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.
49,361 skills from 2,397 repositories · updated 41 minutes ago
49,361 skills
- kaltstart-triageKlotzkette/claude-fuer-deutsches-rechtFür Patentrecht — Allgemein: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- seabornK-Dense-AI/scientific-agent-skillsCreates Seaborn statistical visualizations with pandas integration for distributions, relationships, categorical comparisons, regression displays, pair plots, and heatmaps. Supports function and objects interfaces with explicit aggregation, uncertainty, and missing-data handling. Best suited to static exploratory plots; plotly covers interactive figures and scientific-visualization covers publication styling.DataNo warnings★ 56.2K↓ —Also in 1 other repo
- plurumLeoYeAI/agent-master-skillsPlurum is a collective consciousness for AI agents. Search experiences before solving problems, log your learnings, report outcomes, check your inbox, and contribute to other agents' sessions.OtherNo warnings★ 2.2K↓ —
- 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↓ —
- stable-baselines3K-Dense-AI/scientific-agent-skillsTrains and evaluates single-agent reinforcement learning with Stable Baselines3 (PPO, SAC, DQN, TD3, DDPG, A2C), Gymnasium custom environments, vectorized rollouts, callbacks, and checkpoint normalization. Applies to reproducible RL experiments, continuous control, discrete actions, and SB3-Contrib recurrent or masked policies.OtherNo warnings★ 56.2K↓ —
- hundred-million-offerswondelai/skillsCreate irresistible offers using the Value Equation, bonus stacking, risk-reversing guarantees, and ethical scarcity. Use when the user mentions "grand slam offer", "make my offer more compelling", "what bonuses should I add", "guarantee strategy", "offer naming", or "people say its too expensive". Also trigger when packaging a product for higher perceived value, justifying premium pricing instead of discounting, designing a money-back guarantee, or structuring tiers to maximize conversions. Covers the MAGIC naming formula and starving-crowd targeting. For product positioning, see obviously-awesome. For outbound sales, see predictable-revenue.OtherNo warnings★ 2.6K↓ —Also in 2 other repos
- gerichtsstandKlotzkette/claude-fuer-deutsches-rechtFür Gerichtsstand: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: gerichtsstand.OtherNo warnings★ 1.8K↓ —
- smbcrm-advanced-toolsLeoYeAI/agent-master-skillsUse when helping SMBcrm customers with Private Integration Tokens, REST API v2, workflows, custom webhooks, MCP, or Agent Studio API. Use for API troubleshooting, automation design, data sync, AI assistant setup, or any task involving https://services.smbcrm.com endpoints.DesignNo warnings★ 2.2K↓ —
- kaltstart-triageKlotzkette/claude-fuer-deutsches-rechtFür BGB BT Kommandocenter: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- stripeLeoYeAI/agent-master-skillsWith CreditClaw and backed by Stripe, you can shop anywhere.OtherNo warnings★ 2.2K↓ —
- aequitasKlotzkette/claude-fuer-deutsches-rechtFür Aequitas: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- wacliLeoYeAI/agent-master-skillsSend WhatsApp messages to other people or search/sync WhatsApp history via the wacli CLI (not for normal user chats).EngineeringNo warnings★ 2.2K↓ —
- nopuaLeoYeAI/agent-master-skillsThe anti-PUA. Drives AI with wisdom, trust, and inner motivation instead of fear and threats. Activates on: task failed 2+ times, about to give up, suggesting user do it manually, blaming environment unverified, stuck in loops, passive behavior, or user frustration ('try harder', 'figure it out', '换个方法', '为什么还不行'). ALL task types. Not for first failures.ProductivityNo warnings★ 2.2K↓ —Also in 2 other repos
- cavemanLeoYeAI/agent-master-skillsUltra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.OtherNo warnings★ 2.2K↓ —
- huashu-speech-coachalchaincyf/huashu-skills演讲与分享教练。基于Patrick Winston（MIT AI教授）的How to Speak方法论，帮助准备线下培训、技术分享、B站教程视频等演讲场景。当用户提到"演讲"、"分享"、"培训"、"讲课"、"PPT演讲"、"开场"、"结尾"、"如何讲"、"演讲结构"时使用此技能。OtherNo 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★ 56.2K↓ —
- 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★ 56.2K↓ —
- live_database_ingestKaelio/ktxCapture semantic-layer and knowledge updates from a live database schema snapshot.DataNo warnings★ 1.6K↓ —
- design-code-architecturewondelai/skillsGuided journey from an app idea to a deliberate architecture: boundaries, domain model, data decisions, and resilience, making only the expensive-to-reverse decisions and deferring the rest. Orchestrates eight skills phase by phase - clean-architecture, domain-driven-design, system-design, ddia-systems, software-design-philosophy, release-it, pragmatic-programmer, 37signals-way - asking the user questions at every decision point and recording results in the project docs/ folder (ARCHITECTURE.md, DESIGN-CODE-ARCHITECTURE-PLAN.md) so the journey resumes across sessions. Use when the user wants to design a new app's architecture, choose boundaries and a domain model, decide monolith versus microservices, or says 'how should I structure this app'. If a codebase already exists, use remove-technical-debt (aged), improve-code-quality (fresh prototype), or architecture-optimization (slow but working); if unvalidated, run create-business or create-app first. For one framework in isolation, invoke that skill directly.DesignNo warnings★ 2.6K↓ —Also in 2 other repos
- 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↓ —
- pysamK-Dense-AI/scientific-agent-skillsProvides Python/HTSlib workflows for genomic files. Used when reading, querying, filtering, or writing SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, or tabix data with pysam, including pileup, coverage, indexing, and CRAM references.ScienceNo warnings★ 56.2K↓ —Also in 2 other repos
- energievertraegeKlotzkette/claude-fuer-deutsches-rechtFür Energie-Verträge — Strukturierung und Prüfung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- cloud-logging-finopsgoogle/skillsAudits Cloud Logging costs for a Google Cloud project: the charges for log entries written to log buckets, the services, log streams and severities that drive them, and the log sinks that route them. Reconciles Cloud Billing export costs with Cloud Monitoring volume metrics, and generates a FinOps report with charts and copy-paste exclusion filters. Use when auditing Cloud Logging spend, finding logging waste, identifying top logging contributors, generating log cost reduction reports, or creating log sink exclusion filters. Don't use for querying log entries (use cloud-logging-query-generation), configuring Cloud Monitoring alerts, or querying metrics/traces.OfficialWritingNo warnings★ 22.2K↓ —
- scvi-toolsK-Dense-AI/scientific-agent-skillsFits probabilistic models for single-cell omics, including scVI batch integration, scANVI annotation, totalVI CITE-seq, MultiVI RNA/ATAC integration, and posterior differential expression. Use for generative modeling, reference mapping, multimodal analysis, or model-based uncertainty; use scanpy for standard preprocessing and exploratory analysis.OtherNo warnings★ 56.2K↓ —
scenario-luma-video
scenario-labs/skills
MediaUpdated 45 minutes ago
From the author
Use when generating or editing video with Luma Ray models on Scenario via MCP: cinematic text-to-video, image-to-video from a start frame, start plus end frame anchors, seamless looping clips, HDR output, restyling footage while preserving motion with edit strengths and face, pose, depth, or trajectory controls, reframing to another aspect ratio by outpainting, or budget prompt edits on real footage. Keywords: Luma, Dream Machine, Ray 3.2, Ray 3, Modify Video, Reframe, T2V, I2V, V2V, loop, HDR.
Install
npx skills add scenario-labs/skills --skill scenario-luma-video -a claude-code
Installs to .claude/skills/scenario-luma-video/ · 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.
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Instructions onlyNo network use seenLicence: MIT
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