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.
49,492 skills from 2,391 repositories · updated 8 hours ago
49,492 skills
- founder-offerJakeschincariol/founder-skillBuilds an offer too good to refuse. Lists every problem the buyer hits on the way to the result they want, turns each into a solution, trims to what is cheap to deliver and valuable to the buyer, and stacks it with honest bonuses, a guarantee the CFO can afford, real urgency and a clear name. Scores it on the value equation (outcome, likelihood, time, effort) and re-tests it on a quick buyer panel. Use when the user says "make my offer better", "why won't people buy", "what should I include", "guarantee", "bonuses", "grand slam offer", or after the panel shows people passing.TestingNo warnings★ 2.4K↓ —
- ingest_triageKaelio/ktxClassify and resolve conflicts detected during bundle ingest (structural duplicates, definitional contradictions, near-duplicate clusters, re-ingest changes, evictions).OtherNo warnings★ 1.6K↓ —
- scenario-storyboardsscenario-labs/skillsUse when a story must unfold across a sequence of Scenario images: a comic page or strip, manga or webtoon panels, a children's storybook, a film, game, or ad storyboard, animatic pre-viz frames, or any shot list where the same characters and world must persist from panel to panel and dialogue must stay legible. Keywords: storyboard, comic, panel, sequential art, storybook, shot list, pre-viz, animatic, scene to scene, character consistency.MarketingNo warnings★ 2.2K↓ —
- geomasterK-Dense-AI/scientific-agent-skillsSupports geospatial research workflows for remote sensing, vector and raster GIS, spatial statistics, terrain and network analysis, and machine learning for Earth observation. Use when processing satellite imagery, aligning coordinate systems and raster grids, accessing STAC catalogs, analyzing geospatial time series, or implementing scientific GIS workflows in Python, R, Julia, JavaScript, C++, Java, Go, or Rust.ScienceNo warnings★ 56.1K↓ —Also in 1 other repo
- lookml_ingestKaelio/ktxMap a LookML view/model/explore into ktx semantic layer sources. Covers the LookML to ktx primitive table, provenance tagging, and three worked examples (overlay, standalone from derived_table, standalone with sql_always_where). Load when the turn contains `.lkml` content.OtherNo warnings★ 1.6K↓ —
- look-and-feelKlotzkette/claude-fuer-deutsches-rechtFür Corporate-Cowork-Look — Design und Ausgabestandard: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Corporate-Kanzlei. Route: look-and-feel.DesignNo warnings★ 1.8K↓ —
- clean-codewondelai/skillsWrite readable, maintainable code through disciplined naming, small functions, and clean error handling. Use when the user mentions "clean up this code", "this function is too long", "code smells", "naming conventions", "boy scout rule", "single responsibility", or "unit test quality". Also trigger when reviewing a pull request for readability, untangling a messy function, debating comment styles, or improving error-handling patterns. Covers SRP, comment discipline, formatting, and unit testing. For refactoring techniques, see refactoring-patterns. For architecture and dependency rules, see clean-architecture.EngineeringNo warnings★ 2.6K↓ —Also in 2 other repos
- liteparseK-Dense-AI/scientific-agent-skillsLocal document and PDF parsing that returns spatial text with bounding boxes. Use for extracting text from PDFs, DOCX, Office files, and images; running OCR on scans; producing layout-preserved JSON for RAG; batch-ingesting folders of papers; or rendering pages to PNG for multimodal agents. Distinguishing capabilities are spatial text boxes, Markdown, page raster output, and local parsing with optional custom HTTP OCR.DocumentsNo warnings★ 56.1K↓ —Also in 1 other repo
- eval-driven-devgithub/awesome-copilotImprove AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.TestingNo warnings★ 40.8K↓ —
- gruen-fehlerkatalogKlotzkette/claude-fuer-deutsches-rechtFür Grün Fehlerkatalog: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- hooked-uxwondelai/skillsDesign habit-forming product loops using the Hook Model (Trigger, Action, Variable Reward, Investment). Use when the user mentions "users arent coming back", "habit formation", "engagement loops", "habit zone", or "the manipulation matrix". Also trigger when designing notification or re-engagement strategies, building streaks or progress systems, or analyzing why users stop after signup. Covers ethics evaluation and onboarding for habits. For friction reduction and B=MAP, see improve-retention. For viral sharing, see contagious.DesignNo warnings★ 2.6K↓ —Also in 2 other repos
- marine-carbonate-chemistryK-Dense-AI/scientific-agent-skillsSolves seawater carbonate chemistry with PyCO2SYS for chemical oceanography, ocean acidification, and marine carbon-cycle research. Use for paired total alkalinity, dissolved inorganic carbon, pH, or seawater pCO2/fCO2 measurements; carbonate speciation; aragonite and calcite saturation; Revelle factors; lab-to-in-situ temperature and pressure corrections; and measurement uncertainty propagation. Applies to carbonate-system calculations, not general aqueous speciation or air-sea gas-flux estimation.ScienceNo warnings★ 56.1K↓ —
- wiki_captureKaelio/ktxktx's knowledge base - wiki pages for durable, reusable business knowledge. Covers capture workflow for user preferences, metric definitions, organizational conventions, and cross-references between wiki pages and semantic-layer sources. Loaded by the post-turn memory-agent only. The research agent reads wiki via `wiki_read`/`wiki_search` but does not write it.ScienceNo warnings★ 1.6K↓ —
- statistical-analysisK-Dense-AI/scientific-agent-skillsGuided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required sample sizes, or write up results - even if they never name a specific test. Covers t-tests, ANOVA, chi-square, correlation, regression, non-parametric and Bayesian methods. For low-level model APIs, see the statsmodels and pymc skills.TestingNo warnings★ 56.1K↓ —
- sigma_ingestKaelio/ktxExtract durable ktx wiki knowledge from staged Sigma data model specs and workbook summaries. Load for WorkUnits with unitKey sigma-data-models or sigma-workbooks.PlanningNo warnings★ 1.6K↓ —
- display-glasses-with-jetpack-compose-glimmerUpdatedandroid/skillsProvides guidelines for developing projected Android XR apps for display glasses using the Jetpack Compose Glimmer UI toolkit. Covers Glimmer design principles, workflows, and interaction models for the glasses form factor. Use this skill to build an Android XR Augmented Experience app with Jetpack Compose Glimmer. Don't use for audio-only AI glasses without a display, non-glasses Android XR headsets (spatial panels or 3D volumes with Jetpack Compose for XR), or phone and tablet Material 3 UIs.OfficialDesignNo warnings★ 10.3K↓ —
- huashu-topic-genalchaincyf/huashu-skills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。OtherNo warnings★ 2.2K↓ —
- stable-baselines3K-Dense-AI/scientific-agent-skillsTrains and evaluates single-agent reinforcement learning with Stable Baselines3 (PPO, SAC, DQN, TD3, DDPG, A2C), Gymnasium custom environments, vectorized rollouts, callbacks, and checkpoint normalization. Applies to reproducible RL experiments, continuous control, discrete actions, and SB3-Contrib recurrent or masked policies.OtherNo warnings★ 56.1K↓ —
- lernplanKlotzkette/claude-fuer-deutsches-rechtFür Staatsexamen-Lernplan: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- pkpd-modelingK-Dense-AI/scientific-agent-skillsPharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".OtherNo warnings★ 56.1K↓ —
- xurlLeoYeAI/agent-master-skillsA Twitter research and content intelligence skill focused on attracting WordPress and Shopify clients. Use to analyze Twitter profiles, threads, and conversations for: (1) Identifying what small agency founders and eCommerce brands are discussing; (2) Understanding pain points around WordPress performance, Shopify CRO, and development bottlenecks; (3) Extracting high-performing content angles; (4) Turning insights into authority-building posts; (5) Converting Twitter intelligence into business leverage for clear content angles, strong positioning, and qualified inbound leads.ScienceNo warnings★ 2.2K↓ —
- changelogcodeaholicguy/ai-devkitAI DevKit · Update CHANGELOG.md Unreleased items from git commits since the latest release. Use when users ask to update changelog/release notes from recent commits, with one concise line per commit and commit/PR links.EngineeringNo warnings★ 1.7K↓ —
- sandbox-npm-installgithub/awesome-copilotInstall npm packages in a Docker sandbox environment. Use this skill whenever you need to install, reinstall, or update node_modules inside a container where the workspace is mounted via virtiofs. Native binaries (esbuild, lightningcss, rollup) crash on virtiofs, so packages must be installed on the local ext4 filesystem and symlinked back.DevOpsNo warnings★ 40.8K↓ —
- unterlagen-lueckenKlotzkette/claude-fuer-deutsches-rechtFür Unterlagen und Lücken: ordnet Akte, Belege und Lücken; Ergebnis: Dokumentenmatrix mit Nachforderungsliste. Fachgebiet: Technik-Governance.OtherNo warnings★ 1.8K↓ —
pr-lens
coldteadotai/pr-lens
PlanningUpdated 6 days ago
From the author
WHAT: Draws a code change or part of a codebase as an animated architecture, data-flow or data-model diagram, on its own or in a pull request. WHEN: asked to diagram, visualise or explain a change, a system or a schema change, or when a pull request should carry a diagram. KEYWORDS: PR Lens, diagram, architecture, data flow, data model, schema, ERD, visualise, visualize, pull request
Install
npx skills add coldteadotai/pr-lens --skill pr-lens -a claude-code
Installs to .claude/skills/pr-lens/ · 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 onlyNo network use seenLicence: MIT
Safety checks on SKILL.md
No warnings.
Why 89
Security100
Provenance80
Maintenance100
Licence100
Adoption54
Files (2)
- LICENSE
- SKILL.md