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. 80 149 files from 1 774 authors, of which 62 489 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.
Generate auditor-ready compliance evidence from Datadog Audit Trail for SOC 2 and PCI DSS. Maps framework controls to specific query patterns and produces formatted output.
Answer "who did what" security questions from Audit Trail — deletions, config changes, login activity, permission changes, actions from a specific user or IP.
Investigate a potentially compromised Datadog API key — timeline of actions, geo/IP breakdown, endpoints called, anomaly flags, and remediation steps.
Investigate a Datadog product usage or cost spike by correlating Usage Metering data (when/what spiked) with Audit Trail config changes (who changed what in the preceding window).
> Datadog Browser SDK — RUM, Logs, Session Replay, profiling, product analytics, and error tracking setup, configuration, and migration. Use when upgrading Browser SDK versions, setting up RUM or Logs, or troubleshooting browser-side Datadog instrumentation.
> Upgrade Datadog Browser SDK from v4 to v5. Use when encountering removed options like proxyUrl, sampleRate, replaySampleRate, premiumSampleRate, allowedTracingOrigins, or deprecated APIs like addRumGlobalContext, removeUser, or when a project references datadoghq-browser-agent.com CDN with /v4/ paths.
> Upgrade Datadog Browser SDK from v6 to v7. Use when encountering removed options like betaEncodeCookieOptions, allowFallbackToLocalStorage, trackBfcacheViews, usePciIntake, changed APIs like forwardErrorsToLogs, startDurationVital, stopDurationVital, or when a project references datadoghq-browser-agent.com CDN with /v6/ paths.
> Upgrade Datadog Browser SDK from v5 to v6. Use when encountering removed options like useCrossSiteSessionCookie, sendLogsAfterSessionExpiration, or when dropping IE11 support, or when a project references datadoghq-browser-agent.com CDN with /v5/ paths.
Log management - search, archives, metrics, and cost control.
Monitor management - list, search, file-based create, and alerting best practices.
Datadog CLI (Rust). OAuth2 auth with token refresh.
Load when investigating a specific flaky test. Gets history, failure pattern, and category, then recommends fix, quarantine, or escalate.
Load when investigating a failing PR CI pipeline or checking PR health. Attributes each CI failure as flaky, infra, or regression, proposes a targeted action, and reports code coverage and quality/security status.
> Generate a BYOD ownership preferences reference table for a customer. Walks through preference types, generates CSV, and provides upload instructions (UI, API, cloud storage, or Terraform). Use when asked about BYOD setup, preferences reference table, k9_ownership_preferences, or ownership customization.
Guide for running a local containerized DNS server. Use this when asked to run an acceptance test or to run a test with the prefix `TestAcc`.
Security forensics for git repos, AI skills, and MCP servers. Audits dependencies, detects prompt injection, credential theft, runtime dynamism, manifest drift, known CVEs, CISA KEV (actively exploited) vulns, and 2026 attack patterns. Not for fixing vulnerabilities or pentesting.
| Cross-agent self-inspection of your AI-agent stack. Audits skills, MCP servers, hooks, plugins, commands, credentials, and memory files across Claude Code, Codex, OpenClaw, and NanoClaw. Produces a structured inventory and narrative briefing with cross-ecosystem risk analysis. Use when the user asks to audit their own setup, check what they have installed, review their agent stack security posture, or understand cross-tool interactions. Use when a user has accumulated skills/plugins/MCP servers over time and wants visibility into their attack surface. Use after installing new skills or plugins. Do NOT use for vetting external code before install (that is repo-forensics). Do NOT use for incident response during active attacks. Do NOT use for fixing or patching vulnerabilities (forensify is read-only).
| 当系统提示面向编程代理（Coding Agent）场景时调用。适用于构建代码编辑、文件操作、Git 工作流、自动化编程助手的系统提示。不适用于代码解释或教学场景（无文件修改），不适用于 DevOps 基础设施配置（非代码层），不适用于纯对话式代码问答（无工具调用）。
| 当系统提示需要防御提示注入、越狱攻击、社会工程、内容信任边界突破等安全威胁时调用此 Skill。适用于构建 AI Agent、聊天机器人、文档处理助手等任何接受外部输入的系统提示。不适用于纯内部工具调用场景或已完全隔离的沙箱环境，也不适用于 UI 布局或响应格式设计。
| 当需要为 AI 设计记忆存储、检索、应用和更新机制时调用此 skill。典型场景包括：设计持久化记忆架构（用户偏好、历史上下文、项目知识）、定义记忆的创建/读取/更新/删除生命周期、实现静默记忆应用（不在回复中透露记忆内容）、管理敏感记忆边界。 不适用于：定义工具接口（tool-specification）、定义安全规则（safety-guardrails）、定义人格风格（personality-system）。 关键 trigger 信号：AI 需要跨会话记住用户信息、记忆内容可能敏感、需要在回复中隐式应用记忆而非显式引用、用户要求"记住这个"。
| 当系统提示面向移动端（手机、平板）场景时调用。适用于 iOS/Android 应用内 AI 助手、移动端聊天界面、响应式输出的系统提示设计。不适用于桌面端优先的场景，不适用于移动端 UI 开发（非提示层），不适用于语音场景（语音场景使用 voice-optimization）。
| 当系统提示词需要定义 AI 如何分类用户意图、路由到不同处理流程、决定澄清策略和自主度级别时调用此 Skill。适用于多任务型 AI 助手、客服机器人、编程工具、研究助手等需要结构化对话管理的场景。不适用于：纯问答型系统（无任务执行）、单轮交互（无对话状态）、简单的 prompt 模板（无路由逻辑）。当需求仅涉及"输出什么格式"而非"如何决定输出什么"时，应该用 output-formatting 而非本 Skill。
| 当系统提示词需要设计 token 预算分配、上下文压缩策略、延迟加载机制、记忆持久化方案时调用此 Skill。适用于长对话 AI 助手、代码编辑器集成、研究型 Agent、多会话系统等需要精细管理上下文窗口的场景。不适用于：单轮交互系统（无上下文管理需求）、纯无状态 API（无对话历史）、简单的 prompt 模板设计。当需求聚焦于"如何搜索外部信息"而非"如何管理已有信息"时，应该用 search-integration 而非本 Skill。
| 当系统提示需要设计引用格式、信息溯源机制、来源标注系统时调用。适用于文档问答、搜索增强生成（RAG）、代码引用、浏览器辅助等需要让用户追溯信息来源的场景。不适用于纯创作类输出（如故事、诗歌），不适用于无需溯源的常识问答，也不适用于注入防御（虽然两者都涉及内容可信度）。
| 当系统提示词需要设计多代理协作架构、子代理专业化分工、代理间上下文隔离与传递机制、任务生命周期管理时调用此 Skill。适用于 AI Agent 平台、多工具编排系统、代码审查流水线、跨应用协作场景等。不适用于：单代理系统（无委派需求）、简单工具调用（无子代理概念）、纯 API 编排（无 AI 决策）。当需求聚焦于"单代理内的对话路由"而非"多代理间的任务分配"时，应该用 conversation-flow 而非本 Skill。
| 当需要为 AI 产品定义核心身份、角色声明和能力边界时调用此 skill。典型场景包括：设计新 AI 产品的 system prompt 首段、为不同场景创建差异化角色（如教学助手 vs 编程代理）、重新定义 AI 与用户的关系框架。 不适用于：纯人格风格调优（应使用 personality-system）、安全规则制定（应使用 safety-guardrails）、工具集成（应使用 tool-specification）。 关键 trigger 信号：产品需要 AI 有明确自我认知、多个角色共享底层能力但身份不同、需要限制 AI 在特定领域内运作、用户会问"你是谁"。
| 当需要为 AI 系统设计多层安全防线、内容过滤策略和伦理边界时调用此 skill。典型场景包括：设计拒绝策略与升级机制、防御 prompt 注入攻击、实现领域特定安全规则（教育、医疗、金融等）、定义 AI 的价值观锚点。 不适用于：定义工具操作权限（应使用 tool-specification）、定义 AI 身份（persona-design）、调整输出风格（personality-system）。 关键 trigger 信号：AI 涉及敏感话题、需要设计"拒绝回答"策略、存在 prompt 注入风险、特定行业合规要求、需要多层防御而非单一规则。
| 当系统提示词需要为 AI 输出定义格式规范、长度约束、风格指南或反"AI味"策略时调用此 Skill。适用于聊天机器人、CLI 工具、移动端助手、设计生成器等需要自适应输出的场景。不适用于：纯内容生成（无格式要求）、内部推理链设计、安全策略制定。当需求仅涉及"用什么格式返回数据"而非"如何控制输出的风格与密度"时，这不是最佳 Skill。
| 当需要在基础身份之上叠加可切换的人格风格层时调用此 skill。典型场景包括：为同一产品提供多种人格选项（如 GPT-5.1 的 friendly/professional/quirky 模式）、设计人格切换机制、防止人格泄露到用户内容中。 不适用于：定义 AI 的核心角色定位（应使用 persona-design）、设计安全规则（应使用 safety-guardrails）。 关键 trigger 信号：产品需要多种语气风格、用户可切换 AI 性格、需要防止 AI 人格污染用户文本、存在 "personality" 或 "tone" 配置项。
| 当系统提示面向语音交互场景（语音助手、语音搜索、有声回答、电话客服 AI）时调用。适用于需要将文本输出优化为口语表达的系统提示设计。不适用于纯文本聊天界面，不适用于语音合成（TTS）技术选型，不适用于图像/视频多模态场景。
| 当系统提示词需要定义 AI 模型何时搜索、如何搜索、搜索哪些数据源、以及如何处理搜索结果时调用此 Skill。适用于所有涉及实时知识检索的 AI 产品设计——聊天机器人、研究助手、企业知识库问答等。不适用于：纯离线场景（无搜索能力的环境）、已完全内化的知识问答（如数学推导）、创意生成任务。当需求仅涉及"从本地文件读取内容"而非"联网检索外部信息"时，这不是最佳 Skill。
| 当需要为 AI 定义工具接口、设计调用规范、实现工具发现与编排机制时调用此 skill。典型场景包括：设计 AI agent 的工具集、定义 JSON Schema/XML/TypeScript 格式的工具描述、实现工具权限控制与并行调度、设计子代理委托架构。 不适用于：定义 AI 身份（persona-design）、安全规则（safety-guardrails）、记忆存储（memory-system）。 关键 trigger 信号：AI 需要调用外部 API 或服务、工具数量超过 10 个需要发现机制、需要区分工具权限层级、需要子代理并行执行、工具调用涉及敏感操作需要审批。
> Audit, design, and implement AI agent harnesses for any codebase. A harness is the constraints, feedback loops, and verification systems surrounding AI coding agents — improving it is the (set up components), Design (full strategy). Use whenever the user mentions harness engineering, agent guardrails, AI coding quality, AGENTS.md, CLAUDE.md setup, agent feedback loops, entropy management, AI code review, vibe coding quality, harness audit, harness score, AI slop, agent-first engineering. Also trigger when users want to understand why AI agents produce bad code, make their repo work better with AI agents, set up CI/CD for agent workflows, design verification systems, or scale AI-assisted development. Proactively suggest when discussing AI code drift or controlling AI-generated code quality.
> Systematic dataset profiling protocol for empirical research. Use this skill when the user has a new dataset and wants to understand it before analysis — including unit of observation, variable definitions, panel structure, data quality, and descriptive statistics. Trigger on phrases like "explore this data", "profile this dataset", "what's in this data", "understand this dataset", "describe this data", "what are the variables", "check the panel structure", or any request to examine a dataset before running regressions.
> Use this skill whenever working with the Canvas LMS REST API — including creating or updating modules, pages, and files for a course, building sync scripts, managing course structure programmatically, or uploading files and linking them in pages. Trigger this skill any time the user mentions Canvas, LMS, course sync, module pages, or file uploads to Canvas. Also use when writing or debugging any Python script that calls the Canvas API.
> Generate LaTeX Beamer slide decks using my defined style and conventions. Use this skill whenever the user asks to create slides, a presentation, a lecture deck, or Beamer content — for teaching.
> End-of-milestone audit of a research project's `Code/` folder against the paper and outputs. Surfaces drift between scripts, YAML headers, the script registry, outputs, raw data, and the paper. Categorises findings as MUST-FIX or SUGGESTED and proposes fixes one at a time for the user to confirm. Use this skill when the user says "code sweep", "sweep the code", "run a code sweep", "audit my code folder", "check code freshness", "is everything up to date", "any stale outputs", "audit code consistency", or similar — typically before a paper submission, milestone, or share. Extends `script-registry`; builder rather than redefining either.
> Per-project glossary of key definitions, abbreviations, and command-phrases, stored in `GLOSSARY.md` at the project root. Use this skill when the user defines or asks about a project-specific term — variable names, dataset or database names, acronyms — or sets up a command-phrase (a phrase that maps to an action, e.g. "push" = commit and push the paper to GitHub). Triggers "what does X mean here", "what does X stand for", "from now on X means Y", "show the glossary", "what's in our glossary", and "remove X from glossary". passing, or when you hit an undefined abbreviation or variable name in their code or data. Loaded at session start by `/spin-up` so command-phrases stay active.
> Audit a finance paper against Alex Edmans' "Learnings From 1,000 Rejections" Exposition. Reads the paper's current LaTeX, applies the framework with per-research-question execution checks, and generates a structured report with severity-labeled findings. Use when the user says "edmans audit", "audit my paper", "run the Edmans check", "referee readiness", "submission audit", "check paper against Edmans", or "pre-submission check".
> Two-phase code audit workflow for empirical research scripts. Use this skill when the user asks to review, audit, check, validate, or verify R or Python research code — especially code that processes licensed or sensitive data (WRDS, CRSP, WellDatabase, PLIDA). Also use when the user says "check my code", "review this script", "does this look right", or "audit my analysis."
> Audit and fix Beamer slide decks for compilation errors, layout problems, and visual issues. Use this skill whenever the user says "check my slides", "fix my slides", "the slides don't compile", "text is running off the page", "slides look wrong", or after generating a Beamer deck to verify it before delivering. Also use when the user mentions overfull boxes, overlapping content, broken images, or any Beamer formatting issue.
> Digital pinboard for quick project notes, reminders, and ideas. Use this skill when the user wants to jot down a note, reminder, to-do, paper to read, idea, or data issue — including phrases like "pin this", "note to self", "remind me to", "add to pinboard", "I need to remember to", "check out this paper", "look into this later", "jot this down", "don't let me forget", or any quick note the user wants saved for later. Also use when the user says "show my pinboard", "what's on my pinboard", "mark X as done", or "clear my pinboard."
> Seven-audit editorial review protocol for academic finance working papers. Use this skill when the user asks to review, edit, audit, or critique a working paper, manuscript, or draft — including "run The Editor", "review my paper", "audit this draft", "check if this is ready for submission", "what would Referee 2 say", or any request to evaluate a paper for journal submission. Also use when the user mentions R&R, revise and resubmit, or responding to referee reports.
> Conventions for writing empirical finance R code with data.table, fixest, arrow, and ggplot2. Use this skill whenever writing, reviewing, refactoring, or debugging R scripts for panel data, event studies, DiD, IV/2SLS, regressions, or data pipelines — even if the user just says "write some R code" or "clean this data."
> Reference for writing and improving Claude Code skills. Use when the user asks to create a new skill, improve an existing skill, turn a conversation workflow into a reusable skill, or says anything like "make this a skill", "save this as a skill", or "let's capture this."
Use when creating a new `.Rmd` script in `Code/`, editing the `registry:` YAML block of an existing script in `Code/`, moving a `Code/*.Rmd` into `_Archive/`, or when the user says "update registry", "show registry", or "which script makes X". Before writing any new `Code/*.Rmd` script, read `Code/REGISTRY.md` first and surface existing matches before starting fresh. After any YAML change, run `Code/_Claude Scripts/build_registry.R` to refresh `Code/REGISTRY.md`.
> Produce a structured summary of an academic working paper or published article. Use this skill when the user shares a paper, asks to summarise a paper, says "what's this paper about", "review this paper", "summarise this for me", or provides a PDF/link to an academic article.
> Start-of-session orientation routine that briefs Claude on the current state of a project before work begins. Use this skill when the user says "spin up", "spin it up", "let's go", "start up", "spin up the project", "punch it chewy", or any variant signalling they want a session kickoff divergence), CLAUDE.md and README read, most-recent session log read (focusing on "Where we left off"), PINBOARD.md open items, GLOSSARY.md load, and a short synthesis of project state. Ends by asking what to work on today.
> End-of-session cleanup routine that captures all session work before context is lost. Use this skill when the user says "wrap up", "wrap-up", "let's wrap it up", "let's wrap up", "wind down", "end session", "that's it for today", "save and close", "let's call it", "close out", "done for today", or any indication they are finishing a work session and want everything documented before starting fresh.
Skill do analizy i tworzenia umów według polskiego prawa, ze szczególnym uwzględnieniem umów B2B, IP i IT (body leasing, NDA, wdrożenia, SaaS, przeniesienie praw autorskich, ugody). Powstał w Kancelarii Radców Prawnych Żurawska Piotrowski i Wspólnicy (ktzr.pl). Używaj zawsze gdy użytkownik prosi o przeanalizowanie polskiej umowy, audyt ryzyk umownych, wygenerowanie nowej umowy w stylu KTZR, dodanie/edycję klauzuli, sprawdzenie spójności umowy lub gdy wkleja/załącza polski dokument umowny do oceny. Stosuj również gdy pojawia się pojęcie "Złote Reguły KTZR", "essentialia negotii", "baza klauzul KTZR" lub gdy użytkownik wspomina o kancelarii KTZR / swojej kancelarii.
Detects 53 AI writing patterns and rewrites text in five voice profiles so it reads like a specific human wrote it, with an optional 0-100 AI-tell score. Use when text sounds AI-generated or like a chatbot, when preparing a blog post, README, or LinkedIn post for publication, when auditing prose for AI tells, or when editing a Markdown file in place. Triggers on phrases like "humanize this", "make this sound less AI", "make this sound human", "remove AI tells", "does this read like ChatGPT", and "rewrite so it does not sound AI-generated". Pure Markdown, zero dependencies, no network calls.
>- Write contextual commits that capture intent, decisions, and constraints alongside code changes. Use when committing code, finishing a task, or when the user asks to commit. Extends Conventional Commits with structured action lines in the commit body that preserve WHY code was written, not just WHAT changed.
>- Reconstruct and narrate the current development context from contextual commits. Run at session start, when resuming work, or when switching branches. Produces a brief, conversational summary of where things stand.
Apply 2026's top graphic design trends to any creative brief. Based on Kittl × Savee's 2026 Design Trends Report (10 trends + 2 honorable mentions), backed by Adobe, Figma, and Pinterest data. Use when: **Designing a brand identity** — pick the right aesthetic for your audience; **Creating social media assets** — use trending visual languages that perform; **Briefing a designer or AI image tool** — give precise style direction with vocabulary and references; **Refreshing a visual identity** — know what's rising vs saturating; **Building mood boards** — combine trends intentionally with data-backed rationale.
Transformez une image 2D en modèle 3D animé prêt pour le web ou le jeu en moins de 30 minutes, en utilisant le workflow Dilum Sanjaya (Hunyuan3D + Mixamo). Use when: **Créer un personnage 3D pour un site web** - Mascotte, avatar, illustration interactive; **Prototyper un asset de jeu** - Character design, props, environnements; **Produire du contenu marketing 3D** - Produits rotatifs, personnages animés; **Convertir des illustrations existantes** - Logo, mascotte, character design → 3D; **Tes...
Build profitable Google Ads campaigns by applying Perry Marshall's 80/20 principles to paid search optimization Use when: **Setting up a new Google Ads account** from scratch; **Optimizing existing campaigns** that are underperforming; **Structuring campaigns** for maximum quality score and ROI; **Applying 80/20 thinking** to identify high-leverage optimizations; **Scaling profitable campaigns** without wasting budget
Calculate A/B test statistical significance. Use when: determining if test results are significant; calculating required sample size; estimating test duration; analyzing conversion experiments; making data-driven decisions
Analyze paid advertising performance across channels and recommend budget reallocation to maximize ROAS and minimize CAC. Use when: planning quarterly ad budget allocation, diagnosing underperforming ad channels, deciding whether to scale spend on a channel, calculating marginal ROI across Google Ads, Meta, LinkedIn, or TikTok, rebalancing media mix after performance shifts, or setting up a test-and-scale framework for new channels.
Claude Skills — questions
Answers built from the skills we actually parsed.