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 6 hours ago
49,492 skills
- program-managementcbrock84/headcountPlans and drives cross-functional programs to delivery — scope, sequencing, dependencies, status, risk, and the escalations that keep work moving. Use this to run a multi-team initiative, recover a program that is slipping, build a delivery plan with dependencies, structure status reporting, or diagnose why cross-team work keeps missing dates.PlanningNo warnings★ 2.6K↓ —
- pydicomK-Dense-AI/scientific-agent-skillsReads, inspects, writes, transforms, and preflights local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.WritingNo warnings★ 56.1K↓ —Also in 2 other repos
- 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↓ —
- scenario-texturesscenario-labs/skillsUse when a task involves game textures or materials through the Scenario MCP: seamless or tileable textures, themed texture packs (brick, wood, stone, floors, hand-painted), PBR materials (albedo, metallic, roughness, normal) on 3D assets, retexturing a mesh, material iteration from reference images, texture upscaling that must preserve tiling, or sizing textures for game engines. Keywords: seamless texture, tileable, PBR, material, retexture, texture upscale, surface.ProductivityNo warnings★ 2.2K↓ —
- eval-driven-devgithub/awesome-copilotImprove 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.TestingNo warnings★ 40.8K↓ —
- budgeting-and-forecastingcbrock84/headcountRuns the planning cycle — annual budget, rolling forecast, consolidation of business unit inputs, and the variance analysis that explains actuals against plan. Use this to build or challenge a budget, run a forecast cycle, consolidate departmental submissions, explain why results diverged from plan, or improve forecast accuracy.PlanningNo warnings★ 2.6K↓ —
- chief-data-officercbrock84/headcountOwns data as an asset — governance, quality, the warehouse and semantic layer, analytics capability, and the governance of models built on top. Use this for a decision about how data is collected, stored, defined, or shared; when numbers disagree between teams; when deciding what to build in-house versus buy; when standing up a data function; or when an AI or model decision needs governance rather than engineering.DataNo warnings★ 2.6K↓ —
- backup-and-recoverycbrock84/headcountProtects and restores data — backup coverage and scope, retention, immutability against ransomware, and proving restores actually work. Use this to design a backup regime, verify restores, plan retention, protect backups from ransomware, or recover from data loss.DesignNo warnings★ 2.6K↓ —
- scenario-thumbnailsscenario-labs/skillsUse when creating or revising finished video thumbnails or cover images with Scenario: game trailers, boss reveals, patch updates, devlogs, or community videos needing readable composition, exact headline text and consistent characters. Not for title ideas or critique alone, in-video title cards, or a generic image without a thumbnail deliverable.MediaNo warnings★ 2.2K↓ —
- compensation-and-levelingcbrock84/headcountBuilds and maintains the leveling framework and pay structure — level definitions, salary bands, benchmarking, pay equity, and how raises and promotions are decided. Use this to design or revise leveling, set or adjust salary bands, benchmark against market, handle a compensation request or counteroffer, run a review cycle, or diagnose pay compression and equity issues.DesignNo warnings★ 2.6K↓ —
- statusKlotzkette/claude-fuer-deutsches-rechtFür Fallstatus: Zielgruppengerechte Fallzusammenfassung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- deal-negotiationcbrock84/headcountNegotiates a commercial deal without giving away the terms that matter — preparing your walk-away and theirs, trading concessions rather than conceding them, recognizing the tactics that create false urgency, protecting price by moving other variables, and closing on terms someone can actually deliver. Use this to prepare for a negotiation, respond to a demand mid-deal, work out why discounts keep landing at quarter end, or review terms before they are signed.FinanceNo warnings★ 2.6K↓ —
- unit-economicscbrock84/headcountEstablishes whether the business makes money on each customer or unit — contribution margin, acquisition cost, payback period, lifetime value, and the cohort behavior underneath. Use this to assess whether growth is profitable, evaluate a channel or segment, support a pricing decision, judge how fast the business can afford to grow, or diagnose why revenue growth is not producing profit.MarketingNo warnings★ 2.6K↓ —
- 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↓ —
- scenario-product-shotsscenario-labs/skillsUse when producing product photography with Scenario from a real product photo: e-commerce packshots on white, transparent, or brand backgrounds, lifestyle scenes placing the product in an environment, hero shots for a landing page or marketplace listing, angle and colorway sets, relighting or shadow fixes, or any shot where the label, logo, and shape must stay exact. Keywords: product photo, packshot, e-commerce, lifestyle shot, compositing, relight, label fidelity, catalog.DesignNo warnings★ 2.2K↓ —
- 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★ 56.1K↓ —Also in 1 other repo
- output-versandKlotzkette/claude-fuer-deutsches-rechtFür Output und Versandsteuerung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- alphagenomeK-Dense-AI/scientific-agent-skillsLooks up precomputed AlphaGenome Atlas effects for any GRCh38 single-nucleotide variant (AVI score with Phred and 18 SHAP feature attributions, plus raw and quantile scores for RNA-seq, DNase, ATAC, ChIP-TF, ChIP-histone, CAGE, PRO-cap, splicing, polyadenylation and contact-map tracks), scores variants or scans windows on demand with the AlphaGenome model for human and mouse (variant scoring, in silico mutagenesis, REF-versus-ALT track prediction), and builds Atlas website deep links. Use when the user mentions AlphaGenome, AlphaGenome Atlas, AVI or AlphaGenome Variant Impact, DeepMind variant effect prediction, or wants to prioritise or mechanistically interpret non-coding, regulatory, splicing, enhancer, promoter, or chromatin-accessibility effects of SNVs from a VCF, credible set, or region. Research use only; not a clinical tool.ScienceNo warnings★ 56.1K↓ —
- convert-pdf-to-mdgithub/awesome-copilotConverts PDF (.pdf) documents into Markdown so their contents can be accurately analyzed, summarized, searched, or extracted from. Use this skill whenever the user shares, references, or asks about a .pdf file — even if they don't say "convert" or "markdown" explicitly. This includes requests to "read", "summarize", "review", "extract data from", "compare", or "analyze" a PDF report, paper, invoice, form, contract, or scanned document. Always run the bundled conversion script to produce Markdown first; do not attempt to parse PDF content directly or write ad-hoc extraction code. Also use this skill for batch requests involving a whole folder of PDF documents. IMPORTANT: When the user references a folder or set of documents containing multiple file types (.pdf, .docx, .xlsx), invoke ALL three sibling skills — convert-pdf-to-md, convert-word-to-md, and convert-excel-to-md — so no file type is silently skipped.DocumentsNo warnings★ 40.8K↓ —
- openpivK-Dense-AI/scientific-agent-skillsPerforms Particle Image Velocimetry (PIV) analysis with OpenPIV. Use when extracting velocity fields from PIV image pairs, analyzing fluid dynamics or flow visualization experiments, cross-correlating interrogation windows, validating and replacing spurious PIV vectors, or computing vorticity, strain rate, and turbulence statistics from measured velocity fields.MediaNo warnings★ 56.1K↓ —Also in 2 other repos
- brand-voicecbrock84/headcountCaptures how a person or brand actually writes and turns it into reusable voice instructions every other content skill draws from. Use this before drafting any content for a new brand or client, when output keeps coming back sounding generic, when several writers need to sound like one, or when a voice needs defining without existing samples to learn from.WritingNo warnings★ 2.6K↓ —
- systems-administrationcbrock84/headcountRuns servers and corporate systems — patching, configuration baselines, change control, capacity, and the routine that prevents incidents. Use this to establish a patching cadence, standardize server configuration, plan a maintenance window, decide change control for infrastructure, or clean up systems that have drifted from any known state.DevOpsNo warnings★ 2.6K↓ —
- zxLeoYeAI/agent-master-skillsComprehensive guide for writing shell scripts with Google zx — a tool for writing better scripts using JavaScript/TypeScript. Use when writing, debugging, or refactoring zx scripts (.mjs, .js, .ts files using zx), executing shell commands from JavaScript, working with ProcessPromise/ProcessOutput APIs, piping streams, configuring zx options, or using zx CLI. Do NOT use for general Node.js questions unrelated to shell scripting.WritingNo warnings★ 2.2K↓ —
- 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★ 56.1K↓ —
scenario-skyboxes
scenario-labs/skills
MediaUpdated 16 hours ago
From the author
Use when a task involves generating or iterating on skyboxes, 360 panoramas, equirectangular images, environment maps, HDRI-style backdrops, or VR backdrops through the Scenario MCP. Triggers include text-to-skybox, turning a photo into a 360 environment, restyling a panorama's mood, upscaling a skybox without breaking the seam wrap, or exporting equirectangular or cubemap layouts for game engines such as Unity, Unreal, or Godot.
Install
npx skills add scenario-labs/skills --skill scenario-skyboxes -a claude-code
Installs to .claude/skills/scenario-skyboxes/ · 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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