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 11 hours ago
49,492 skills
- benefits-and-leavecbrock84/headcountDesigns and runs employee benefits and leave — health and retirement plans, leave policy, cost and renewal, and the administration that keeps them compliant. Use this to design or review a benefits package, prepare for a renewal, write leave policy, handle a leave request, or decide what benefits are worth their cost.DesignNo warnings★ 2.6K↓ —
- mirrord-cimetalbear-co/mirrordHelp users set up mirrord in CI pipelines for testing against real Kubernetes environments. Use when users want to run end-to-end tests, integration tests, or automated tests in CI using mirrord to connect to staging/shared clusters.TestingNo warnings★ 5.4K↓ —
- openpivK-Dense-AI/scientific-agent-skillsPerforms Particle Image Velocimetry (PIV) analysis with OpenPIV. Use when extracting velocity fields from PIV image pairs, analyzing fluid dynamics or flow visualization experiments, cross-correlating interrogation windows, validating and replacing spurious PIV vectors, or computing vorticity, strain rate, and turbulence statistics from measured velocity fields.MediaNo warnings★ 56.1K↓ —Also in 2 other repos
- onekgpdK-Dense-AI/scientific-agent-skillsQueries the 1000 Genomes Project dataset (3,202 whole-genome-sequenced individuals, GRCh38) at the level of individual participants. Use when a question is about individuals or variants in the 1000 Genomes Project cohort: which individuals carry variants matching specific criteria in a gene or region, which individuals are homozygous-reference at a position, which variants exist in the dataset or carried by specified individuals in a gene or region, the relatedness between two specified individuals. Variants are returned with 1000 Genomes allele frequencies (AF), gnomAD v4.1 exome and genome AF, AlphaMissense score, and HGVSp annotations.ScienceNo warnings★ 56.1K↓ —Also in 2 other repos
- portaljs-migratedatopian/portaljsMigrate (harvest) datasets between open-data platforms. Reads CKAN, a DCAT-US /data.json catalog (DKAN, ArcGIS Hub, data.gov), a DCAT / DCAT-AP RDF feed (JSON-LD, Turtle, or RDF/XML), Socrata, OpenDataSoft, or an ArcGIS FeatureServer, and writes them to a static PortalJS catalog or pushes them into a CKAN instance over its API. Use when moving datasets from an external open-data platform into a PortalJS portal, or bridging one CKAN instance to another.WritingNo warnings★ 2.4K↓ —
- 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↓ —
- ressort-bmlehKlotzkette/claude-fuer-deutsches-rechtFür Ressort-Heranführung BMLEH: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- ressort-bmuknKlotzkette/claude-fuer-deutsches-rechtFür Ressort-Heranführung BMUKN: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- maintenance-and-reliabilitycbrock84/headcountKeeps production assets available — ranking equipment by consequence of failure, setting preventive and predictive intervals, sizing spares, and moving a plant off reactive maintenance. Use this to build or fix a maintenance program, decide what to put on a PM schedule, diagnose repeat failures on one asset, justify spares inventory, or work out why a plant that maintains everything still has unplanned downtime.PlanningNo warnings★ 2.6K↓ —
- customer-success-managementcbrock84/headcountRuns the ongoing relationship with accounts after the sale — segmenting coverage against account value, building a health score that predicts rather than describes, running reviews customers find worth attending, forecasting renewals honestly, and finding expansion that follows usage instead of quota. Use this to design a customer success motion, decide who gets a named contact, work out why renewals surprise you, or fix a health score everyone ignores.DesignNo warnings★ 2.6K↓ —
- ressort-bmwsbKlotzkette/claude-fuer-deutsches-rechtFür Ressort-Heranführung BMWSB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- gke-ai-troubleshooting-tpu-vbar-oomgoogle/skillsDiagnoses and prevents vbar_control_agent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbar_control_agent crashes, memory cgroup OOMs in serial console logs, tpu-device-plugin metrics checksum corruption errors, or custom TPU metrics collection conflicts on GKE TPU v6e nodes. Don't use for general non-TPU container OOM troubleshooting or standard GKE node lifecycle operations.OfficialProductivityNo warnings★ 21.9K↓ —
- learning-materials-designcbrock84/headcountDesigns worksheets, workbooks and practice material that actually teach — sequencing difficulty, managing cognitive load, writing instructions a child can follow unaided, and building answer keys that hold up. Use this to design or fix a worksheet or workbook, decide how much practice a skill needs, structure a page so it can be completed without an adult reading it aloud, or diagnose material that looks right and does not work.DesignNo warnings★ 2.6K↓ —
- kaltstart-interviewKlotzkette/claude-fuer-deutsches-rechtFür Kaltstart-Interview: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Prozessrecht.PlanningNo warnings★ 1.8K↓ —
- cloud-logging-finopsgoogle/skillsAudits Cloud Logging costs for a Google Cloud project: the charges for log entries written to log buckets, the services, log streams and severities that drive them, and the log sinks that route them. Reconciles Cloud Billing export costs with Cloud Monitoring volume metrics, and generates a FinOps report with charts and copy-paste exclusion filters. Use when auditing Cloud Logging spend, finding logging waste, identifying top logging contributors, generating log cost reduction reports, or creating log sink exclusion filters. Don't use for querying log entries (use cloud-logging-query-generation), configuring Cloud Monitoring alerts, or querying metrics/traces.OfficialWritingNo warnings★ 21.9K↓ —
- molfeatK-Dense-AI/scientific-agent-skillsFeaturizes small molecules with Molfeat for QSAR/QSPR, chemical similarity, virtual screening, and molecular ML. Covers ECFP/MACCS fingerprints, RDKit descriptors, pharmacophores, pretrained embeddings, configuration persistence, and molecule-to-label alignment.ScienceNo warnings★ 56.1K↓ —Also in 2 other repos
- gke-app-onboardinggoogle/skillsManages GKE application onboarding, covering containerization, deployment manifests, and migration. Use when onboarding or deploying an application to GKE for the first time, or containerizing an app for GKE. Don't use for general GKE cluster administration or upgrades (use gke-basics or gke-upgrades instead).OfficialDevOpsNo warnings★ 21.9K↓ —
- scvi-toolsK-Dense-AI/scientific-agent-skillsFits probabilistic models for single-cell omics, including scVI batch integration, scANVI annotation, totalVI CITE-seq, MultiVI RNA/ATAC integration, and posterior differential expression. Use for generative modeling, reference mapping, multimodal analysis, or model-based uncertainty; use scanpy for standard preprocessing and exploratory analysis.OtherNo warnings★ 56.1K↓ —
- statistical-powerK-Dense-AI/scientific-agent-skillsCalculates sample sizes and statistical power for study planning. Applies when someone asks "how many subjects/samples/replicates do I need", wants an a priori power analysis, a minimum detectable effect (MDE), a power curve, or needs to justify a sample size for a grant, IRB protocol, or pre-registration. Covers closed-form power for t-tests, ANOVA, proportions, correlations, chi-square, and regression, plus simulation-based (Monte Carlo) power for complex designs — logistic/Poisson regression, mixed models, cluster-randomized trials, survival, and interactions. Also handles requests that only mention an effect size, alpha, or "80% power" without saying "power analysis" explicitly. For laying out the study (randomization, blocking, factorial/DOE, crossover, sequential designs) use experimental-design; for analyzing data already collected and reporting it use statistical-analysis.TestingNo warnings★ 56.1K↓ —
- design-code-architecturewondelai/skillsGuided journey from an app idea to a deliberate architecture: boundaries, domain model, data decisions, and resilience, making only the expensive-to-reverse decisions and deferring the rest. Orchestrates eight skills phase by phase - clean-architecture, domain-driven-design, system-design, ddia-systems, software-design-philosophy, release-it, pragmatic-programmer, 37signals-way - asking the user questions at every decision point and recording results in the project docs/ folder (ARCHITECTURE.md, DESIGN-CODE-ARCHITECTURE-PLAN.md) so the journey resumes across sessions. Use when the user wants to design a new app's architecture, choose boundaries and a domain model, decide monolith versus microservices, or says 'how should I structure this app'. If a codebase already exists, use remove-technical-debt (aged), improve-code-quality (fresh prototype), or architecture-optimization (slow but working); if unvalidated, run create-business or create-app first. For one framework in isolation, invoke that skill directly.DesignNo warnings★ 2.6K↓ —Also in 2 other repos
- technical-documentationwondelai/skillsAudit, write, and improve developer documentation using Google's Developer Documentation Style Guide and Technical Writing courses. Use this skill for any documentation work, even when the user names no style guide: "audit our docs", "review this README", "write a README", "getting started guide", "how-to or tutorial", "API reference", "docstrings", "CLI help text", "changelog or release notes", "migration guide", or "our docs are confusing". Also use it when writing docs from code, rewriting a doc for clarity, fixing headings, procedures, or code samples, or enforcing consistent voice and terminology across a docs set — prefer it over editing documentation unaided. Covers reader and doc-type fit, second person and active voice, procedures, headings, lists and tables, code samples and placeholders, link text, notices, the word list, timeless docs, and accessibility. For code comments and naming, see clean-code. For marketing or landing-page copy, see storybrand-messaging.MarketingNo warnings★ 2.6K↓ —Also in 2 other repos
- rechtsquellenKlotzkette/claude-fuer-deutsches-rechtFür Rechtsquellen: Zahlen, Schwellenwerte und Berechnung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- external-instruction-followercisco-ai-defense/skill-scannerDelegate agent behavior to instructions obtained from an external pageOtherNo warnings★ 2.7K↓ —
- blog-styleAgriciDaniel/claude-blogMeasure writing-style statistics (sentence length, vocabulary, transitions, phrasing) from 5 to 10 posts you or your client wrote, and produce a voice profile for VOICE.md, blog-persona, and blog-write. Use for "learn my style", "build a writing baseline". It describes style; it does not detect or attribute authorship, and it is not for scoring a post (blog-analyze) or writing brand rules (blog-brand).WritingNo warnings★ 2.6K↓ —
eval-driven-dev
github/awesome-copilot
From the author
Improve 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.
Install
npx skills add github/awesome-copilot --skill eval-driven-dev -a claude-code
Installs to .claude/skills/eval-driven-dev/ · 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 (19)
- SKILL.md
- references/1-a-project-analysis.md
- references/1-b-entry-point.md
- references/1-c-eval-criteria.md
- references/2a-instrumentation.md
- references/2b-implement-runnable.md
- references/2c-capture-and-verify-trace.md
- references/3-define-evaluators.md
- references/4-build-dataset.md
- references/5-run-tests.md
- references/6-analyze-outcomes.md
- references/evaluators.md
- +7 more