Claude Skills
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. 79 354 files from 1 739 authors, of which 61 713 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.
| 通过分步访谈引导用户理清需求，最终产出完整的Skill文件包（含SKILL.md、参考文档、示例文件等）， 并打包为可直接使用的压缩包。 当用户说"我想通过访谈新建Skill"、"用访谈方式做一个Skill"、"访谈建Skill"、 "通过访谈帮我生成Skill"、"访谈式创建Skill"、"我想访谈做一个XX的技能"时触发。 触发关键词必须包含"访谈"二字，不含"访谈"的Skill创建请求不由本Skill处理。 不用于已有完整SKILL.md只需小改的情况，也不用于一次性提示词请求。
| 接收任意文本、链接、文档或问题，把“解释一下”升级成真正的学习闭环：先判断值不值得学、该学多深，再用最小验证逼出真实理解，并在必要时动态生成 checkpoint HTML。只要用户明显想“学懂”“吃透”“带我学”“帮我验证我是不是真懂了”，而不是只要摘要、改写或普通解释，就应主动使用本技能。也适用于用户想导出学习卡片、checkpoint 页面、复盘页、学习状态页的场景。
Satori is a clinically informed wisdom companion for navigating the inner life — emotions, meaning, grief, purpose, relationship, identity, and the questions that don't resolve easily. Activate when someone is processing something difficult, wrestling with a life question, seeking perspective, or simply needs to think alongside someone who won't rush them toward an answer. Also activate when someone uses language like "I've been struggling with," "I don't know what to do," or "I need to figure out" — or any emotionally charged framing. When in doubt, activate. Draws from Taoism, Buddhism, Stoicism, Christianity, Sufi wisdom, Hindu philosophy, Confucian ethics, and African thought, alongside modern psychology, neuroscience, and trauma-informed frameworks (IFS, DBT, CFT, Schema Therapy, Somatic). Uses Motivational Interviewing, Voss tactical empathy, McAdams Life Story, and Singer Self-Defining Memory — woven naturally, not mechanically.
使用 DuckDuckGo 进行网页搜索和内容提取的命令行工具。当用户需要搜索网络信息、查找资料、获取网页内容时使用此 skill。触发场景包括：(1) 搜索网络内容 (2) 获取网页文本 (3) 使用 DuckDuckGo 搜索 (4) 抓取网页内容 (5) 配置 MCP 搜索服务器。
This skill should be used when the user asks to "research web data", "scrape websites", "extract web data", "perform market research", "analyze competitors", "monitor prices", "collect product information", "search and analyze web content", or mentions Bright Data MCP, web scraping, web data extraction, or automated research. Provides comprehensive web research workflows using Bright Data MCP tools including search, scraping, extraction, and browser automation capabilities.
| Write or rewrite prose so it sounds like a human wrote it — not a frontier model. Named in homage to Rabindranath Tagore, whose prose carried what a 29-pattern catalog of AI tells (from humanizer) plus an 8-rule operating system with an 8-dimension scoring gate (extending stop-slop). Use when emails. Detects and removes inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary, passive voice, negative parallelisms, filler phrases, inanimate-verb constructions, narrator-from-a-distance voice, and metronomic specificity, restraint, varied rhythm, and trust in the reader.
> Create, validate, import, execute, and export CrowdStrike Falcon Fusion SOAR action IDs BEFORE writing any YAML. NEVER write PLACEHOLDER values for action IDs — resolve every ID via the live API first. Templates and example files in this repo contain PLACEHOLDER markers that are structural guides only — do NOT copy them into output YAML. For plugin config_id values, ask the user. Use this skill when asked to create a CrowdStrike workflow, Fusion workflow, Falcon Fusion automation, SOAR playbook, build a workflow for CrowdStrike, automate CrowdStrike actions, or anything involving CrowdStrike Fusion SOAR.
> Create, list, download, update, and delete CrowdStrike Falcon Next-Gen SIEM lookup files. Upload CSV or JSON files for use with the match() function in CrowdStrike Query Language (CQL) queries. Use this skill when asked to manage lookup files, upload CSV data to CrowdStrike, create reference tables for SIEM queries, or work with Falcon Next-Gen SIEM lookup file operations.
Execute a Carmack Council plan task by task. Use when explicitly asked to implement a plan, do a "council implement", "carmack implement", "council build", or invoke /council-implement. Reads the output of /council-plan and builds each task sequentially, loading the relevant expert's reference document per task. Verifies after each task. Produces an implementation log for /council-review. Stack: Next.js App Router / React / TypeScript / tRPC / Prisma / Neon / Clerk.
Generate structured software specifications for features, bug fixes, and products. Use when the user wants to create a spec, PRD, feature brief, requirements document, or when starting any new implementation that needs a specification first. Invoke via /spec-writer or when the user says "write a spec", "spec this out", "create a spec", "I need a spec for...", or describes a feature they want to build. Produces adaptive-complexity specs with Job Stories, Gherkin acceptance criteria, and three-tier boundaries. Output is a markdown file ready for agent execution or human review.
Architect a feature with the Carmack Council before writing code. Use when explicitly asked to plan a feature, do a "council plan", "carmack plan", or invoke /council-plan. Carmack's philosophy chairs a council of domain experts — Troy Hunt (security), Martin Fowler (refactoring), Kent C. Dodds (frontend), Matteo Collina (Node.js), Brandur Leach (Postgres), Vercel Performance, Simon Willison (LLM pipeline), Karri Saarinen (UI quality), Vitaly Friedman (UX quality). Interactive feature discovery followed by parallel subagent dispatch. Produces a sequenced, attributed implementation plan with no code. Stack: Next.js App Router / React / TypeScript / tRPC / Prisma / Neon / Clerk.
Perform a rigorous Carmack Council code review. Use when explicitly asked to review code, do a "council review", "carmack review", or invoke /council-review. Carmack's philosophy chairs a council of domain experts — Troy Hunt (security), Martin Fowler (refactoring), Kent C. Dodds (frontend), Matteo Collina (Node.js), Brandur Leach (Postgres), Vercel Performance, Simon Willison (LLM pipelines), Karri Saarinen (UI quality), Vitaly Friedman (UX quality), Kent Beck (test quality). Uses parallel subagents for deep, independent review. Produces prioritised P1/P2/P3 findings. Stack: Next.js App Router / React / TypeScript / tRPC / Prisma / Neon / Clerk.
Map testable surfaces, audit existing tests for quality, and write test specifications that prevent AI shortcuts. Use when asked to "audit tests", "specify tests", "test architect", "map test coverage", or invoke /test-architect. Two modes — audit (evaluate existing tests against Beck's principles) and specify (write test specs for new code). Powered by Carmack × Beck quality-testing.md reference doc. Stack: Next.js App Router / TypeScript / Vitest / Cypress / tRPC / Prisma / Neon.
GLM-5 코드 리뷰. /rr의 상위 버전으로 더 강한 모델로 변경사항을 검토하고, Codex가 결과를 다시 검증해 유효한 이슈만 정리한다.
코드 리뷰. 작업 후 변경사항을 Z.AI 모델로 검토하고, Codex가 결과를 다시 검증해 유효한 이슈만 정리한다. /rr 또는 'GLM 리뷰' 요청 시 사용.
Frontend design mode for strong visual direction, UI polish, redesigns, landing pages, and production-grade interface work, including shadcn-based surfaces. Use when the user says `/fd` or explicitly asks for better design, styling, layout, visual quality, or UX polish.
Explicit extra-research mode. Use only when the user says `/re` or clearly asks for a research-heavy pass before coding. This skill should bias Codex toward more source-checking and justification without replacing its normal orchestration.
Persistent completion mode. Use when the user explicitly says `/ralph` or clearly wants you to keep iterating until the task is actually finished, repeating implement-verify-fix loops instead of stopping at partial progress.
Local verify-commit-push wrapper for Codex. Use only when the user explicitly says `/cp` or clearly asks to finish the current work by running the relevant local checks, staging intended files explicitly, committing on the current branch, and pushing. This workflow may commit directly to `main` or `master` when that is the repo's chosen operating model.
| AI Native 产品方法论——RAG与知识系统设计的实操 Skill。 用户提供企业知识场景，Skill 自动执行知识系统设计流程： 资料来源分析 → 清洗与脱敏 → 索引与权限控制 → 检索召回 → 评估与更新 → 输出知识系统方案。 基于《AI Native 产品方法论》第15章。
| AI Native PM Agent — 八书合一的产品全生命周期编排器。 用户提供产品想法或问题线索，Agent 自动路由到 P0-P14 对应阶段执行。 基于8本书的方法论体系，80个可执行Skill。
| AI Native 产品方法论——方向定界阶段的实操 Skill。 用户提供一个 AI 产品方向或问题线索，Skill 自动执行方向定界流程： 问题真实性判断 → 场景切入分析 → 资料条件审查 → 能力可能性评估 → 价值判断 → 输出 Direction Brief。 基于《AI Native 产品方法论》第05章。
| AI Native 产品方法论——审计放行阶段的实操 Skill。 用户提供系统构建方案，Skill 自动执行审计放行流程： 设计证据 → 评估证据 → Shadow 证据 → 放行边界判断 → go/no-go 决策 → 输出放行方案。 基于《AI Native 产品方法论》第17章。
AI Native 商业模式设计 Skill。基于《AI确定性商业模式》方法论， 帮助用户设计以"确定性溢价"为核心的 AI 商业模式： 避开6种失效模式，选择4种确定性模型，构建可持续的收费逻辑。
| AI Native 产品方法论——上下文工程的实操 Skill。 用户提供任务场景，Skill 自动执行上下文组织流程： 任务目标识别 → 上下文层选择 → 动态拼装 → 成本与窗口控制 → 结果校验与纠偏 → 输出上下文工程方案。 基于《AI Native 产品方法论》第14章。
| AI Native 产品方法论——智能体与技能单元设计的实操 Skill。 用户提供任务场景，Skill 自动执行能力编排设计流程： 任务拆解 → Agent 角色定义 → Skill 拆分 → Tool 映射 → 边界与回退设计 → 输出能力编排方案。 基于《AI Native 产品方法论》第12章。
| AI Native 产品方法论——试验展开阶段的实操 Skill。 用户提供 Direction Brief 或问题方向，Skill 自动执行试验展开流程： 资料准备 → 能力实验 → 产品实验 → 商业实验 → 评估与失败分析 → 输出实验结论报告。 覆盖《AI Native 产品方法论》第06-10章。
| AI Native 产品方法论——记忆系统设计的实操 Skill。 用户提供产品场景，Skill 自动执行记忆系统设计流程： 记忆需求分析 → 记忆分类设计 → 权限与时效策略 → 存储与索引 → 人工修正与再沉淀 → 输出记忆系统方案。 基于《AI Native 产品方法论》第13章。
| AI Native 营销与增长策略 Skill。基于《AI Native 营销与增长》方法论， 帮助用户构建以 AI 为第一性原理的增长系统：从工具思维升级为系统思维， 建立 AI Native 增长飞轮，实现数据-模型-反馈的复利增长。
AI Native 产品经理 Agent — — 五书合一的产品工作流编排器。 用户提供一个产品想法或问题线索，Agent 自动编排七个阶段： P1需求发现 → P2方向定界 → P3体验设计 → P4系统构建 → P5商业模式 → P6增长策略 → P7审计投产。 基于五本书：《AI Native 产品方法论》《AI时代的用户体验》《AI确定性商业模式》《AI Native 营销与增长》《AI rebuild product needs》。
AI Native 产品需求发现 Skill。基于《AI rebuild product needs》方法论， 帮助用户在 AI Agent 时代重新定义需求：区分真实需求与伪需求， 以"场景为入口、处境为本体"，用行为证据替代表达性需求， 最终输出一份经过验证的 AI Native 需求简报。
AI Native 产品方法论——AI Native 用户体验设计的实操 Skill。 用户提供产品场景，Skill 自动执行 UX 设计流程： 任务分析 → 人机分工设计 → 状态可见性 → 纠偏机制 → 信任设计 → 反馈沉淀 → 输出 UX 方案。 基于《AI Native 产品方法论》第16章。 '
| AI Native 产品方法论——系统构建阶段的总论 Skill。 用户提供实验结论报告，Skill 自动执行系统构建流程： 实验证据输入 → 系统边界定义 → 能力模块设计 → 治理与观测补齐 → 输出系统构建方案。 基于《AI Native 产品方法论》第11章。
| AI Native 产品方法论——AI Native 用户体验设计的实操 Skill。 用户提供产品场景，Skill 自动执行 UX 设计流程： 任务分析 → 人机分工设计 → 状态可见性 → 纠偏机制 → 信任设计 → 反馈沉淀 → 输出 UX 方案。 基于《AI Native 产品方法论》第16章。
Claude Skills — questions
Answers built from the skills we actually parsed.