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 16 hours ago
49,492 skills
- customer-researchcbrock84/headcountPlans, runs, and synthesizes customer research — interviews, surveys, win-loss analysis, and message testing — into findings that change decisions. Use this when the customer is being guessed at, before positioning or a major launch, when churn or conversion has an unexplained cause, or when a team is arguing from anecdotes. Also use to turn raw interview notes into usable findings.ScienceNo warnings★ 2.6K↓ —
- anschluss-routerKlotzkette/claude-fuer-deutsches-rechtFür Fluggastrechte — Allgemein: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- visual-reference-generationcbrock84/headcountProduces design reference imagery before implementation — screen concepts, layout directions, and flows for web or mobile that make a verbal brief concrete enough to argue with. Use this when a brief needs visualizing before anyone builds, when comparing layout directions, when handing a developer a target, or when stakeholders are describing different things with the same words.DesignNo warnings★ 2.6K↓ —
- product-requirementscbrock84/headcountWrites down what is being built so a team can build it and know when they are done — problem and success measure before solution, scope stated by exclusion, user-visible behavior including the states everyone forgets, acceptance criteria someone can test, and the open questions named rather than buried. Use this to write a specification, review one that is causing rework, or work out why a delivered feature technically matched the request and still was not what anyone wanted.PlanningNo warnings★ 2.6K↓ —
- data-governancecbrock84/headcountEstablishes ownership, definitions, quality, access, and lineage for the organization's data. Use this when metrics disagree between teams, when nobody knows which dataset is authoritative, when setting up data ownership or access policy, when data quality is unreliable, or before opening a dataset to a wider audience.OtherNo warnings★ 2.6K↓ —
- assuredworkloads-frameworks-navigatorgoogle/skillsActs as a Data Boundary Compliance Analyst that maps user compliance queries against Data Boundary Frameworks and cloud controls, validates matched resources, and recommends appropriate Frameworks or cloud controls. Use when mapping direct natural language workload requirements to Assured Workloads / Data Boundary Frameworks and cloud controls, browsing built-in Data Boundary frameworks, or identifying major requirement gaps. Don't use for non-Data-Boundary Compliance Manager posture assessments or direct Terraform deployment execution without framework selection.OfficialDevOpsNo warnings★ 21.9K↓ —
- pricing-and-packagingcbrock84/headcountSets price, structures packages and tiers, and designs the monetization surfaces that carry them — upgrade paths, paywalls, and offer construction. Use this to set or change pricing, design or restructure tiers, choose a pricing metric, build an offer, design upgrade prompts and paywalls, or evaluate whether a pricing change is safe to make.DesignNo warnings★ 2.6K↓ —
- performance-managementcbrock84/headcountRuns performance systems that change behavior — expectations, feedback, review cycles, calibration, and handling underperformance. Use this to design or fix a review process, run calibration, write or coach on feedback, address sustained underperformance, or work out why reviews consume weeks and change nothing.DesignNo warnings★ 2.6K↓ —
- ai-workflow-architectcbrock84/headcountDesigns AI systems, automations, and agent workflows for a business — identifying which manual work is worth automating, how to structure the system, which tools fit, and what could go wrong. Use this to automate part of an operation, design an agent or MCP workflow, reduce repetitive manual work, connect tools into a system, decide which automation to build first, or audit an automation that is not delivering.PlanningNo warnings★ 2.6K↓ —
- datanalysis-credit-riskgithub/awesome-copilotCredit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.OtherNo warnings★ 40.8K↓ —
- arcgis-to-portaljsdatopian/portaljsMigrate a whole ArcGIS Hub site into a PortalJS Arc portal end-to-end. Harvests the Hub /data.json (DCAT-US) inventory, exports every FeatureService layer through the ArcGIS REST query API with resultOffset paging, converts each to the serverless dual tier (PMTiles render + GeoParquet query) with tabular items to Parquet, pushes everything to Cloudflare R2 via Git LFS, appends dual-tier datasets.json entries, and writes a source-vs-derived parity report. Use to move a City or sector ArcGIS Hub open-data portal onto PortalJS with no server-side compute.DevOpsNo warnings★ 2.4K↓ —
- agent-platform-eval-flywheelgoogle/skillsMeasures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when generating synthetic user scenarios, evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For general production deployment, use agent-platform-deploy.OfficialDevOpsNo warnings★ 21.9K↓ —
- ai-ml-governancecbrock84/headcountGoverns models and AI systems in production — intended use, evaluation, monitoring, human oversight, documentation, and the decision to deploy or retire. Use this before deploying a model or AI feature, when defining evaluation criteria, when a model's behavior has drifted, when assessing AI risk or regulatory exposure, or when deciding whether an AI system is fit for a consequential decision.DevOpsNo 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★ 56.1K↓ —
- quality-gateKlotzkette/claude-fuer-deutsches-rechtFür Common-Law-Qualitätstor: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.LegalNo warnings★ 1.8K↓ —
- improve-retentionwondelai/skillsDiagnose and fix retention problems using behavior design (B=MAP). Use when the user mentions "users sign up but dont stick around", "activation rate", "onboarding friction", "retention metrics", "why users dont complete", "churn analysis", or "aha moment". Also trigger when analyzing cohort retention curves, designing activation milestones, reducing time-to-value for new users, or investigating why users quit after their first session. Covers the Ability Chain, prompt design, and tiny behaviors that compound. For habit loops and variable rewards, see hooked-ux. For intrinsic motivation, see drive-motivation.DesignNo warnings★ 2.6K↓ —Also in 2 other repos
- factoring-agbKlotzkette/claude-fuer-deutsches-rechtFür Factoring AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- widerspruchKlotzkette/claude-fuer-deutsches-rechtFür Fahrgastrechte-Widerspruch — Skill: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- onboardingKlotzkette/claude-fuer-deutsches-rechtFür Onboarding: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- skill-authoringcbrock84/headcountWrites and revises agent skills so they trigger at the right moments and give usable instruction when they do. Use this when creating a new skill, editing an existing one, diagnosing a skill that fires too often or never fires, or reviewing a set of skills for overlap. Also use before adding to a skill library, to check the capability is not already covered.WritingNo warnings★ 2.6K↓ —
- huashu-topic-genalchaincyf/huashu-skills快速生成3-4个选题方向，含标题、大纲和优劣分析。当用户提到"选题"、"写什么"、"文章方向"、"题目建议"时使用。OtherNo warnings★ 2.2K↓ —
- ml-kit-genai-prompt-apiandroid/skillsAnalyzes Android codebases to implement ML Kit GenAI Prompt API. Use this skill to send natural language requests on-device to Gemini Nano, use structured output with Prompt API, implement prefix caching, optimize the current prompt, or apply best practices."OfficialEngineeringNo warnings★ 10.3K↓ —
- scenario-grok-imagine-imagescenario-labs/skillsUse when generating or editing images with Grok Imagine models on Scenario via MCP: text-to-image, instruction editing with up to three reference images, posters, packaging, ads, or infographics with exact in-image text, photoreal shots from camera and lighting cues, extended aspect ratios up to 20:9 and 9:20, quality and resolution tiers, or batches of variations. Keywords: Grok Imagine Image 2.0, Image Quality, xAI, Aurora, Grok, txt2img, img2img, typography, 2K.MediaNo warnings★ 2.2K↓ —
- 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↓ —
matchms
K-Dense-AI/scientific-agent-skills
PlanningUpdated 3 days ago
From the author
Processes, cleans, compares, and searches tandem mass spectra with matchms. Use for MS/MS file I/O, metadata harmonization, peak filtering, spectral similarity, library matching, score matrices, and molecular-similarity networks. Use pyopenms instead for LC-MS feature detection or proteomics pipelines.
Install
npx skills add K-Dense-AI/scientific-agent-skills --skill matchms -a claude-code
Installs to .claude/skills/matchms/ · 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 scriptsUses the networkLicence: APACHE-2.0
Safety checks on SKILL.md
- Ships scripts we have not reviewedLow
Why 89
Security85
Provenance95
Maintenance100
Licence100
Adoption73
Files (8)
- SKILL.md
- references/filtering.md
- references/importing_exporting.md
- references/migration.md
- references/similarity.md
- references/sources.md
- references/workflows.md
- scripts/library_search.py