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.
49,459 skills from 2,407 repositories · updated 5 minutes ago
49,459 skills
- 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★ 56.2K↓ —
- 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★ 56.2K↓ —
- 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★ 56.2K↓ —
- scenario-model-trainingscenario-labs/skillsUse when generated assets must keep a consistent style, character, or product look and references stop scaling, or when a user asks to train a custom model through the Scenario MCP, fine-tune a LoRA, clone a voice, curate a training dataset, choose a base model, set epochs and sample prompts, estimate training cost, diagnose a trained model that lost its identity or has one epoch, or generate with a trained model. Keywords: custom model, LoRA, dataset curation, epoch previews.OtherNo warnings★ 2.8K↓ —
- geomasterK-Dense-AI/scientific-agent-skillsSupports geospatial research workflows for remote sensing, vector and raster GIS, spatial statistics, terrain and network analysis, and machine learning for Earth observation. Use when processing satellite imagery, aligning coordinate systems and raster grids, accessing STAC catalogs, analyzing geospatial time series, or implementing scientific GIS workflows in Python, R, Julia, JavaScript, C++, Java, Go, or Rust.ScienceNo warnings★ 56.2K↓ —Also in 1 other repo
- citation-managementK-Dense-AI/scientific-agent-skillsComprehensive citation management for academic research. Search OpenAlex, PubMed, and Google Scholar for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.ScienceNo warnings★ 56.2K↓ —
- 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★ 56.2K↓ —
- 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↓ —
- hunt-lfielementalsouls/Claude-BugHunterHunt Local File Inclusion (LFI), Remote File Inclusion (RFI), and Path Traversal — /etc/passwd read, log poisoning → RCE, PHP filter-chain RCE (no upload needed), php:// / data:// / zip:// / phar:// wrappers, RFI via allow_url_include, directory traversal read/write/delete. Covers OOB/blind LFI confirmation and false-positive discipline. Use when hunting file-include or path-traversal bugs on any target.WritingNo warnings★ 5.4K↓ —
- pyhealthK-Dense-AI/scientific-agent-skillsBuilds and validates PyHealth clinical machine-learning pipelines for EHR, signals, imaging, and medical codes. Use for PyHealth dataset loading, MIMIC-III/IV, eICU or OMOP prediction tasks, patient-level evaluation, mortality/readmission/length-of-stay modeling, medication recommendation, sleep staging, Trainer checkpoints, and ICD/ATC/NDC/RxNorm mapping.ScienceNo warnings★ 56.2K↓ —Also in 1 other repo
- 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↓ —
- webapp-testinggithub/awesome-copilotToolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.TestingNo warnings★ 40.8K↓ —
- 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★ 49.2K↓ —
- waypoint-bioK-Dense-AI/scientific-agent-skillsSupports work with Outpost Bio's open microbiome foundation models - the Waypoint checkpoints (Waypoint-6m, Waypoint-45m, Waypoint-170m), the Atlas pretraining corpus, the Compass eight-task benchmark, or the `waypoint` CLI from the `waypoint-bio` package. Covers embedding microbiome samples, fine-tuning on taxonomic abundance data, benchmarking a checkpoint on Compass, pretraining a GPT-2 model on taxonomic abundance profiles, and converting MetaPhlAn, Kraken2, QIIME 2, or MGnify abundance tables into waypoint format.EngineeringNo warnings★ 56.2K↓ —
- canteraK-Dense-AI/scientific-agent-skillsRuns Cantera homogeneous chemical reactors and evaluates ignition delay with mechanism provenance, conservation checks, and numerical refinement. Use for combustion kinetics, closed adiabatic ideal-gas constant-volume or constant-pressure ignition, temperature histories, or mechanism-specific ignition-delay comparisons.ScienceNo warnings★ 56.2K↓ —Also in 2 other repos
- typeuibergside/typeuiUse TypeUI with OpenClaw to access project design skills, brand kits, UI prompts, and layout variations through the TypeUI MCP server when creating or refining user interfaces.DesignNo warnings★ 2.2K↓ —
- diffdockK-Dense-AI/scientific-agent-skillsPredicts protein-small-molecule binding poses with DiffDock and DiffDock-L from PDB or sequence plus SMILES/SDF/MOL2. Covers batch docking, pose triage, confidence interpretation, and validation. Use for molecular docking and virtual-screening pose generation, not binding-affinity prediction.ScienceNo warnings★ 56.2K↓ —Also in 1 other repo
- datamolK-Dense-AI/scientific-agent-skillsPythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.DesignNo warnings★ 56.2K↓ —Also in 2 other repos
- monetizing-innovationwondelai/skillsDesign products and pricing around validated willingness to pay, from Ramanujam & Tacke's "Monetizing Innovation". Use when the user mentions "pricing", "how much should we charge", "willingness to pay", "pricing page", "packaging", "freemium vs free trial", "are we leaving money on the table", "nobody buys at this price", "price increase", or "good-better-best". Also trigger when designing or auditing pricing and packaging, validating willingness to pay before building, segmenting customers by value, or choosing between subscription, usage-based, and freemium models. Covers price-before-product, willingness-to-pay talks, the four failures (feature shock, minivation, hidden gem, undead), leader/filler/killer packaging, and behavioral pricing. For offers and guarantees, see hundred-million-offers. For what customers value, see jobs-to-be-done.DesignNo warnings★ 2.6K↓ —Also in 2 other repos
- gentle-ai-judgment-dayGentleman-Programming/gentle-shellTrigger: judgment day, judgement day, dual review, adversarial review, juzgar. Run explicit blind dual review with at most two scoped fix/re-judgment rounds.EngineeringNo warnings★ 1.7K↓ —
- dokumente-intakeKlotzkette/claude-fuer-deutsches-rechtFür Dokumentenintake: ordnet Akte, Belege und Lücken; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Meinungsprüfer.OtherNo warnings★ 1.8K↓ —
- mlkit-agent-apiandroid/skillsBuilds autonomous on-device agentic workflows in Android apps using the ML Kit GenAI Agent API powered by Gemini Nano and AICore. Use this skill when implementing conversational agents, multi-turn chat with AgentSession in a ViewModel, autonomous tool calling using Android AppFunctions (@AppFunctionDeclaration and AppFunctionAgentTools.discover), ephemeral single-turn execution with runner.runSingleTurnAsync, or handling GenAiException error resilience. It solves the problem of orchestrating local reasoning loops, typed tool dispatch, and session persistence on-device with zero cloud latency and privacy preservation. Don't use for cloud-based Gemini models or Vertex AI, single-turn text generation without agent loops (suggest Prompt API), or non-Android platforms.OfficialEngineeringNo warnings★ 10.4K↓ —
- ressort-bmuknKlotzkette/claude-fuer-deutsches-rechtFür Ressort-Heranführung BMUKN: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- ressort-bmlehKlotzkette/claude-fuer-deutsches-rechtFür Ressort-Heranführung BMLEH: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
scenario-wan
scenario-labs/skills
MediaUpdated 3 hours ago
From the author
Use when generating or editing video with Wan models on Scenario via MCP: text-to-video, image-to-video from a still, first and last frame brackets, extending a clip, instruction-based video editing, character motion transfer or person replacement (Animate), aspect ratio reframing, video outpainting, uploaded-audio sync or auto-generated audio, or multi-shot prompts with timing brackets. Keywords: Wan 2.7, 2.6, 2.5, 2.2, Alibaba, VACE, T2V, I2V, V2V, lip-sync, multiShots.
Install
npx skills add scenario-labs/skills --skill scenario-wan -a claude-code
Installs to .claude/skills/scenario-wan/ · 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
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