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.
49,409 skills from 2,375 repositories · updated 15 hours ago
49,407 skills
- smtp-penetration-testingzebbern/claude-code-guideThis skill should be used when the user asks to "perform SMTP penetration testing", "enumerate email users", "test for open mail relays", "grab SMTP banners", "brute force email credentials", or "assess mail server security". It provides comprehensive techniques for testing SMTP server security.TestingNo warnings★ 4.7K↓ —
- industriekundenKlotzkette/claude-fuer-deutsches-rechtFür Industriekunden — Sonderregelungen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- 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★ 56K↓ —Also in 2 other repos
- open-notebookK-Dense-AI/scientific-agent-skillsOrganizes research with the self-hosted Open Notebook alternative to NotebookLM. Supports source ingestion (PDFs, web pages, audio, video, and Office documents), cited document chat, text and vector search, notes, custom transformations, and multi-speaker podcasts. Use when automating Open Notebook through its REST API or configuring its local or cloud AI providers, including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral.MediaNo warnings★ 56K↓ —
- blog-factcheckAgriciDaniel/claude-blogVerify statistics and claims in blog posts by fetching cited source URLs and checking if the claimed data actually appears on the page. Extracts all load-bearing claims (statistics, product or policy claims, ranking and comparative claims, named sources), validates cited URLs before fetching, and scores match confidence (exact match 1.0, paraphrase 0.7-0.9, not found 0.0). Flags uncited claims as UNVERIFIED and marks a claim verified only when this run fetched the source and found the passage. Checks that a source says what the post says it says; it cannot prove the source is true or verify first-hand experience. Use when the user says "fact check", "verify statistics", "check sources", "factcheck". Report only; not for rewriting posts (blog-rewrite).WritingNo warnings★ 2.6K↓ —
- 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↓ —
- stripeLeoYeAI/agent-master-skillsWith CreditClaw and backed by Stripe, you can shop anywhere.OtherNo warnings★ 2.2K↓ —
- pgvector-semantic-searchtimescale/pg-aiguideUse this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.DataNo warnings★ 1.9K↓ —
- backup-and-recoverycbrock84/headcountProtects and restores data — backup coverage and scope, retention, immutability against ransomware, and proving restores actually work. Use this to design a backup regime, verify restores, plan retention, protect backups from ransomware, or recover from data loss.DesignNo warnings★ 2.6K↓ —
- what-if-oracleK-Dense-AI/scientific-agent-skillsSupports structured what-if scenario analysis for research planning, experimental contingencies, and scientific project decisions. Explores favorable, reference, adverse, wild-card, contrarian, and second-order scenarios with explicit assumptions, evidence, and decision triggers. Use to stress-test a research plan under uncertainty; scenario narratives do not estimate causal effects or calibrated forecast probabilities.TestingNo warnings★ 56K↓ —
- experimental-designK-Dense-AI/scientific-agent-skillsDesigns experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use statistical-analysis.DesignNo warnings★ 56K↓ —
- aeonK-Dense-AI/scientific-agent-skillsThis skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.PlanningNo warnings★ 56K↓ —Also in 2 other repos
- solution-explorationcbrock84/headcountExplores the problem and the range of possible approaches before any code is written — clarifying what is actually being asked, surfacing options with their tradeoffs, and converging on one. Use this at the start of any feature, component, or behavior change, when a request is ambiguous, when the first idea is the only idea on the table, or when a design decision needs pressure-testing before commitment.TestingNo warnings★ 2.6K↓ —
- literature-reviewK-Dense-AI/scientific-agent-skillsConducts systematic, scoping, and narrative literature reviews using PubMed, arXiv, bioRxiv, Semantic Scholar, and other appropriate sources. Use for research synthesis, reproducible literature searches, screening, citation checking, or preparing Markdown and PDF reviews. Tracks search coverage, records versus studies, and evidence limitations; supports meta-analysis planning but does not supply a meta-analysis engine.EngineeringNo warnings★ 56K↓ —
- onboarding-and-offboardingcbrock84/headcountDesigns the joining and leaving experience — first-day readiness, ramp to productivity, knowledge capture, and clean exits. Use this to design or fix onboarding, shorten time to productivity, structure a leaver process, capture knowledge before someone leaves, or coordinate the access and asset steps around a joiner or leaver.DesignNo warnings★ 2.6K↓ —
- compensation-and-levelingcbrock84/headcountBuilds and maintains the leveling framework and pay structure — level definitions, salary bands, benchmarking, pay equity, and how raises and promotions are decided. Use this to design or revise leveling, set or adjust salary bands, benchmark against market, handle a compensation request or counteroffer, run a review cycle, or diagnose pay compression and equity issues.DesignNo warnings★ 2.6K↓ —
- scientific-writingK-Dense-AI/scientific-agent-skillsDrafts, revises, and audits scientific manuscripts or reports with explicit evidence provenance, reporting-guideline coverage, authorship accountability, confidentiality controls, and local consistency checks. Use for manuscript sections, references, declarations, tables, figures, or submission preparation when scientific accuracy and traceability matter.ScienceNo warnings★ 56K↓ —
- cloud-trace-queryinggoogle/skillsQuery Cloud Trace spans, filter by latency thresholds or error status, correlate distributed traces with Cloud Logging, and diagnose latency bottlenecks across Google Cloud services. Use when investigating slow requests, analyzing trace hierarchies, or resolving latency regressions. Do NOT use for querying non-GCP telemetry or database query optimization outside Cloud Trace.OfficialDevOpsNo warnings★ 21.8K↓ —
- pr-dashboardgithub/awesome-copilotOpen a GitHub PR dashboard in the browser. Use when the user asks to see their pull requests, open the PR dashboard, show PRs for a date range, or check PR status. Trigger phrases include "show my PRs", "open PR dashboard", "pull request dashboard".BrowserNo warnings★ 40.8K↓ —
- 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★ 21.8K↓ —
- omero-integrationK-Dense-AI/scientific-agent-skillsInspects and automates microscopy data workflows against OMERO.server with omero-py, BlitzGateway, OMERO CLI, tables, annotations, ROIs, rendering, and documented OMERO.web APIs. Use this skill for scoped OMERO inventory, metadata export, import/export planning, or reviewed write workflows.MediaNo warnings★ 56K↓ —
- cloud-infrastructurecbrock84/headcountDesigns and runs cloud infrastructure — environments, infrastructure as code, networking and isolation, scaling, and cost. Use this to design a cloud environment, control infrastructure spend, set up environment separation, plan for scale or region failure, or review infrastructure someone configured by hand.DevOpsNo warnings★ 2.6K↓ —
- historic_sql_patternsKaelio/ktxIdentify recurring cross-table historic-SQL analytical intents from a bounded pattern shard and emit typed pattern evidence for deterministic wiki projection.DataNo warnings★ 1.6K↓ —
- regulatory-compliancecbrock84/headcountIdentifies which regulations apply and builds the program that keeps you inside them — obligation mapping, controls, monitoring, and responding to regulators. Use this to work out what applies to your business, stand up a compliance program, prepare for a regulatory exam or certification, respond to a finding, or assess exposure before entering a new market.LegalNo warnings★ 2.6K↓ —
mini-context-graph
github/awesome-copilot
ProductivityUpdated yesterday
From the author
A 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.
Install
npx skills add github/awesome-copilot --skill mini-context-graph -a claude-code
Installs to .claude/skills/mini-context-graph/ · 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
Runs bundled scriptsNo network use seenLicence: MIT
Safety checks on SKILL.md
- Ships scripts we have not reviewedLow
Why 89
Security85
Provenance95
Maintenance100
Licence100
Adoption71
Files (15)
- SKILL.md
- references/ingestion.md
- references/lint.md
- references/ontology.md
- references/retrieval.md
- scripts/config.py
- scripts/contextgraph.py
- scripts/template_agent_workflow.py
- scripts/tools/__init__.py
- scripts/tools/documents_store.py
- scripts/tools/graph_store.py
- scripts/tools/index_store.py
- +3 more