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 14 hours ago
49,492 skills
- bulk-rnaseqK-Dense-AI/scientific-agent-skillsPrepares bulk RNA-seq FASTQ, Salmon, STAR or featureCounts output for gene-level differential expression. Covers nf-core/rnaseq and standalone quantification, biological replication, strandedness, reference provenance, validated count assembly and a PyDESeq2 handoff. Use for FASTQ-to-counts analysis, nf-core/rnaseq configuration, STAR/Salmon quantification, or building a counts matrix for DESeq2. For single-cell data use scanpy; for statistical fitting alone use pydeseq2.ScienceNo warnings★ 56.1K↓ —
- get-available-resourcesK-Dense-AI/scientific-agent-skillsDetects host inventory and effective CPU, memory, disk, scheduler, container, and accelerator limits when a user asks for resource-aware planning or before a clearly resource-sensitive local workload. Produces a redacted JSON snapshot and conservative planning helpers without stress tests or assuming visible host hardware is usable.TestingNo warnings★ 56.1K↓ —
- steve-jobs-design-reviewwondelai/skillsReview designs, products, and features with Steve Jobs' standards: ruthless simplicity, focus, and end-to-end excellence. Use when the user mentions "Steve Jobs review", "design review", "product review", "what would Steve do", "insanely great", "this feels too complicated", "too many features", "product taste", "saying no", or "is this good enough to ship". Also trigger when critiquing a UI, feature, or roadmap for focus and simplicity, cutting scope to the essential, or pressure-testing the whole experience from first run to daily use. Covers the simplicity audit, the no list, design-is-how-it-works, end-to-end ownership, demo culture, and a Jobs-style review protocol with binary verdicts. For visual design fundamentals, see refactoring-ui. For usability audits, see ux-heuristics. For detail polish, see microinteractions.DesignNo warnings★ 2.6K↓ —Also in 2 other repos
- videodbsickn33/agentic-awesome-skillsVideo and audio perception, indexing, and editing. Ingest files/URLs/live streams, build visual/spoken indexes, search with timestamps, edit timelines, add overlays/subtitles, generate media, and create real-time alerts.MediaNo warnings★ 49.1K↓ —
- relsa-severity-assessmentK-Dense-AI/scientific-agent-skillsSupports multivariate severity assessment and exploratory endpoint-time score forecasting for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-based foRcast forecasting. Use when combining welfare readouts — body weight or weight loss, body temperature, clinical or nesting scores, biomarkers, activity, heart rate, burrowing, wheel running — into one severity score per animal per day, when asking which animals are at risk of reaching a humane endpoint at a specified future observation time, when defining attention/danger zones or thresholds on a severity scale by kernel density estimation, or when reporting severity for a 3Rs, refinement, animal-welfare, or EU Directive 2010/63/EU severity-assessment context. Covers directionality ("turned" variables), baseline normalization, reference sets, RELSA weights, ARIMA prediction intervals, and RMSE/PICP/MPIW evaluation.ScienceNo warnings★ 56.1K↓ —
- 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↓ —
- nature-citationYuan1z0825/nature-skillsFind and verify Nature/CNS-family literature supporting manuscript claims, with claim-to-source mapping and reference-manager export. Use for Nature系列引用、CNS支撑文献、分段补引用 when this journal scope is requested; use broader literature search for unrestricted sources.OtherNo warnings★ 52.2K↓ —
- release-helperSahir619/fable-methodEnsures configuration and code changes are released correctly. Use PROACTIVELY whenever you edit config.json, change any setting, or fix a configuration bug in this project, so the change reaches production.WritingNo warnings★ 2.3K↓ —
- gevetyLeoYeAI/agent-master-skillsAccess your Gevety health data - biomarkers, healthspan scores, biological age, supplements, medications, medical profile, activities, strength training, erg results, daily actions, 90-day health protocol, upcoming tests, lab reports, health documents, and health contentTestingNo warnings★ 2.2K↓ —
- mandat-aufnahmeKlotzkette/claude-fuer-deutsches-rechtFür Mandat-Intake: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- mahnbescheidKlotzkette/claude-fuer-deutsches-rechtFür Mahnverfahren – Paragrafen 688 ff. ZPO: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- bau-vob-agbKlotzkette/claude-fuer-deutsches-rechtFür Bau VOB/B AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- kaltstart-triageKlotzkette/claude-fuer-deutsches-rechtFür Patentrecht — Allgemein: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- agents-best-practicesDenisSergeevitch/agents-best-practicesUse this skill when designing, generating an MVP blueprint for, auditing, troubleshooting, refactoring, or explaining an agentic harness for any domain. Covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs: agent loops, tool design, record provenance, interactive presentation, user-memory lifecycles, environment-adaptive tools, speculative tool execution, late-bound capabilities, permissions, system prompts, planning, goals, always-on agents and durable runtime, adaptive agent teams, context compaction, memory, skills, MCP/external connectors, public-board communications, realtime voice agents, hardware agents and board deployment, self-refining recursive harnesses, programmable context, continual refinement, observability, evals, prompt caching, agent-legible environments, feedback loops, and safety.DevOpsNo warnings★ 2.4K↓ —
- inso-plKlotzkette/claude-fuer-deutsches-rechtFür Mandantenkommunikation: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Insolvenzrecht.OtherNo warnings★ 1.8K↓ —
- imsgLeoYeAI/agent-master-skillsiMessage/SMS CLI for listing chats, history, watch, and sending.EngineeringNo warnings★ 2.2K↓ —
- bmlehKlotzkette/claude-fuer-deutsches-rechtFür Legistik-Werkstatt — Allgemein: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- scenario-luma-videoscenario-labs/skillsUse when generating or editing video with Luma Ray models on Scenario via MCP: cinematic text-to-video, image-to-video from a start frame, start plus end frame anchors, seamless looping clips, HDR output, restyling footage while preserving motion with edit strengths and face, pose, depth, or trajectory controls, reframing to another aspect ratio by outpainting, or budget prompt edits on real footage. Keywords: Luma, Dream Machine, Ray 3.2, Ray 3, Modify Video, Reframe, T2V, I2V, V2V, loop, HDR.MediaNo warnings★ 2.2K↓ —
- hivemind-goalsactiveloopai/hivemindCreate, track and update team goals via the Deeplake virtual filesystem at memory/goal/. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.EngineeringNo warnings★ 1.6K↓ —
- nvidiaLeoYeAI/agent-master-skillsBuy at Nvidia | Manage compatible cards, wallets & payments. Financial management for Agents and OpenClaw bots.FinanceNo warnings★ 2.2K↓ —
- webapp-testinggithub/awesome-copilotToolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.TestingNo warnings★ 40.8K↓ —
- kaltstart-interviewKlotzkette/claude-fuer-deutsches-rechtFür /kaltstart-interview: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Produkthaftung und Produktrecht.PlanningNo warnings★ 1.8K↓ —
- portaljs-add-mapdatopian/portaljsRender a GeoJSON dataset on an interactive Leaflet map in the Views section of a dataset's showcase. Installs react-leaflet and a Map component, then renders the map for the chosen dataset. Use when a dataset's data is geographic and a map view is needed alongside the showcase's default metadata and download.MediaNo warnings★ 2.4K↓ —
- translatefeiskyer/claude-code-settingsTranslate English or Japanese tech articles into natural, fluent Chinese. Use whenever the user asks for Chinese translation, says "translate to Chinese" or "翻译", or provides English/Japanese content (pasted text or a file) to convert into Chinese. Chinese output only — not for translating into other languages.OtherNo warnings★ 1.7K↓ —
auto-empirical-research-skills
brycewang-stanford/Auto-Empirical-Research-Skills
ScienceUpdated 3 days ago
From the author
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows, or an end-to-end run from raw data all the way to a finished Word (.docx) manuscript, without reading the entire repository at once.
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill auto-empirical-research-skills -a claude-code
Installs to .claude/skills/auto-empirical-research-skills/ · Each command fetches the skill straight from GitHub with the open skills CLI.
No download: this skill’s licence (CC-BY-SA-4.0) does not let us redistribute its files. The install commands fetch them from GitHub instead.
What it can touch
Instructions onlyNo network use seenLicence: CC-BY-SA-4.0
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Files (23)
- .gitignore
- .gitmodules
- .nojekyll
- .pre-commit-config.yaml
- CHANGELOG.md
- CITATION.cff
- CODE_OF_CONDUCT.md
- CONTRIBUTING.md
- INSTALL.md
- LICENSE
- Makefile
- README-en.md
- +11 more