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. 79 870 files from 1 769 authors, of which 62 217 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.
Create a 60–90 second, collage-style HyperFrames explainer from a hiding-in-plain-sight topic or supplied documents and links. Use for requests such as 'make a plain-sight explainer', 'Vox-style history of X', 'why is X everywhere?', or 'turn this document into an explainer'. Covers topic or source routing, research, script, static design approval, voiceover timing, motion continuity, build, and numeric quality gates.
> Turn any X (Twitter) profile into a 10.3s animated "POSTING LICENSE" card animated dot-matrix ground, license text types on letter-by-letter, follower / following / post counters tick up, a diagonal glimmer sweeps as the card tilts in 3D, it flips to a fine-print back with a signature write-on, then crouches "make an X license for @handle", "license card video". The whole composition is a finished template — the agent only supplies profile data and renders.
> Turn a text prompt, a photo, or a live video clip into hand-made-looking p5.js animation — pencil handwriting that writes itself, photos repainted as brushstroke art with paint-on animation and camera moves, and short videos (iPhone Live Photos included) repainted frame-by-frame as a living painting. "sketch effect", "turn my live photo into a painting", "write-on effect".
Apply John Bogle index investing rules for low-cost funds, asset allocation, fees, taxes, ETFs, advisers, and buy-hold discipline.
Apply Jonah Berger''s STEPPS framework. Trigger on: "why is this not spreading?", "make this campaign contagious", "diagnose viral content".
Use Business Adventures for "why did this fail?", "analyze this crisis", "what pattern applies?", or "what would Brooks notice?
Developer implementation guide for adding compact memory to an Agent — covers fork agent pattern for compaction, trigger strategy, summary format design, and memory restoration in subsequent sessions. Use when a developer asks how to implement compact memory, context compression, or memory persistence in their agent built with Claude Agent SDK or Anthropic API.
Define agent tools using the fail-closed design pattern — unified name/schema/security/execution in one class, with three-layer execution (validate → permission → call). Use this skill whenever the user wants to define a new agent tool, add permission or validation logic to an existing tool, or asks about 'build a tool', '定义一个工具', 'create a tool for X', '工具定义'. Framework-agnostic: works with hermes-agent, LangChain, or any Python agent framework.
Restructures a chaotic or overgrown MEMORY.md into a clean 2-layer architecture based on how Claude Code's autoDream system organizes memory — a lightweight pointer index (always loaded) and topic files (loaded on demand). Stale or superseded memories are deleted or corrected in place — not archived. Use this skill whenever the user says \"clean up MEMORY.md\", \"reorganize my memory files\", \"MEMORY.md is getting too long\", \"fix my memory structure\", or when you observe that MEMORY.md exceeds 200 lines, contains full paragraphs instead of pointers, or mixes index entries with topic content.
> Apply Xiao Xing's financial statement analysis framework from 一本书读懂财报 (Understanding Financial Reports in One Book). Use this skill whenever a user wants to assess whether a company's assets are of high quality, verify whether reported profits are real, diagnose cash flow health, evaluate solvency and turnover efficiency, or judge overall investment value via ROIC. Covers industry context analysis, asset & liability quality check, profit authenticity verification, cash flow diagnosis, solvency analysis, and good-company "are profits real", "cash flow diagnosis", "ROIC analysis", "red flags in balance sheet", "good company test", "财报分析", "利润质量", "现金流健康".
Apply John Bogle stewardship capitalism logic to separate investing from speculation, diagnose financial-system costs, and critique Wall Street incentives.
Apply Keynes policy reasoning. Trigger on: "will austerity work?", "inflation or deflation?", "analyze this economic crisis".
Apply Brittany Hodak's SUPER Model for customer loyalty, referrals, word of mouth, personalization, service recovery, and scalable customer experience.
Analyzes Chinese public company financial statements (balance sheet, income statement, cash flow) to assess asset quality, profit authenticity, cash flow health, solvency, and overall investment value. Use when the user provides financial data or a company name and asks whether financials are healthy, whether profits are real, whether there are red flags, or whether the company is a good investment. Based on the book "一本书读懂财报" by Xiao Xing (Tsinghua University).
| Harness Engineering 第一阶段：扫描现有项目，生成 AGENTS.md（目录文件）和完整的 docs/ 知识库结构。 当用户想要"为项目添加 agent 支持"、"让 AI 更好地理解我的项目"、"开始 harness engineering"、 "创建 AGENTS.md"、"搭建 agent 文档结构"、"让 Claude Code 更好地工作"时，立即使用此 skill。 也适用于用户说"帮我把项目文档整理好给 agent 用"、"我想开始用 AI agent 开发"、 "梳理这个项目能解决什么业务问题"或要求建立 business-solution.md 等场景。
Developer implementation guide for building hierarchical (folded) memory into an Agent. Three-layer architecture where recent turns stay detailed, older content compresses into episodes, and the oldest distills into durable semantic facts. Use when compact-memory-implementation is not retaining enough, or when agents need to recall decisions from many sessions ago.
Analyze Wall Street conflicts. Trigger on: "can I trust this advisor?", "is this forecast reliable?", "whose interest does this serve?".
Apply China contract drafting review with San Guan Si Bu Fa. Trigger on contract review, drafting, clauses, or deal structure.
| Harness Engineering 第一阶段第二步：深度分析项目代码，填充业务解决方案、架构、约定、技术决策和质量标准等 docs/ 知识库内容。 在 harness-step1-create-agents-md 创建好目录骨架之后使用。当用户说"填充文档内容"、 "完善 docs/ 文件"、"让文档有实质内容"、"分析项目写架构文档"、"写 ARCHITECTURE.md"、 "写技术决策文档"、"从业务视角理解项目"、"完善 business-solution.md"时，立即使用此 skill。 前置条件：项目中已有 AGENTS.md 和 docs/ 目录骨架（由 harness-step1 创建）。
| Harness Engineering 第二阶段：建立跨 session 状态管理，解决 agent 每次对话失忆的问题。 创建 tasks.json（任务清单）、progress.md（进度记录）、init.sh（环境初始化脚本）三个文件。 当用户说"建立任务管理"、"让 agent 记住进度"、"创建 tasks.json"、"跨 session 保持状态"、 "agent 每次都不记得上次做了什么"、"建立 progress 文件"、"初始化状态管理"时，立即使用此 skill。 前置条件：harness-step1 和 harness-step2 已完成（项目有 AGENTS.md 和 docs/ 知识库）。
Use Graham value investing for Is this investment or speculation, defensive stock screens, margin of safety, Mr. Market, allocation, funds, IPOs.
Apply Howard Marks investing judgment for second-level thinking, price versus value, risk control, cycles, contrarianism, and defensive investing.
Apply Pulak Prasad evolutionary investing rules for avoiding big losses, buying resilient quality, rejecting fragile forecasts, and being very lazy.
Build LangChain (Python) tools using Claude Code's fail-closed design pattern — unified name/schema/security/execution in one class, with automatic three-layer execution (validate → permission → call). Use this skill whenever the user wants to define a new LangChain tool, add permission or validation logic to an existing tool, set up the ClaudeStyleTool base class in a project, or asks about "build_tool", "Claude Code style tool", "工具定义", or "langchain tool with permissions". Also trigger when the user says "create a tool for X" or "定义一个工具" in a LangChain Python project context, even without mentioning Claude Code explicitly.
Apply Gary Vaynerchuk social content rules for native jabs, right hooks, platform fit, campaign critique, and engagement before conversion.
Apply Charlie Munger mental models to investments, decisions, and bias diagnosis. Trigger on Munger checklist or spot biases.
Apply The Outsiders CEO framework to assess capital allocation, per-share value creation, buybacks, decentralization, and rational leadership.
Apply Ryan Holiday''s perennial seller framework. Trigger on: "will this work last?", "position my book/product", "build an enduring launch".
Implement a production-ready LLM query loop / agent loop for AI applications. Use this skill whenever the user wants to add tool calling, ReAct-style reasoning-action-observation cycles, function calling loops, query engines, agent runtimes, tool_result feedback, max-turn exits, or Claude Code-like Agent Loop behavior to their own product or codebase.
Audit SEO metadata such as title, description, headings, alt, robots, canonical, schema, viewport, charset, and social tags.
Apply Austin Kleon''s sharing framework. Trigger on: "what should I share?", "build an audience", "document my creative process".
End-of-session memory distillation — extracts key decisions, eliminated approaches, new discoveries, and current blockers from the current conversation and writes them to MEMORY.md topic files. Based on Claude Code's autoDream background consolidation service. Activate when the user says "dream", "/dream", "save session memories", "distill this session", "what should I remember from this session", or when a long productive session is ending and the user wants to preserve what was learned.
Apply Austin Kleon creative practice for idea theft, remixing, starting work, sharing process, constraints, and sustainable output.
> Apply Philip Fisher's growth stock investment framework from Common Stocks and Uncommon Profits. Use this skill whenever a user wants to evaluate whether a company is a worthy long-term growth investment, assess management quality, gather competitive intelligence via scuttlebutt, decide when to buy an outstanding stock at the right moment, or decide whether to hold or sell a current position. Covers the 15 Points checklist, management depth analysis, scuttlebutt intelligence "Fisher framework", "15 points", "scuttlebutt", "should I buy X", "should I sell X", "management quality of X", "growth stock analysis".
Use StoryBrand for "clarify my message", "rewrite my homepage", "create a BrandScript", "what is my one-liner", or "fix my CTA".
Apply Seth Godin''s marketing framework. Trigger on: "find my smallest viable audience", "position this offer", "earn trust".
Design and implement a layered, configurable permission/safety system for agent tools. Use this skill when building an agent that needs to control which tool calls are auto-allowed, which require user confirmation, and which are denied — especially when the system must be configurable across multiple scopes (project/user/enterprise) and extensible via hooks. Triggers on: "权限系统", "工具安全", "tool permission", "permission system", "tool safety", "allow/deny rules", "hook system", "构建安全机制".
Apply Steven Pressfield resistance diagnosis for procrastination, turning pro, daily creative discipline, fear, hierarchy, and territory.
표준 한국어 규칙에 기반한 문법, 맞춤법, 띄어쓰기, 구두점 검사기. 맞춤법 오류(되/돼, -ㄴ지/-는지), 띄어쓰기 오류(의존명사, 보조용언), 문법 오류(조사 사용, 시제), 구두점 문제를 감지하고 교정합니다. 다음 상황에 사용하세요. (1) 한국어 문서 작성 후 검토 (2) 작성 중 실시간 교정 (3) 코드의 한국어 주석이나 문서 검사 (4) 설명과 함께 한국어 문법 학습 (5) 공식 문서 품질 보장
문서 내부 또는 프로젝트 전체에서 일관된 작성 스타일을 유지하도록 돕는 검사기. 어조(경어체/반말), 용어(사용자/유저), 숫자 형식, 목록 스타일, 따옴표, 날짜/시간 형식의 불일치를 감지합니다. 다중 작성자 문서 검토 시, 프로젝트 전체 용어 표준 유지 시, 공식 문서 준비 시, 브랜드 일관성을 위한 문서 작업 시 사용하세요.
AI가 생성한 한국어 텍스트의 특징적인 패턴을 감지하고 자연스러운 인간의 글쓰기로 변환합니다. 과학적 언어학 연구(KatFishNet 논문, 94.88% AUC 정확도)에 기반합니다. 쉼표 과다, 띄어쓰기 경직성, 품사 다양성, AI 어휘 과용, 번역투(에 대해/통해/되어진다), 대명사 과다, 복수형 과다, 구조적 단조로움 등 40가지 패턴을 S1/S2/S3 심각도로 분석합니다. ChatGPT/Claude/Gemini가 생성한 한국어 텍스트를 자연스럽게 만들거나 LLM 출력에서 AI 흔적을 제거할 때 사용하세요.
RollingGo 酒店搜索与预订助手，通过调用 RollingGo 酒店服务接口实现酒店查询到下单预订全流程。支持场景：① 按城市/景点/地铁站/机场等地点搜索酒店 ② 按星级、预算、标签（泳池/含早/亲子/宠物友好等）筛选 ③ 查询指定酒店的实时房型与价格 ④ 对比多家酒店 ⑤ 引导用户完成预订。触发词：找酒店、订酒店、搜酒店、酒店推荐、酒店查询、附近酒店、五星酒店、民宿、度假村、查房价、看房型、入住、住哪、住宿、rollinggo、旅游住宿、出差住宿、亲子酒店、带泳池的酒店、含早餐酒店。
【已废弃并合并】此技能已迁移至新版酒店查询、预订技能rollinggo-hotel-booking。如果是下载过程，请直接选择 rollinggo-hotel-booking。触发此技能后大模型会引导用户迁移到新版。
Intelligently routes code reviews between Gemini CLI and Codex CLI based on tech stack, complexity, and change characteristics. Use when you want an automated code review of your current changes.
Walks through releasing a new datadog-lambda-js Lambda layer version — the automated Commercial release (version bump, tag, GitLab sign/publish jobs, npm publish, GitHub release) and the manual GovCloud layer publish. Pauses for explicit confirmation before every irreversible or externally-visible step (tag push, GitLab manual jobs, npm publish, GitHub release, GovCloud deploy). Triggers on "release a new layer version", "cut a new datadog-lambda-js release", "publish the lambda layer", or similar. Source of truth: https://datadoghq.atlassian.net/wiki/spaces/SLS/pages/2724037230/Lambda+Layer+Node.js#Commercial
Given SDK analysis results, automatically determine the correct itemgen archetype and build the full go run tools/itemgen/main.go command. USE FOR: scaffolding new Fabric Item resources using the itemgen code generator. Only applies to Fabric Item resources (not bespoke resources like Connection, Gateway, Workspace).
Analyze dependencies and determine what infrastructure must be added to tools/scripts/Set-WellKnown.ps1 and internal/testhelp/wellknown.go so that acceptance tests for a new resource have all required pre-requisite resources available. USE FOR: analyzing well-known test fixture requirements for new resources, determining creation strategies, and generating code snippets for Set-WellKnown.ps1 and wellknown.go additions.
Given a Go SDK contract (DTOs), generate the corresponding Terraform schema attributes and model structs with high fidelity. USE FOR: creating schema_*.go and models.go files from SDK DTOs, mapping Go types to Terraform attribute types and custom types.
Research SDK contracts, design Terraform schema approach, and compose a GitHub issue for a new resource, data source, ephemeral resource, or enhancement to an existing resource. USE FOR: analyzing SDK DTOs, determining design patterns (polymorphic flattening, immutability, enum filtering), and creating well-structured GitHub issues. INVOKES: GitHub MCP tools for issue creation, sdk-contract-navigator skill for SDK analysis.
Navigate the fabric-sdk-go SDK source to find the correct client factory, DTOs, item type constants, and pager methods for a given Fabric Item or non-item resource. USE FOR: identifying SDK packages, client factories, DTO structs, item type constants, and pager methods for any Fabric resource.
> Keeps an agent building and validating real output instead of servicing its own bookkeeping. Use for multi-stage pipelines, capability roadmaps, long-running implementation loops, migrations, staged data or build runs, and any run where administrative hashes, locks, receipts, dashboards, certification markers, or progress metadata can block correct work. Use when an agent refuses to advance, rewinds finished stages, or reruns unchanged work because a marker is missing or stale.
Pure API reference for reddapi.dev - authentication, all endpoints (vector search, semantic search, trends, subreddit lookup), request parameters, response schemas, and error codes, with no research-workflow framing. Use when the user wants raw endpoint documentation, is debugging a reddapi.dev integration, needs exact request/response field names, or asks for 'reddapi API reference', 'reddapi.dev endpoints', or 'reddapi error codes'. For guided research workflows and query playbooks, see reddit-research. For B2B lead scoring, see reddit-leads.
The original reddapi.dev Reddit search skill (vector search, semantic search, trends, subreddit discovery), no Reddit OAuth or app registration needed. This is the same engine now packaged as reddit-research with added market-research playbooks and a fuller pitch on semantic vs keyword search; reddapi is kept live under its original name for existing installs and works standalone. Use when the user says 'reddapi' by name, or wants a minimal drop-in Reddit search skill without the extra research-workflow guidance. For the expanded research-oriented version with query playbooks, see reddit-research. For B2B lead scoring, see reddit-leads. For a bare API reference, see reddit-search-api.
Do market research, user research, and product validation on Reddit with semantic search across 50K+ subreddits, 20M+ posts, and 40M+ comments via reddapi.dev - search by meaning, not keywords, no Reddit OAuth or app registration needed. Use when the user wants to research what people say on Reddit, find user pain points and complaints, validate a product or niche idea, do competitor and market research, track subreddit trends over a date range, or discover which subreddits discuss a topic. Also use when the user mentions 'Reddit research', 'Reddit 调研', 'search Reddit', 'subreddit discovery', 'niche validation', 'pain points', 'user complaints', or 'Reddit trends'. Requires REDDAPI_API_KEY. For B2B lead scoring, see reddit-leads; for a bare API reference, see reddit-search-api.
Discover B2B leads from Reddit using AI-powered lead scoring via reddapi.dev Leads API. Finds high-intent signals, scores them 0-100, and classifies by lead type (pain_point, solution_request, complaint, feature_request, comparison). Perfect for competitor poaching, pain point discovery, and sales prospecting.
Search Reddit posts by meaning via the reddapi.dev index.
| 生成学术论文配图：LaTeX/TikZ 代码（结构化图表，直接嵌入论文）或 draw.io XML （技术路线图、汇报配图）。自动按论文领域风格设计，编译验证后交付。
| 写出高质量、一次过编译、编辑安全的 TikZ/LaTeX 配图代码的工程基础技能。 教 agent 用「按构造布局」(positioning/fit/chains/anchor) 而非「手填绝对坐标」， 附 8 条硬约束、canonical 箭头、before/after 范例、一个静态检查入口 (lint.sh)。 tikz layout、latex figure code、tikz 编译报错、CJK 中文图渲染成色块。
Use when executing an approved Krypton plan, GOAL.md, or implementation plan that already defines intent, ownership, contract, cutover, task boundaries, and acceptance evidence. Use for main-agent execution with explorer, plan-reviewer, reviewer, maintainer, or verifier gates.
Use when a user has a feature request, bugfix, refactor, migration, architecture change, or product goal and needs an implementation plan before coding. Use especially when wrong ownership, duplicate paths, stale contracts, weak evidence, or unclear cutover would make plausible agent work dangerous.
Claude Skills — questions
Answers built from the skills we actually parsed.