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 15 hours ago
17,846 skills
- founder-offerJakeschincariol/founder-skillBuilds an offer too good to refuse. Lists every problem the buyer hits on the way to the result they want, turns each into a solution, trims to what is cheap to deliver and valuable to the buyer, and stacks it with honest bonuses, a guarantee the CFO can afford, real urgency and a clear name. Scores it on the value equation (outcome, likelihood, time, effort) and re-tests it on a quick buyer panel. Use when the user says "make my offer better", "why won't people buy", "what should I include", "guarantee", "bonuses", "grand slam offer", or after the panel shows people passing.TestingNo warnings★ 2.4K↓ —
- exploratory-data-analysisK-Dense-AI/scientific-agent-skillsPerforms bounded, local exploratory analysis of explicitly supported scientific files. Supports redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain formats are reference-only and unknown formats fail closed.DataNo warnings★ 56.1K↓ —
- founder-competitorsJakeschincariol/founder-skillMaps every competitor and the gap they leave. Finds the direct competitors, indirect ones and the substitutes a buyer would use instead, from public sources only, and records what each sells, at what price, how they position themselves and what their customers complain about in public reviews, every fact with a link. Ends with a positioning map and the gap the new business can own. Use when the user says "who are my competitors", "is this market crowded", "what else is out there", "competitor analysis", "find the gap", or "who am I up against".OtherNo warnings★ 2.4K↓ —
- scenario-veoscenario-labs/skillsUse when generating or extending video with Google Veo models on Scenario via MCP: text-to-video, image-to-video from a first frame, first and last frame transitions, reference-to-video (R2V) with asset or style reference images, native audio with dialogue, sound effects, and ambience, negative prompts, seeded reruns, extending a 16:9 clip, or choosing a quality, fast, or lite tier. Keywords: Veo 3.1, Veo 3.1 Fast, Veo 3.1 Lite, Extend Video, Google, T2V, I2V, V2V, 720p, 1080p.MediaNo warnings★ 2.2K↓ —
- founder-launchJakeschincariol/founder-skillYour launch lead. Builds a dated, step-by-step launch plan: a cheap real-world test first (a waitlist, a pre-sale or a pop-up with a real price, so real buyers confirm what the simulated panel said), then the countdown to opening day with owners and deadlines, the launch-day run sheet, and the first 30 days of what to measure and what to change. Use when the user says "how do I launch", "launch plan", "when can I open", "launch checklist", "go live", or "soft open".TestingNo warnings★ 2.4K↓ —
- 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↓ —
- 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↓ —
- labarchive-integrationK-Dense-AI/scientific-agent-skillsIntegrates with the official LabArchives ELN REST-like API and Inventory API v1. Supports regional endpoint selection, signed-request construction, user authorization and UID flows, local LA container validation, and verified LabArchives integration workflows.EngineeringNo warnings★ 56.1K↓ —
- founder-brandJakeschincariol/founder-skillYour brand designer. Names the business (with the trademark, domain and handle checks to run before falling in love with a name), writes the voice, a one-line promise and a tagline, and briefs the look: colours, type, logo and the first things a customer sees, so they match the positioning the marketing director chose. Use when the user says "name my business", "brand this", "logo", "brand identity", "what should it look like", "tagline", or "brand voice".MarketingNo warnings★ 2.4K↓ —
- pr-summaryscenario-labs/skillsRefresh the current pull request description from its net changes, following the repository's PR template, when asked to update or write the PR summary. Works in any Scenario repository, whatever its default branch.ProductivityNo warnings★ 2.2K↓ —
- uncertainty-and-unitsK-Dense-AI/scientific-agent-skillsTracks physical units and propagates measurement uncertainty in scientific calculations using pint and uncertainties. Use for unit conversion and dimensional checking, GUM uncertainty budgets, Type A and Type B evaluation, coverage factors and expanded uncertainty, Monte Carlo propagation, significant-figure and plus-minus reporting, error propagation through curve fits, CODATA constants, auditing Python code for stripped units or broken uncertainty propagation, and order-of-magnitude plausibility checks using dimensionless groups (Reynolds, Peclet, Damkohler, Knudsen, Biot, Womersley), characteristic scales such as diffusion time or Debye length, and observed magnitude ranges. Trigger on "is this number physically reasonable", "sanity check these units", "what regime is this flow in", or a result that looks off by orders of magnitude.ScienceNo warnings★ 56.1K↓ —
- hypothesis-generationK-Dense-AI/scientific-agent-skillsFormulates evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions, measurements, and preregistration-ready analysis plans. Used when turning observations or preliminary findings into transparent, testable research plans without treating hypotheses as facts.ScienceNo warnings★ 56.1K↓ —
- dnanexus-integrationK-Dense-AI/scientific-agent-skillsBuilds and operates reproducible genomics workloads on DNAnexus with the dx CLI, dxpy, apps/applets, native workflows, dxCompiler, and Nextflow. Supports DNAnexus data transfers, dxapp.json development, execution monitoring, workflow import, and project automation.ScienceNo warnings★ 56.1K↓ —
- 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↓ —
- 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↓ —
- founder-boardJakeschincariol/founder-skillYour board of directors. Puts a business idea in front of a three-member board, each a sub-agent reading the idea through one published framework: the Offers lens (from Alex Hormozi's $100M Offers), the Monopoly lens (from Peter Thiel's Zero to One) and the Product lens (from Walter Isaacson's biography of Steve Jobs). Each member scores the idea, names the risks that would kill it and votes fund, fund with conditions, or pass. Use when the user says "test my business idea", "would this work", "pressure-test this", "what would a board say", "is this a good business", or starts the founder pack on a new idea.TestingNo warnings★ 2.4K↓ —
- ai-devkit-setupcodeaholicguy/ai-devkitAI DevKit · Check local AI DevKit readiness and run setup only when status shows onboarding or harness integration gaps.OtherNo warnings★ 1.7K↓ —
- scikit-survivalK-Dense-AI/scientific-agent-skillsBuilds, evaluates, and audits right-censored or competing-risk survival workflows with scikit-survival, including leakage-safe preprocessing, model selection, probability prediction, and censoring-aware metrics.OtherNo warnings★ 56.1K↓ —
- hugging-scienceK-Dense-AI/scientific-agent-skillsDiscovers and evaluates scientific datasets, models, methodology posts, and Spaces through the Hugging Science catalog. Used when selecting scientific ML resources in biology, chemistry, genomics, materials, climate, physics, astronomy, medicine, mathematics, protein design, single-cell analysis, or PDE modeling, and when checking their actual datasets, Transformers, native-runtime, Inference Providers, or Gradio interfaces.ScienceNo warnings★ 56.1K↓ —
- scenario-team-adminscenario-labs/skillsUse when administering a Scenario team from an agent through MCP: restricting which models a team or project can run (model access control, allowlist, blocklist), inviting or removing team and project members, changing roles, capping a member's Creative Unit spend, creating or deleting projects, auditing API keys and their roles or scopes, or attributing consumption per user or model. Keywords: governance, model control, consumption cap, spend limit, API key hygiene, team admin, enterprise.EngineeringNo warnings★ 2.2K↓ —
- nwb-conversionK-Dense-AI/scientific-agent-skillsConverts neuroscience acquisition data to Neurodata Without Borders files with NeuroConv and PyNWB, preserves metadata and timebases, checks evidence-based clock alignment, and produces schema validation, NWB Inspector findings and round-trip checks. Use for NWB conversion and synchronization of planar single-channel two-photon TIFF imaging plus timestamped behavioral position CSV; this skill does not perform spike sorting or claim tested support for arbitrary acquisition formats.MarketingNo warnings★ 56.1K↓ —
- 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↓ —
- primer-designK-Dense-AI/scientific-agent-skillsDesigns and audits PCR and RT-qPCR primers with Primer3, explicit thermodynamic conditions, reference-based off-target amplification searches, and traceable sequence coordinates. Use for designing primer pairs, checking existing primers, exon-junction or isoform-specific assays, variant masking, cloning tails, multiplex compatibility, and interpreting Primer-BLAST results. Includes bounded local in-silico PCR and BLAST screening; distinguishes computational candidates from experimentally validated assays.DesignNo warnings★ 56.1K↓ —
- what-if-oracleK-Dense-AI/scientific-agent-skillsSupports structured what-if scenario analysis for research planning, experimental contingencies, and scientific project decisions. Explores favorable, reference, adverse, wild-card, contrarian, and second-order scenarios with explicit assumptions, evidence, and decision triggers. Use to stress-test a research plan under uncertainty; scenario narratives do not estimate causal effects or calibrated forecast probabilities.TestingNo warnings★ 56.1K↓ —