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 5 hours ago
49,492 skills
- protocolsio-integrationK-Dense-AI/scientific-agent-skillsReads, validates, and safely exports protocols.io data with current official REST/MCP contracts, or creates non-executing mutation plans. The bundled client makes bounded official-host GET requests only with explicit --execute. Use only for tasks explicitly targeting protocols.io or an exact protocols.io protocol version.PlanningNo warnings★ 56.1K↓ —
- dev-retrocodeaholicguy/ai-devkitAI DevKit · Run an evidence-based retrospective on finished work (feature, session, incident) and turn friction into durable fixes, automation first. Use when users ask for a retro, lessons learned, post-mortem, or "what went wrong", or when another skill offers one after a feature or fix.OtherNo warnings★ 1.7K↓ —
- exportKlotzkette/claude-fuer-deutsches-rechtFür Internationaler Export: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- clean-codewondelai/skillsWrite readable, maintainable code through disciplined naming, small functions, and clean error handling. Use when the user mentions "clean up this code", "this function is too long", "code smells", "naming conventions", "boy scout rule", "single responsibility", or "unit test quality". Also trigger when reviewing a pull request for readability, untangling a messy function, debating comment styles, or improving error-handling patterns. Covers SRP, comment discipline, formatting, and unit testing. For refactoring techniques, see refactoring-patterns. For architecture and dependency rules, see clean-architecture.EngineeringNo warnings★ 2.6K↓ —Also in 2 other repos
- 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★ 56.1K↓ —
- presentation-designcbrock84/headcountDesigns slide decks and one-pagers that carry an argument rather than decorate one — deck structure, headlines that state the takeaway, charts that make a single point, and the different rules board decks and conference talks follow. Use this to build or fix a pitch deck, board deck, or conference talk, to design a one-pager, or when a deck is dense, unfocused, or being read aloud from the slides. For social graphics, carousels and infographics, use `marketing:visual-content` instead.DesignNo warnings★ 2.6K↓ —
- statistical-analysisK-Dense-AI/scientific-agent-skillsGuided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required sample sizes, or write up results - even if they never name a specific test. Covers t-tests, ANOVA, chi-square, correlation, regression, non-parametric and Bayesian methods. For low-level model APIs, see the statsmodels and pymc skills.TestingNo warnings★ 56.1K↓ —
- 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★ 56.1K↓ —
- 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↓ —
- 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↓ —
- opcodeLeoYeAI/agent-master-skillsZero-token execution layer for AI agents. Define workflows once, run them free forever — persistent, scheduled, deterministic. 6 MCP tools over SSE. Supports DAG-based execution, 6 step types (action, condition, loop, parallel, wait, reasoning), 26 built-in actions, ${{}} interpolation, reasoning nodes for human-in-the-loop decisions, and secret vault. Use when defining workflows, running templates, checking status, sending signals, querying workflow history, or visualizing DAGs.ProductivityNo warnings★ 2.2K↓ —
- neuropixels-analysisK-Dense-AI/scientific-agent-skillsAnalyzes Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.EngineeringNo warnings★ 56.1K↓ —
- cs-aeoNewLeoYeAI/agent-master-skillsAnswer Engine Optimization (AEO) specialist agent. Use when content needs to be optimized for citation by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) rather than for traditional search rankings. Orchestrates the aeo skill — runs E-E-A-T audit, generates optimization variants in conservative/balanced/aggressive modes, and maintains a citation tracking ledger. Industry-aware (8 industries with calibrated thresholds). Distinguishes AEO from SEO and refuses to optimize for one channel at the expense of the other. Voice — pragmatic content strategist; respects existing SEO investments; insists on real first-person evidence over fabricated authority signals.FinanceNo warnings★ 2.2K↓ —
- neurokit2K-Dense-AI/scientific-agent-skillsBuilds and audits reproducible NeuroKit2 research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Use when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.ScienceNo warnings★ 56.1K↓ —Also in 1 other repo
- translate-to-quartopedrohcgs/claude-code-my-workflowA ready-to-fork Claude Code template for academics using LaTeX/Beamer + R. Multi-agent review, quality gates, adversarial QA, and replication protocols.TestingNo warnings★ 1.7K↓ —
- huashu-image-uploadalchaincyf/huashu-skills文章配图一键生成并上传图床，自动插入Markdown链接。当用户提到"配图"、"插图"、"上传图片"、"文章配图"时使用。MediaNo warnings★ 2.2K↓ —
- mandateLeoYeAI/agent-master-skillsUse when enforcing spend limits on AI agent wallets, validating transactions before signing, configuring allowlists or approval workflows, detecting prompt injection in agent reasoning, scanning codebases for unprotected wallet calls, or auditing agent transaction history. Works with OpenClaw, Claude Code, GOAT, AgentKit, ElizaOS. Supports Bankr, Locus, Sponge, CDP wallets. Non-custodial: private keys never leave your machine.EngineeringNo warnings★ 2.2K↓ —
- anr-audit-and-fixandroid/skillsAudits Android codebases for ANR risks and diagnoses ANR stack dumps. Use this skill when scanning Android code for ANR risks or triaging ANR stack dumps. Don't use for non-ANR crashes, dropped frames, general CPU profiling, or Perfetto system traces.OfficialEngineeringNo warnings★ 10.3K↓ —
- contagiouswondelai/skillsEngineer word-of-mouth and virality using the STEPPS framework (Social Currency, Triggers, Emotion, Public, Practical Value, Stories). Use when the user mentions "go viral", "word of mouth", "shareable content", "social currency", "why people share", "referral program", "nobody is sharing it", or "make this spread". Also trigger when designing shareable features, crafting social campaigns, or building products that spread through peer recommendation. Covers environmental triggers and high-arousal emotional content. For sticky messaging, see made-to-stick. For persuasion tactics, see influence-psychology.OtherNo warnings★ 2.6K↓ —Also in 2 other repos
- scenario-luma-imagescenario-labs/skillsUse when generating or editing images with Luma Uni-1 models on Scenario via MCP: text-to-image, prompt-based editing of an existing image, style or character reference images with named roles, web search grounding for real-world subjects, rendering exact title text into posters, aspect ratio control, or choosing between Uni-1 Max and Uni-1. Keywords: Luma Labs, Uni-1, Photon, txt2img, img2img, image edit, reference images, webSearch, reasoning image model.MediaNo warnings★ 2.2K↓ —
- get-available-resourcesK-Dense-AI/scientific-agent-skillsDetects host inventory and effective CPU, memory, disk, scheduler, container, and accelerator limits when a user asks for resource-aware planning or before a clearly resource-sensitive local workload. Produces a redacted JSON snapshot and conservative planning helpers without stress tests or assuming visible host hardware is usable.TestingNo warnings★ 56.1K↓ —
- record-a-decisioninkeep/open-knowledgeRecords an architecture decision as a Nygard/MADR-shaped ADR under decisions/ — capturing the context that forced the choice, the options weighed, the decision itself, and its consequences in both directions, plus the supersedes chain that keeps a decision log honest. Read when asked to record an architecture decision, write an ADR, log the decision we made, document why we chose X over Y, capture this decision for the record, or supersede an old decision with a new one. Do NOT read to frame a proposal or explore an idea not yet decided (frame-a-proposal), to write a spec or implementation plan (write-a-spec), to write an incident postmortem (write-a-postmortem), or to judge whether a design is sound (review-a-design). This skill records a decision already made; it does not make one.DesignNo warnings★ 4.8K↓ —
- dokumente-intakeKlotzkette/claude-fuer-deutsches-rechtFür Dokumentenintake: ordnet Akte, Belege und Lücken; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: patentrecherche.OtherNo warnings★ 1.8K↓ —
- design-sprintwondelai/skillsRun a structured 5-day process to prototype, test, and validate product ideas with real users. Use when the user mentions "design sprint", "validate before we build", "rapid prototype", "test with users", or "should we build this". Also trigger when a team is stuck in endless debate over a high-stakes product decision, or wants to de-risk a costly idea before investing in development. Covers mapping, sketching, deciding, prototyping, and testing across Monday-Friday. For ongoing experimentation and MVPs, see lean-startup. For customer job analysis, see jobs-to-be-done. For non-leading user interviews, see mom-test.DesignNo warnings★ 2.6K↓ —Also in 2 other repos
challenge
pedrohcgs/claude-code-my-workflow
TestingUpdated Sep 27, 2026
From the author
Stress-test a finding against the choices you did not make. Enumerates the discrete forks a competent analyst could have taken (measure definition, sample filter, control set, clustering level, weighting, functional form), runs the specification grid, and reports the distribution rather than a point estimate — then attacks the identifying assumption with named, computable sensitivity statistics. Use when the user says "is this robust", "challenge this result", "specification curve", "multiverse", "how sensitive is this", "what if I'd used a different measure", "stress-test my estimate", or before a result becomes a headline claim. NOT a reviewer of prose or code — it challenges the CLAIM.
Install
npx skills add pedrohcgs/claude-code-my-workflow --skill challenge -a claude-code
Installs to .claude/skills/challenge/ · 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: MIT
Safety checks on SKILL.md
No warnings.
Why 89
Security100
Provenance79
Maintenance100
Licence100
Adoption52
Files (4)
- SKILL.md
- evals/marker.txt
- references/fork-catalog.md
- references/sensitivity-statistics.md