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 4 hours ago
49,492 skills
- 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↓ —
- google-cloud-filestore-auditinggoogle/skillsAudits Filestore instances on Google Cloud across projects for disaster recovery readiness (missing or stale backups), security access governance (overly permissive NFS export rules, 0.0.0.0/0 exposure, missing ROOT_SQUASH), and reliability compliance (Physical Zone Isolation PZI and Physical Zone Separation PZS). Use when assessing storage health posture, auditing NFS export permissions, identifying unprotected file shares, or validating zone failure domains. Don't use for Cloud Storage buckets, Persistent Disk, or NetApp Volumes.OfficialSecurityNo warnings★ 21.9K↓ —
- 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↓ —
- huashu-proofreadingalchaincyf/huashu-skills三遍审校降低AI检测率，让文章更有人味。当用户提到"AI味太重"、"像AI写的"、"降低AI检测率"、"审校"、"自然一些"时使用。WritingNo warnings★ 2.2K↓ —
- 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★ 56.1K↓ —
- aws-penetration-testingzebbern/claude-code-guideThis skill should be used when the user asks to "pentest AWS", "test AWS security", "enumerate IAM", "exploit cloud infrastructure", "AWS privilege escalation", "S3 bucket testing", "metadata SSRF", "Lambda exploitation", or needs guidance on Amazon Web Services security assessment.TestingNo warnings★ 4.7K↓ —
- 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★ 56.1K↓ —
- rowanK-Dense-AI/scientific-agent-skillsRowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.DevOpsNo warnings★ 56.1K↓ —Also in 2 other repos
- pruefenKlotzkette/claude-fuer-deutsches-rechtSteuert die Bearbeitung eines Phishingvorfalls von Sicherung und Zahlungszuordnung bis zum fertigen Bankbrief, Vermerk oder beauftragten Prozessentwurf. Trennt unverzügliche Erstattung, Betrugsverdachtsausnahme und späteren Rückgriff.OtherNo warnings★ 1.8K↓ —
- shapK-Dense-AI/scientific-agent-skillsExplain and audit machine-learning predictions with SHAP. Use for selecting SHAP explainers and maskers, computing and validating feature attributions, handling multi-output explanations, and producing local or global SHAP visualizations.OtherNo warnings★ 56.1K↓ —Also in 2 other repos
- 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
- 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★ 56.1K↓ —Also in 2 other repos
- incident-managementcbrock84/headcountRuns an operational incident from detection to closed action — declaring it and naming a commander, separating the people restoring service from the people communicating, keeping a timeline as it happens, deciding when it is over, and running a review that produces a small number of changes someone actually completes. Use this to set up an incident process, run one, work out why the same failure keeps recurring, or fix a review practice that generates findings nobody closes.EngineeringNo warnings★ 2.6K↓ —
- treatment-plansK-Dense-AI/scientific-agent-skillsFormats and structurally validates local treatment-plan documentation after clinical decisions have already been supplied and verified by authorized licensed professionals. Use for source traceability, clinician-authored intervention records, goals and checkpoints, shared-decision records, reconciliation handoffs, and release gates—not for clinical decision-making.PlanningNo warnings★ 56.1K↓ —
- 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↓ —
- data-management-planpedrohcgs/claude-code-my-workflowDraft a funder-compliant Data Management Plan (NSF DMP, NIH DMS Policy 2023, ERC, Horizon Europe) by composing the confidential-data and environment-capture primitives. Sections cover data description, formats/metadata, storage/backup, access/sharing, preservation/archiving, and roles. Use when user says "data management plan", "DMP", "DMSP", "NIH data sharing plan", "write the data plan for my grant", or when a grant proposal needs a data-management section. NOT a submission tool — produces a draft the user pastes into the funder portal (DMPTool, NIH ASSIST, Horizon Europe portal).PlanningNo warnings★ 1.7K↓ —
- scientific-slidesK-Dense-AI/scientific-agent-skillsBuilds slide decks and presentations for research talks. Used for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer.DocumentsNo warnings★ 56.1K↓ —
- shopLeoYeAI/agent-master-skillsClaw goes shopping. Give your claw a creditcard. Financial management for Agents and OpenClaw bots.FinanceNo warnings★ 2.2K↓ —
- spss-amos-sembrycewang-stanford/Auto-Empirical-Research-SkillsQuestionnaire structural equation modeling in the SPSS + AMOS workflow that Chinese management, psychology, education, nursing and tourism theses use — data cleaning of an SPSS .sav file, reverse coding, straight-lining, demographics, Harman common-method-bias test, Cronbach's alpha / CITC reliability, EFA (KMO, Bartlett), CFA convergent validity (standardized loadings, CR, AVE), discriminant validity (Fornell-Larcker, HTMT), model fit (chi2/df, CFI, TLI, RMSEA, SRMR), structural paths and hypothesis tests, bootstrap mediation with specific indirect effects, multi-group measurement invariance, and Hayes PROCESS models 1/4/6/7/8/14. One spec card drives an R/lavaan engine set to AMOS defaults and writes ready-to-run SPSS syntax (.sps), AMOS Program Editor VB.NET code, AMOS user-defined estimands, an AMOS drawing checklist with the numbers AMOS should show, Chinese three-line tables in Word, a results-chapter draft and a transparent model-modification log. Use when the user mentions SPSS, AMOS, SEM, structural TestingNo warnings★ 4.9K↓ —
- hivemind-graphactiveloopai/hivemindQuery the local AST-derived code graph (functions, classes, calls, imports) for structural codebase questions — what calls X, what does Y import, where is Z defined, blast radius of a change. The graph rebuilds automatically after each agent turn; use hivemind_graph_search and hivemind_graph_neighborhood tools (no manual build step).EngineeringNo warnings★ 1.6K↓ —
- hivemind-graphactiveloopai/hivemindQuery the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what is the architecture / which subsystems exist?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).PlanningNo warnings★ 1.6K↓ —
- eyeballgithub/awesome-copilotDocument analysis with inline source screenshots. When you ask Copilot to analyze a document, Eyeball generates a Word doc where every factual claim includes a highlighted screenshot from the source material so you can verify it with your own eyes.OtherNo warnings★ 40.8K↓ —
- spark-memory-thermal-opswshobson/agentsManage unified memory and thermals during long-running ML jobs on NVIDIA DGX Spark. Use when planning memory headroom for a training run on GB10, when a job OOMs on unified memory, or when monitoring temperature and power during multi-hour training.ProductivityNo warnings★ 42.2K↓ —
- market-entrycbrock84/headcountDecides whether and how to enter a new market — sizing demand from the bottom up rather than from a market report, testing whether your advantage transfers, choosing between organic entry, partnership and acquisition, sequencing the operational and regulatory work that entry actually requires, and setting the criteria that would tell you to stop. Use this to evaluate a new geography, segment or vertical, pressure-test an entry plan, or work out why a launched market never reached scale.TestingNo warnings★ 2.6K↓ —
hivemind-graph
activeloopai/hivemind
PlanningUpdated 13 hours ago
From the author
Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what is the architecture / which subsystems exist?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).
Install
npx skills add activeloopai/hivemind --skill hivemind-graph -a claude-code
Installs to .claude/skills/hivemind-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
Instructions onlyNo network use seenLicence: APACHE-2.0
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