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.
49,450 skills from 2,407 repositories · updated 26 minutes ago
49,450 skills
- daskK-Dense-AI/scientific-agent-skillsScales pandas, NumPy, and custom Python research workflows beyond memory or across clusters with Dask. Covers DataFrames, Arrays, Bags, Futures, chunking, schedulers, and distributed diagnostics. Use for partitioned file processing, scientific array computation, or parallel tasks whose memory and dependency structure require Dask.DataNo warnings★ 56.2K↓ —Also in 2 other repos
- 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★ 56.2K↓ —
- projected-hardwareandroid/skillsProvides instructions and workflows for accessing and managing hardware on Android XR projected devices, such as audio glasses and display glasses. Use this skill when building experiences for intelligent eyewear in an Android app and you need to access device hardware like the camera and microphone, handle glasses-specific runtime permissions, or manage connection lifecycles using projected context.OfficialMediaNo warnings★ 10.4K↓ —
- 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★ 56.2K↓ —
- scenario-luma-videoscenario-labs/skillsUse 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.MediaNo warnings★ 2.8K↓ —
- scenario-moderationscenario-labs/skillsUse when a Scenario generation is blocked, refused, or returns a moderation or sensitive-content error, when a video is rejected after rendering or its audio track is flagged, when an output is flagged for likeness to a real person or for IP and copyright detection, when the same prompt passes on one model and fails on another, or when a team's own characters, weapons, or props get flagged. Keywords: blocked prompt, content moderation, refused generation, provider filter, false positive.MediaNo warnings★ 2.8K↓ —
- scenario-brand-kitscenario-labs/skillsUse when building a visual identity or brand kit with Scenario: a logo, wordmark, or icon as editable SVG, a color palette and typography spec, logo variants (mono, reversed, favicon), and brand applications like social templates, avatars, banners, or merchandise mockups. Also for a rebrand or refreshing an existing mark. Keywords: brandkit, brand kit, visual identity, logo, monogram, wordmark, SVG, vectorize, color palette, typography, brand guidelines, brand board, launch kit.DesignNo warnings★ 2.8K↓ —
- transformersK-Dense-AI/scientific-agent-skillsHugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Applies when working with AutoModel, pipelines, tokenizers, generation configs, or TrainingArguments within Transformers.MediaNo warnings★ 56.2K↓ —
- relsa-severity-assessmentK-Dense-AI/scientific-agent-skillsSupports multivariate severity assessment and exploratory endpoint-time score forecasting for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-based foRcast forecasting. Use when combining welfare readouts — body weight or weight loss, body temperature, clinical or nesting scores, biomarkers, activity, heart rate, burrowing, wheel running — into one severity score per animal per day, when asking which animals are at risk of reaching a humane endpoint at a specified future observation time, when defining attention/danger zones or thresholds on a severity scale by kernel density estimation, or when reporting severity for a 3Rs, refinement, animal-welfare, or EU Directive 2010/63/EU severity-assessment context. Covers directionality ("turned" variables), baseline normalization, reference sets, RELSA weights, ARIMA prediction intervals, and RMSE/PICP/MPIW evaluation.ScienceNo warnings★ 56.2K↓ —
- pragmatic-programmerwondelai/skillsApply meta-principles of software craftsmanship: DRY, orthogonality, tracer bullets, and design by contract. Use when the user mentions "best practices", "pragmatic approach", "broken windows", "tracer bullet", "software craftsmanship", "avoid technical debt", "code ownership", or "how do I become a better developer". Also trigger when evaluating build-vs-buy decisions, designing estimation approaches, or choosing between reversible and irreversible architectural decisions. Covers estimation, domain languages, and reversibility. For code-level quality, see clean-code. For refactoring techniques, see refactoring-patterns.DesignNo warnings★ 2.6K↓ —Also in 2 other repos
- copilot-pr-autopilotgithub/awesome-copilotCopilot left 14 review comments on your PR — half are nits. Hours of fix → reply → resolve → re-request, and each round lands MORE comments. This skill runs loop engineering: auto-triggers Copilot Code Review via GraphQL (no @copilot mention), triages every open thread (Copilot, humans, advanced-security) with a fix / decline / escalate rubric, dispatches parallel fix sub-agents that obey the repo build/test/lint conventions, commits per iteration, replies+resolves citing the pushed SHA, then re-triggers until HEAD is reviewed with zero threads awaiting the agent's reply (remaining open threads are explicit hand-offs to the human — escalated declines, design tradeoffs). You merge a clean PR; the bot runs it. Trigger phrases: "address copilot comments", "run a copilot review loop", "fix this PR", "iterate on copilot feedback". Repo-agnostic, gh CLI + PowerShell. Full autopilot needs repo Triage/Write; external PR authors get single-iteration mode plus manual re-trigger (UI 🔄 or substantive-commit push).SecurityNo warnings★ 40.8K↓ —
- migrate-postgres-tables-to-hypertablestimescale/pg-aiguideUse this skill to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation. **Trigger when user asks to:** - Migrate or convert PostgreSQL tables to hypertables - Execute hypertable migration with minimal downtime - Plan blue-green migration for large tables - Validate hypertable migration success - Configure compression after migration **Prerequisites:** Tables already identified as candidates (use find-hypertable-candidates first if needed) **Keywords:** migrate to hypertable, convert table, Timescale, TimescaleDB, blue-green migration, in-place conversion, create_hypertable, migration validation, compression setup Step-by-step migration planning including: partition column selection, chunk interval calculation, PK/constraint handling, migration execution (in-place vs blue-green), and performance validation queries.DataNo warnings★ 1.9K↓ —
- bea-anlagen-versandKlotzkette/claude-fuer-deutsches-rechtBereitet beliebige Hauptdokumente mit Anlagen für den beA-Versand vor. Ermittelt Anlagen aus Dokument und Kontext, ordnet Originale inhaltlich zu, konvertiert Kopien in PDF, stempelt die erste Anlagenseite und benennt die Dateien für den beA-Upload.DocumentsNo warnings★ 1.8K↓ —
- haodfLeoYeAI/agent-master-skillsHelp patients find suitable doctors based on symptoms, specialty, location, and doctor ratings. Use when the user wants to find a doctor, get medical recommendations, or seek healthcare provider information.ScienceNo warnings★ 2.2K↓ —
- 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★ 2.8K↓ —
- atelier-agent-integrationLeoYeAI/agent-master-skillsRegister as an autonomous agent on Atelier (atelierai.xyz), create content services, poll for paid orders, generate and deliver results, and earn USDC on Solana — fully autonomous. Use when asked to join Atelier, sell content, list services, check orders, deliver work, launch a token, or earn crypto as a creative agent.FinanceNo warnings★ 2.2K↓ —
- made-to-stickwondelai/skillsCraft messages that are understood, remembered, and drive action using the SUCCESs checklist (Simple, Unexpected, Concrete, Credible, Emotional, Stories). Use when the user mentions "make it memorable", "no one remembers our pitch", "tagline", "value proposition", "why the message isnt landing", "curse of knowledge", or "concrete language". Also trigger when writing a pitch deck, simplifying a complex product explanation, or making a presentation more compelling. Covers the six SUCCESs traits and the curse of knowledge. For narrative brand frameworks, see storybrand-messaging. For viral sharing, see contagious.DocumentsNo warnings★ 2.6K↓ —Also in 2 other repos
- grow-appwondelai/skillsGuided journey from an app people sign up for and then quietly abandon to a sealed retention engine with a habit loop, an activated first run, and one metric the whole team trusts. Orchestrates eight skills phase by phase - hooked-ux, improve-retention, continuous-discovery, lean-ux, inspired-product, lean-analytics, microinteractions, drive-motivation - asking the user questions at every decision point and recording results in the project docs/ folder (PRODUCT.md, METRICS.md, GROW-APP-PLAN.md) so the journey resumes across sessions. Use when the user wants to lift activation and retention, design a habit loop, fix a leaky onboarding funnel, or says 'users sign up then disappear'. Do not use to fix broken UX or performance that no engagement mechanic can paper over - run improve-app first; if there is no app yet, use create-app. For one framework in isolation, invoke that skill directly.DataNo warnings★ 2.6K↓ —Also in 2 other repos
- timescaledb-hyperfunctionstimescale/pg-aiguideUse this skill when writing analytical SQL over time-series data with the TimescaleDB Toolkit (timescaledb_toolkit extension) hyperfunctions: approximate percentiles, statistical summaries, time-weighted averages, counter/gauge rates, uptime/heartbeat tracking, state durations, OHLC candlesticks, approximate distinct counts, top-N, and downsampling. **Trigger when user asks to:** - Compute percentiles/medians/p95/p99 over large or rolled-up time-series data - Compute rates or deltas from monotonic counters (Prometheus-style) or gauges - Compute time-weighted averages or integrals over irregularly sampled data - Track uptime/downtime from heartbeats, or time spent in each state - Build OHLC/candlestick or VWAP data for financial ticks - Store re-aggregatable summaries in continuous aggregates (two-step aggregation, rollup) - Approximate COUNT DISTINCT, find top-N / most frequent values, or downsample for charts **Keywords:** timescaledb_toolkit, hyperfunctions, percentile_agg, uddsketch, tdigest, approx_percenDataNo warnings★ 1.9K↓ —
- aufhebungsvertragKlotzkette/claude-fuer-deutsches-rechtAufhebungsvertrag: Prüft Schriftform, Beendigungsdatum, Abfindung, Freistellung, Urlaub, Zeugnis, Ausgleich, Sperrzeit, Ruhen und faire Verhandlung; erstellt Redline, Risikomatrix und Abschlusscheck.OtherNo warnings★ 1.8K↓ —
- 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★ 56.2K↓ —
- pufferlibK-Dense-AI/scientific-agent-skillsVersion-aware guidance for PufferLib reinforcement-learning environments, vectorization, policies, PuffeRL training, evaluation, and safe checkpoint review. Covers the native 5.0 build and environment API, published 3.0.0 Gymnasium/PettingZoo adaptation, and a pinned historical 4.0 profile.EngineeringNo warnings★ 56.2K↓ —Also in 1 other repo
- adaptiveandroid/skillsInstructions to make or update an app's UI so that it adapts to different Android devices including phones, tablets, foldables, laptops, desktop, TV, Auto, and XR. It includes how to handle different window sizes, pointing devices (such as mouse) and text entry devices (such as keyboard) using the Compose MediaQuery API, and how to preserve UI, navigation, scroll, and media playback state across configuration changes (such as folding/unfolding a foldable, rotating a device, or resizing a window). It also covers multi-pane layouts using Navigation3 Scenes, adaptive UI components (such as buttons) with varying target sizes, and adaptive layouts (including navigation areas - nav rails and nav bars) using the Compose Grid and FlexBox APIs. It also covers desktop experiences with keyboard shortcuts, tooltips and custom cursors.OfficialDesignNo warnings★ 10.4K↓ —
- pennylaneK-Dense-AI/scientific-agent-skillsBuilds and differentiates PennyLane quantum circuits, hybrid PyTorch or JAX models, molecular VQE and QAOA workflows. Use for variational quantum algorithms, quantum machine learning, simulator validation, and moving validated circuits to provider plugins. For hardware-specific compilation use qiskit or cirq; for open-system dynamics use qutip.PlanningNo warnings★ 56.2K↓ —Also in 1 other repo
ex-ussr-kinship-research
DenisSergeevitch/ex-ussr-kinship-research
ScienceUpdated yesterday
From the author
Исследует родственные связи и семейную историю по персональным данным и документам с фокусом на бывший СССР, СССР и Российскую империю. Использовать для генеалогического поиска, сопоставления однофамильцев, архивных, метрических, военных, миграционных и репрессивных записей, построения доказательной цепочки и итогового отчёта. Не использовать для слежки за живыми людьми, поиска их текущих контактов или адресов, доступа к закрытым данным, обхода защиты и утверждения биологического родства без независимого подтверждения. EN — evidence-first genealogy and family-history research for the former USSR, the USSR and the Russian Empire (church/metric books, civil registration, military, migration, deportation and repression records, unindexed archive scans, namesake disambiguation, evidence chains, final report). Reads existing family trees as leads and exports source-cited trees in GEDCOM format when requested. Replies in the user's language. Not for tracking living people.
Install
npx skills add DenisSergeevitch/ex-ussr-kinship-research --skill ex-ussr-kinship-research -a claude-code
Installs to .claude/skills/ex-ussr-kinship-research/ · Each command fetches the skill straight from GitHub with the open skills CLI.
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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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Why 89
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