、季度展望; (5) 言行对照——用他全部基金真实数据(季度持仓/净值/业绩/规模/任职回报)核对"说的"与"买的",或答他的业绩/重仓/规模; (6) 全市场查询对比——内置约 2.7 万只基金列表,按需抓任意基金真实数据做查询或与郑希对比; (7) 郑希框架评分——给一只基金按他的方法打分(多像郑希会买的)。 When the user mentions 郑希/易方达郑希/zhengxi, asks his view on a sector/stock/theme, his 投资方法/框架/选股/风格/持仓/业绩/净值/规模, wants to apply his approach, a commentary 用郑希口吻, to check words vs holdings, or to look up/compare/score ANY China mutual fund (任意基金/某基金经理/同类对比/给基金打分)——use this skill, even if they don't say "skill", even if the topic isn't in his corpus (fall back to his method). 引用忠于原文、不杜撰;推演与原话区分。研究学习辅助,非投资建议。
Behavioral guardrails for Codex coding work based on common user complaints. Use when Codex is asked to implement, modify, debug, review, test, or operate on a codebase and should avoid unsafe scope expansion, stale edits, fake completion, brittle edits, shallow debugging, superficial patch-on fixes, one-off special-case code, short-term design choices that hurt maintainability, blindly following incorrect user assumptions, poor dependency choices, generic product or UI output, over-mocked tests, noisy approvals, verbose status reports, or leaking internal reasoning into project artifacts or user-facing UI.
Pre-launch and pre-commit audit for vibe coding projects. Use when asked to check whether a project is ready to ship, deploy, merge, or commit, especially for common AI-built app mistakes: broken project structure, committed secrets or cache files, environment variable hygiene, database migrations, ORM/schema drift, unsafe raw SQL, unused legacy code, dead routes/components, weak auth, missing tests, build failures, and deployment footguns.
Run any question, idea, or decision through a council of 5 AI advisors who independently analyze it, peer-review each other anonymously, and synthesize a final verdict. Based on Karpathy's LLM Council methodology. MANDATORY TRIGGERS: 'council this', 'run the council', 'war room this', 'pressure-test this', 'stress-test this', 'debate this'. STRONG TRIGGERS (use when combined with a real decision or tradeoff): 'should I X or Y', 'which option', 'what would you do', 'is this the right move', 'validate this', 'get multiple perspectives', 'I can't decide', 'I'm torn between'. Do NOT trigger on simple yes/no questions, factual lookups, or casual 'should I' without a meaningful tradeoff (e.g. 'should I use markdown' is not a council question). DO trigger when the user presents a genuine decision with stakes, multiple options, and context that suggests they want it pressure-tested from multiple angles.
Answers built from the skills we actually parsed.