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 7 hours ago
49,407 skills
- huashu-researchalchaincyf/huashu-skills结构化网络调研流程，确保调研成果增量保存到文件，不因会话截断丢失。当用户说"调研"、"搜索资料"、"帮我查一下"、"了解一下"、"最新信息"时使用此技能。ScienceNo warnings★ 2.2K↓ —
- paymentLeoYeAI/agent-master-skillsShopping Claw | Give your agent spending power. Financial management for Agents and OpenClaw bots.FinanceNo warnings★ 2.2K↓ —
- seabornsickn33/agentic-awesome-skillsSeaborn is a Python visualization library for creating publication-quality statistical graphics. Use this skill for dataset-oriented plotting, multivariate analysis, automatic statistical estimation, and complex multi-panel figures with minimal code.EngineeringNo warnings★ 49.1K↓ —
- ux-product-auditorcbrock84/headcountAudits a website, app, onboarding flow, or design for usability, conversion, and product problems, tying every finding to a business outcome and a severity. Use this to review an interface, diagnose low conversion or activation, find where users drop off, get structured product feedback, or decide which UX fixes to ship first. For raising visual quality rather than finding problems, use `interface-craft`.DesignNo 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↓ —
- disclosure-checkpedrohcgs/claude-code-my-workflowPre-screen analysis outputs (tables, figures, logs) built on restricted or confidential data for statistical-disclosure-limitation problems before any release. Scans for small cell counts, complementary-suppression gaps, dominance (p-percent / (n,k)), re-identifiable exact counts, PII leakage, and unrounded sensitive statistics; classifies each finding CRITICAL / WARNING / OK and gates on any CRITICAL. Use before depositing or sharing restricted-data results, or when the user says "disclosure check", "SDL scan", "is this output safe to release", "check for small cells", "disclosure avoidance", "pre-screen for the RDC", or "can I export this from the enclave".OtherNo warnings★ 1.7K↓ —
- 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↓ —
- 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↓ —
- landing-page-cro-expertcbrock84/headcountAudits and rewrites landing pages, homepages, and sales pages to increase conversion — diagnosing why a page is not converting, rewriting headlines, hero copy and calls to action, and prioritizing which changes to test first. Use this when a page underperforms, when someone pastes a URL or screenshot asking what is wrong, when writing a new page, or when deciding which conversion changes are worth testing.DesignNo warnings★ 2.6K↓ —
- chief-customer-officercbrock84/headcountOwns the customer's experience after the sale — support, success, escalation, and the feedback loop back into product. Use this for a decision spanning support and product, when service quality and cost are in tension, when deciding what to staff or automate, when a customer relationship is at risk above the account-manager level, or when nobody owns a recurring customer problem.OtherNo warnings★ 2.6K↓ —
- pkpd-modelingK-Dense-AI/scientific-agent-skillsPharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".OtherNo warnings★ 56K↓ —
- observability-and-reliabilitycbrock84/headcountMakes systems debuggable and reliably operable — instrumentation, alerting that is worth waking for, service objectives, and learning from failure. Use this to instrument a service, fix alerting that is ignored, set error budgets or reliability targets, prepare for on-call, or run a blameless post-incident review.DevOpsNo warnings★ 2.6K↓ —
- listing-distributioncbrock84/headcountGets a product listed where buyers and crawlers look — directories, marketplaces, review sites, comparison pages, and aggregators. Use this to plan a submission push, choose which directories are worth the effort, prepare listing assets, build comparison and alternative pages, or manage presence on review platforms.BrowserNo warnings★ 2.6K↓ —
- replication-packagepedrohcgs/claude-code-my-workflowAssemble a submission-ready replication package to the AEA Data and Code Availability Standard (DCAS) / openICPSR / Social Science Reproduction Platform expectations — standard replication README, dataset manifest, computational-requirements capture, a Table/Figure → script:line map, and a confidential-data deposit plan. Use when user says "build the replication package", "prepare the openICPSR deposit", "make the AEA data and code package", "DCAS compliance", "assemble the deposit for the journal", or after a paper is accepted and the journal's data editor needs the package. NOT a numeric verifier — it calls /audit-reproducibility to confirm claims reproduce before packaging.ScienceNo warnings★ 1.7K↓ —
- test-driven-developmentcbrock84/headcountDrives implementation by writing a failing test first, then the smallest code that passes it. Use this before writing implementation code for any feature or bugfix, when a bug needs a regression test, when existing code is hard to change safely, or when someone asks whether a change is covered. Also use to decide what is worth testing and what is not.TestingNo warnings★ 2.6K↓ —
- completion-verificationcbrock84/headcountVerifies that work is actually complete before it is claimed to be — running the checks, reading the output, and confirming the original request was satisfied rather than approximated. Use this before saying something is done, fixed, or passing; before committing or opening a pull request; and whenever a claim of success has not been backed by command output.EngineeringNo warnings★ 2.6K↓ —
- cloud-administrationcbrock84/headcountAdministers the cloud the company runs on rather than the one it sells — tenant and subscription structure, the SaaS estate and who owns each app, identity as the real perimeter, cloud spend that arrives as a surprise, and what the provider does not do for you. Use this to structure subscriptions or tenants, get control of sprawling SaaS, cut a cloud bill, work out who owns an application nobody admits to buying, or decide what corporate workloads belong in cloud at all.OtherNo warnings★ 2.6K↓ —
- chief-operating-officercbrock84/headcountAn agent organization structured as a company — 15+ departments, 125+ skills, each independently installable, citing the standards and regulators that settle the question. Runs in Claude Code and ChatGPT.LegalNo warnings★ 2.6K↓ —
- programmatic-seocbrock84/headcountBuilds large sets of search-targeted pages from a template and a dataset — the location, comparison, integration, and use-case pages that capture long-tail demand at scale. Use this when there is a repeating query pattern with real volume, when a dataset could answer many similar searches, or to judge whether a programmatic approach is viable before building it.MarketingNo warnings★ 2.6K↓ —
- paid-advertisingcbrock84/headcountPlans, runs, and optimizes paid acquisition across search, social, and display — account structure, targeting, creative, bidding, budget, and the analysis that says whether to scale or stop. Use this to set up or restructure campaigns, write and iterate ad creative, diagnose rising costs or falling performance, decide budget allocation, or judge whether a channel is working.MarketingNo warnings★ 2.6K↓ —
- research-ideationpedrohcgs/claude-code-my-workflowGenerate structured research questions, testable hypotheses, and candidate empirical strategies from a topic, phenomenon, or dataset description. Use when user says "give me research ideas on X", "brainstorm questions about Y", "what could I study with this data?", "I'm looking for a paper idea on...", "generate hypotheses for...". One-shot generation, not multi-turn. For idea-refinement use `/interview-me`.ScienceNo warnings★ 1.7K↓ —
- 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↓ —
- experimentationcbrock84/headcountDesigns, runs, and reads A/B tests and growth experiments — hypothesis, sample size, duration, and honest interpretation. Use this to plan a test, judge whether a result is real, build an experimentation program, decide what to test next, or diagnose why tests keep producing inconclusive or non-replicating results.TestingNo warnings★ 2.6K↓ —
- solution-architecturecbrock84/headcountDesigns system structure and makes architectural decisions defensible — boundaries, coupling, trade-offs, and recording why. Use this to design a new system or major component, choose between architectural options, review an existing design, decide where a boundary belongs, or document an architectural decision so it survives the people who made it.PlanningNo warnings★ 2.6K↓ —
eval-driven-dev
github/awesome-copilot
TestingUpdated yesterday
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.
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 (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