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.
49,493 skills from 2,391 repositories · updated 8 minutes ago
49,491 skills
- memorycodeaholicguy/ai-devkitAI DevKit · Use the memory CLI as a durable knowledge layer. Search before non-trivial work, store verified reusable knowledge, update stale entries, and avoid saving transcripts, secrets, or one-off task progress.ProductivityNo warnings★ 1.7K↓ —
- branchenfokusKlotzkette/claude-fuer-deutsches-rechtFür Branchenfokus: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- pybammK-Dense-AI/scientific-agent-skillsSimulates lithium-ion battery charge, discharge and rest experiments with PyBaMM, records parameter-set provenance, checks mesh and solver sensitivity, and compares predicted voltage curves with measured cycling data. Use for SPM or DFN electrochemical battery modeling, C-rate protocols, voltage cutoffs, parameter studies and numerical validation of battery simulations.OtherNo warnings★ 56.1K↓ —Also in 2 other repos
- revenue-recognitioncbrock84/headcountDetermines when and how revenue is recognized — performance obligations, contract terms that change the answer, and the deal structures that create accounting problems. Use this to work out how a contract should be recognized, review a non-standard deal before it is signed, understand deferred revenue, or spot terms that would delay or reverse recognition.FinanceNo warnings★ 2.6K↓ —
- archify-tuningtt-a1i/archifyImprove Archify diagram accuracy, visual quality and complete authoring speed with fewer repairs. Use for generation experiments or evaluating changes to layout, routing, diagnostics, authoring instructions and acceptance rules against actual diagrams and agent traces.OtherNo warnings★ 93.3K↓ —
- nature-responseYuan1z0825/nature-skillsDraft, audit, or revise responses to peer review, revision cover letters, and marked-manuscript or LaTeX revision packages. Use for 审稿意见回复、逐点回复、返修信、 rebuttals and edits to existing response drafts. Initial-submission materials belong to nature-writing; simulated peer review belongs to nature-reviewer.WritingNo warnings★ 52.2K↓ —
- blogAgriciDaniel/claude-blogFull-lifecycle blog engine with 31 sub-skills, 12 templates, 100-point scoring, and 5 agents. Routes requests to the right sub-skill: writing, rewriting, analysis, outlines, audits, schema, charts, images, repurposing, AI citation SEO, FLOW prompts, topic clusters, and multilingual publishing. Optimized for Google rankings, E-E-A-T, and AI citations. Supports any platform. Use when the user asks to create, revise, analyze, plan, translate, localize, audit, or repurpose blog content, or invokes a /blog subcommand. Do not activate merely because the word "blog" appears in an unrelated coding, theme-debugging, database, log-analysis, or definition request.WritingNo warnings★ 2.6K↓ —
- docs-sync-auditgithub/awesome-copilotRun a read-only documentation drift audit for a feature, PR, branch, release, API, configuration change, workflow, CLI, package, or repository area. Use when the user asks whether docs are stale, missing, inconsistent with code, or need updates after code changes. Checks README files, setup guides, API docs, env docs, changelogs, examples, comments, generated docs, and user-facing instructions. This is not a general code review; it compares what the docs claim against what the code does.EngineeringNo warnings★ 40.8K↓ —
- mini-context-graphgithub/awesome-copilotA persistent, compounding knowledge base combining Karpathy's LLM Wiki pattern with a structured knowledge graph. Ingest documents once — the LLM writes wiki pages, extracts entities/relations into the graph, and stores raw content for evidence retrieval. Knowledge accumulates and cross-references; it is never re-derived from scratch.ProductivityNo warnings★ 40.8K↓ —
- anpassenKlotzkette/claude-fuer-deutsches-rechtFür /anpassen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Produkthaftung und Produktrecht.OtherNo warnings★ 1.8K↓ —
- energievertraegeKlotzkette/claude-fuer-deutsches-rechtFür Energie-Verträge — Strukturierung und Prüfung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- reverse-engineer-marketingNewcoreyhaines31/marketingskillsWhen the user wants to reverse engineer how another company grew and copy what worked. Also use when the user mentions 'reverse engineer,' 'how did X grow,' 'how does X get customers,' 'growth teardown,' 'marketing teardown,' 'GTM teardown,' 'growth blueprint,' 'what is X doing for marketing,' 'what made X take off,' 'copy X's playbook,' 'X's distribution strategy,' 'what content works for X,' 'funnel hack,' 'map their funnel,' or 'watch what X is doing.' Builds a dated log of a company's moves against its traffic curve from public data, sign-ups and demos, team interviews, and hidden signals (DNS, certificate logs, archives, sponsorships), compares it with the user's own data, and turns what lined up with growth into plays routed to the skill that runs each one. For a snapshot profile of a competitor's positioning, pricing, and features, see competitor-profiling. For comparison pages, see competitors. For why a single post went viral, see social.MarketingNo warnings★ 58.5K↓ —
- kaltstart-triageKlotzkette/claude-fuer-deutsches-rechtFür Factoring-Recht — Allgemein: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- portaljs-add-chartdatopian/portaljsAdd a chart (line, bar, area, pie, or scatter) to a dataset's showcase in a PortalJS portal. Installs recharts, writes a reusable Chart component, and renders it in the showcase Views section. Use when visualizing a dataset already registered in datasets.json.MediaNo warnings★ 2.4K↓ —
- hivemind-memoryactiveloopai/hivemindGlobal team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.ProductivityNo warnings★ 1.6K↓ —
- quellenkarteKlotzkette/claude-fuer-deutsches-rechtFür Betreuungsrecht Quellenkarte: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- pytdcK-Dense-AI/scientific-agent-skillsProvides Therapeutics Data Commons workflows through PyTDC for registry discovery, dataset access, task-aware splits, evaluator metrics, benchmark groups, and bounded molecular-oracle scoring. Use when working with TDC therapeutic ML datasets or benchmarks.ProductivityNo warnings★ 56.1K↓ —Also in 2 other repos
- chainaiLeoYeAI/agent-master-skillsEthereum & EVM blockchain CLI skill — sign messages, send tokens, swap via 1inch Fusion, check balances, broadcast transactions, and manage wallets across Ethereum and BNB Smart Chain.EngineeringNo warnings★ 2.2K↓ —
- taskcodeaholicguy/ai-devkitAI DevKit · Track dev-lifecycle / dev-debug progress on a durable task with the ai-devkit task CLI. Use to record phase, progress, next step, blockers, and validation evidence.ProductivityNo warnings★ 1.7K↓ —
- ai-seoLeoYeAI/agent-master-skillsWhen the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' or 'optimize for Claude/Gemini.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema-markup.MarketingNo warnings★ 2.2K↓ —
- pyhealthK-Dense-AI/scientific-agent-skillsBuilds and validates PyHealth clinical machine-learning pipelines for EHR, signals, imaging, and medical codes. Use for PyHealth dataset loading, MIMIC-III/IV, eICU or OMOP prediction tasks, patient-level evaluation, mortality/readmission/length-of-stay modeling, medication recommendation, sleep staging, Trainer checkpoints, and ICD/ATC/NDC/RxNorm mapping.ScienceNo warnings★ 56.1K↓ —Also in 1 other repo
- matlabK-Dense-AI/scientific-agent-skillsBuilds, reviews, migrates, and plans MATLAB or GNU Octave numerical workflows. Use for arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.TestingNo warnings★ 56.1K↓ —Also in 2 other repos
- pysamK-Dense-AI/scientific-agent-skillsProvides Python/HTSlib workflows for genomic files. Used when reading, querying, filtering, or writing SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, or tabix data with pysam, including pileup, coverage, indexing, and CRAM references.ScienceNo warnings★ 56.1K↓ —Also in 2 other repos
- industriekundenKlotzkette/claude-fuer-deutsches-rechtFür Industriekunden — Sonderregelungen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
relsa-severity-assessment
K-Dense-AI/scientific-agent-skills
From the author
Supports 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.
Install
npx skills add K-Dense-AI/scientific-agent-skills --skill relsa-severity-assessment -a claude-code
Installs to .claude/skills/relsa-severity-assessment/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Safety checks on SKILL.md
- Ships scripts we have not reviewedLow
Why 89
Files (9)
- SKILL.md
- assets/example_cohort.csv
- references/forecasting.md
- references/relsa-method.md
- references/thresholds-and-zones.md
- scripts/_common.py
- scripts/forecast_relsa.py
- scripts/kde_thresholds.py
- scripts/relsa_score.py