Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
49,399 skills from 2,375 repositories · updated 15 minutes ago
49,399 skills
- code-tourgithub/awesome-copilotUse this skill to create CodeTour .tour files — persona-targeted, step-by-step walkthroughs that link to real files and line numbers. Trigger for: "create a tour", "make a code tour", "generate a tour", "onboarding tour", "tour for this PR", "tour for this bug", "RCA tour", "architecture tour", "explain how X works", "vibe check", "PR review tour", "contributor guide", "help someone ramp up", or any request for a structured walkthrough through code. Supports 20 developer personas (new joiner, bug fixer, architect, PR reviewer, vibecoder, security reviewer, and more), all CodeTour step types (file/line, selection, pattern, uri, commands, view), and tour-level fields (ref, isPrimary, nextTour). Works with any repository in any language.EngineeringNo warnings★ 40.8K↓ —
- blog-brandAgriciDaniel/claude-blogEstablish durable brand and voice context for cross-skill consumption. Generates BRAND.md (audience, positioning, do/don't editorial rules, taboo phrases, competitor differentiation) and VOICE.md (existing persona JSON re-expressed as readable prose), both written to the project root. When present, the blog orchestrator loads these files, fenced as untrusted data, for write, rewrite, brief, outline, calendar, and strategy workflows. Pairs with blog-persona, which manages the structured persona JSON. Use when the user says "blog brand", "create brand context", "BRAND.md", "VOICE.md", "establish editorial brand". Not for learning a voice from existing posts (blog-style) or managing persona JSON (blog-persona).WritingNo warnings★ 2.6K↓ —
- autoskillK-Dense-AI/scientific-agent-skillsAnalyzes user-requested Screenpipe history windows to detect repeated research workflows, match existing scientific skills, and stage new skill drafts or composition recipes for review. Requires a reachable Screenpipe HTTP API, normally on localhost:3030. Detection and embedding inference run locally; the selected LLM receives redacted app/title cluster summaries and matched skill descriptions. Use only when the user explicitly asks to analyze their recent work and propose skills.ScienceNo warnings★ 56K↓ —Also in 1 other repo
- verify-claimspedrohcgs/claude-code-my-workflowRun Chain-of-Verification (CoVe) on a draft or a block of text with factual claims. Spawns the `claim-verifier` agent in a fresh context (never a conversation fork) so it never sees the draft — then reports which claims are supported, contradicted, or unverifiable. Use when user says "verify these citations", "check the claims in X", "did I hallucinate anything", "fact-check this draft", "run CoVe on this", or after any text generation that asserts facts about papers, datasets, or numerical results. NOT for style/grammar review (use `/proofread`) or substance review (use `/review-paper`).ScienceNo warnings★ 1.7K↓ —
- foundry-agentic-loopgithub/awesome-copilotBuild agentic solutions on Microsoft Foundry, GitHub and Azure: hosted agents, toolbox tools and skills, Foundry IQ grounding and a React/FastAPI app. Three modes: rapid prototyping in an existing Foundry project; spec-driven development (SDD), where the foundry-agentic-loop-workflow runs Specify, Implement, Verify and Deploy to create the Foundry project and deploy with azd, or one phase runs alone; and Improve, which refines this skill and the workflow from past runs. Use for Agentic Loop requests and canvas actions, or end-to-end agent solutions from architecture to Azure deployment. Not for isolated Azure administration or unrelated UI edits.DevOpsNo warnings★ 40.8K↓ —
- mom-testwondelai/skillsTalk to customers without leading them using Mom Test rules: discuss their life not your idea, ask about specifics in the past, and talk less. Use when the user mentions "customer interviews", "validate my idea", "users say they want it but dont buy", "leading questions", "The Mom Test", "customer feedback bias", or "interview script". Also trigger when preparing user-research questions, interpreting ambiguous feedback, or designing customer-discovery that avoids false positives. Covers commitment and advancement, avoiding compliments, and extracting signal from noise. For product-market fit, see jobs-to-be-done. For rapid prototype testing, see design-sprint.TestingNo warnings★ 2.6K↓ —Also in 2 other repos
- usus-modernusKlotzkette/claude-fuer-deutsches-rechtFür Usus Modernus: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- blog-localizeAgriciDaniel/claude-blogDeep cultural adaptation of an already translated blog post for one target market: local examples, CTAs, legal references, statistic sources, and formality (Sie/du, tu/vous). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets. Use when the user says "localize blog", "cultural adaptation", "adapt for Germany", "lokalisieren", "localiser", "adaptar" and a translation already exists. Not for translating (use blog-translate), auditing a folder of translations (use blog-locale-audit), or the full write-translate-localize pipeline (use blog-multilingual).WritingNo warnings★ 2.6K↓ —
- datanalysis-credit-riskgithub/awesome-copilotCredit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.OtherNo warnings★ 40.8K↓ —
- scholar-evaluationK-Dense-AI/scientific-agent-skillsProvides qualitative-first, evidence-traceable developmental review of scholarly works and audit low-stakes research-assessment rubrics with optional local quality controls. Never use for ranking people or consequential decisions.ScienceNo warnings★ 56K↓ —
- clinical-decision-supportK-Dense-AI/scientific-agent-skillsPrepares and validates research-only clinical decision-support evaluation, evidence-profile, cohort, survival, biomarker/model, privacy, and governance artifacts. Supports aggregate or synthetic research documentation and traceability, excluding patient care and live clinical operation.ScienceNo warnings★ 56K↓ —
- dsh-client-ui-uxNewqufei1993/skills-hub设计、实现或审查客户端 UI、响应式布局、交互状态、焦点或失败反馈时使用，结合真实运行界面验证用户体验。DesignNo warnings★ 1.9K↓ —
- networkxK-Dense-AI/scientific-agent-skillsCreates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph file formats, or drawing network topologies. Common applications include social, biological, transportation, and citation networks.ScienceNo warnings★ 56K↓ —Also in 1 other repo
- scenario-fan-camscenario-labs/skillsUse when putting a person from a photo into live-broadcast crowd footage with Scenario: a stadium or arena fan-cam reaction, a jumbotron or kiss-cam moment, a spectator cutaway at a match or concert, a courtside or front-row sighting, or a personalized sports-TV still that then animates into video. Keywords: fan cam, crowd reaction, jumbotron, stadium screen, kiss cam, broadcast cutaway, spectator, crowd shot, sports TV, courtside, arena.MediaNo warnings★ 1.9K↓ —
- context-statuspedrohcgs/claude-code-my-workflowShow current context status and session health. Use to check how much context has been used, whether auto-compact is approaching, and what state will be preserved.ProductivityNo warnings★ 1.7K↓ —
- scenario-soniloscenario-labs/skillsUse when adding sound to a video or generating standalone audio with Sonilo models on Scenario via MCP: text-to-sound-effects, text-to-music, video-to-sound-effects or video-to-music from a clip, scoring silent AI video, foley, ambience, muxed video-to-video variants returning the clip with the new track mixed in, keeping speech while replacing music, or per-segment sound control. Keywords: Sonilo V1.1, SFX, soundtrack, score, keepSpeechVocal, segments, royalty-free.MediaNo warnings★ 1.9K↓ —
- huashu-speech-coachalchaincyf/huashu-skills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。OtherNo warnings★ 2.2K↓ —
- scenario-multi-referencescenario-labs/skillsUse when one image must be composed from several reference pictures through the Scenario MCP server, each lending one thing: the character from one, the place, pose, style, light, palette, material, outfit, or layout from others. Also when a reference leaks into the result (its object, colors, or face showing where it should not) or a reference's role is ignored. Keywords: multi-reference, reference roles, combine references, style reference, pose reference, give each picture a job.MediaNo warnings★ 1.9K↓ —
- google-cloud-filestore-nfs-browsergoogle/skillsInspects, searches, and reads files and POSIX metadata on Filestore (NFS) instances on Google Cloud without local NFS client packages or root privileges. Use when browsing Filestore shares, searching files, reading remote logs, or inspecting file attributes; don't use for Cloud Storage buckets, Cloud NetApp Volumes, Persistent Disks, or modifying/deleting files.OfficialBrowserNo warnings★ 21.8K↓ —
- scenario-image-editingscenario-labs/skillsUse when editing an existing image on Scenario through MCP with a tool model, not a new generation: upscale or enhance to 2x, 4K, 8K, super resolution, 3D LUT color grade, color correction, posterize, solarize, vignette, film grain, blur, sharpen, glow, chromatic aberration, oilify, cubism, crystallize, dodge and burn, tint, desaturate, expand or uncrop, reframe an aspect ratio, resize to exact pixels, slice tiles, contact sheet, split into layers, remove a background or watermark, vectorize.MediaNo warnings★ 1.9K↓ —
- labarchive-integrationK-Dense-AI/scientific-agent-skillsIntegrates with the official LabArchives ELN REST-like API and Inventory API v1. Supports regional endpoint selection, signed-request construction, user authorization and UID flows, local LA container validation, and verified LabArchives integration workflows.EngineeringNo warnings★ 56K↓ —
- hivemind-graphactiveloopai/hivemindQuery the local AST-derived code graph (functions, classes, calls, imports) for structural codebase questions — what calls X, what does Y import, where is Z defined, blast radius of a change. The graph rebuilds automatically after each agent turn; use hivemind_graph_search and hivemind_graph_neighborhood tools (no manual build step).EngineeringNo warnings★ 1.6K↓ —
- hivemind-graphactiveloopai/hivemindQuery the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems exist?", "what's the impact of changing this?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).PlanningNo warnings★ 1.6K↓ —
- hivemind-graphactiveloopai/hivemindQuery the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what is the architecture / which subsystems exist?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).PlanningNo warnings★ 1.6K↓ —
verify
codeaholicguy/ai-devkit
TestingUpdated yesterday
From the author
AI DevKit · Enforce evidence-based completion claims — require fresh command output before reporting success. Use when completing any task, fixing a bug, finishing a phase, running tests, building, deploying, or making any "it works" claim.
Install
npx skills add codeaholicguy/ai-devkit --skill verify -a claude-code
Installs to .claude/skills/verify/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Download .zip
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Instructions onlyUses the networkLicence: APACHE-2.0
Safety checks on SKILL.md
No warnings.
Why 89
Security100
Provenance79
Maintenance100
Licence100
Adoption52
Files (2)
- SKILL.md
- agents/openai.yaml