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 18 hours ago
49,492 skills
- live_database_ingestKaelio/ktxCapture semantic-layer and knowledge updates from a live database schema snapshot.DataNo warnings★ 1.6K↓ —
- historic_sql_patternsKaelio/ktxIdentify recurring cross-table historic-SQL analytical intents from a bounded pattern shard and emit typed pattern evidence for deterministic wiki projection.DataNo warnings★ 1.6K↓ —
- historic_sql_table_digestKaelio/ktxConvert one changed historic-SQL table usage bucket into typed table usage evidence for deterministic _schema projection.DataNo warnings★ 1.6K↓ —
- wiki_captureKaelio/ktxktx's knowledge base - wiki pages for durable, reusable business knowledge. Covers capture workflow for user preferences, metric definitions, organizational conventions, and cross-references between wiki pages and semantic-layer sources. Loaded by the post-turn memory-agent only. The research agent reads wiki via `wiki_read`/`wiki_search` but does not write it.ScienceNo warnings★ 1.6K↓ —
- looker_ingestKaelio/ktxExtract durable ktx knowledge and semantic-layer contribution proposals from staged Looker runtime dashboard, Look, and explore JSON. Load for WorkUnits whose raw files are under explores/, dashboards/, or looks/.OtherNo warnings★ 1.6K↓ —
- sl_captureKaelio/ktxHow to capture new reusable patterns into ktx's semantic layer - when a measure, segment, or join belongs in the catalog and how to write it generically so it stays small and useful over time. Loaded by the post-turn memory-agent only. The research agent does not write to the SL.ScienceNo warnings★ 1.6K↓ —
- metabase_ingestKaelio/ktxConvert Metabase questions, models, and metrics into ktx Semantic Layer source definitions. Covers result-metadata to KSL column type mapping, FK/PK detection, near-duplicate deduplication, pre-aggregation decomposition, join-graph connectivity, and how to react to priorProvenance from earlier ingest syncs. Load when the WorkUnit contains `cards/<id>.json` files under a Metabase bundle.EngineeringNo warnings★ 1.6K↓ —
- lookml_ingestKaelio/ktxMap a LookML view/model/explore into ktx semantic layer sources. Covers the LookML to ktx primitive table, provenance tagging, and three worked examples (overlay, standalone from derived_table, standalone with sql_always_where). Load when the turn contains `.lkml` content.OtherNo warnings★ 1.6K↓ —
- slKaelio/ktxktx's semantic layer - a structured catalog of sources (tables/views), measures, joins, and segments expressed as YAML. Covers the schema and how to query it via `sl_query`. Use when the task involves querying pre-defined metrics (ARR, churn, retention, LTV, MAU) or reading SL source YAML to understand the catalog. Capture is handled by the `sl_capture` skill (memory-agent only).ProductivityNo warnings★ 1.6K↓ —
- dbt_ingestKaelio/ktxMap dbt `schema.yml` / `properties.yml` models and sources into ktx semantic-layer overlays and column notes. Covers `sources:` vs `models:`, column `data_tests` (not_null, unique, accepted_values, relationships), and how bundle-time writes complement manifest backfill from git sync. Load when the WorkUnit's `skillNames` includes `dbt_ingest` or when raw files are dbt YAML under `models/` / `sources/`.DataNo warnings★ 1.6K↓ —
- ktx-analyticsKaelio/ktxUse when answering a question that needs data from a ktx-connected database - investigating, analyzing, "how many", "show me", "what's the breakdown of", finding records by value, exploring tables, comparing periods, explaining metrics, or any data-analysis request. Triggers even when the user does not say "analytics"; if the answer requires querying a configured ktx connection, this skill applies.DataNo warnings★ 1.6K↓ —
- hivemind-memoryactiveloopai/hivemindGlobal team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.ProductivityNo warnings★ 1.6K↓ —
- hivemind-memoryactiveloopai/hivemindGlobal team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.ProductivityNo warnings★ 1.6K↓ —
- hivemindactiveloopai/hivemindGlobal team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.ProductivityNo warnings★ 1.6K↓ —
- system-designwondelai/skillsDesign scalable distributed systems using structured approaches for load balancing, caching, database scaling, and message queues. Use when the user mentions "system design", "scale this", "high availability", "rate limiter", "design a URL shortener", "design Twitter", "design Uber", "design a news feed", "system design interview", "capacity planning", or "distributed architecture". Also trigger when estimating infrastructure requirements, choosing between microservices and monoliths, or designing for millions of concurrent users. Covers common system designs (TinyURL, feeds, chat) and back-of-the-envelope estimation. For data fundamentals, see ddia-systems. For resilience, see release-it.DesignNo warnings★ 2.6K↓ —Also in 2 other repos
- 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↓ —
- crossing-the-chasmwondelai/skillsNavigate the technology adoption lifecycle from early adopters to mainstream market. Use when the user mentions "crossing the chasm", "beachhead segment", "whole product", "early adopters vs mainstream", "tech go-to-market", "bowling pin strategy", "technology adoption lifecycle", "pragmatist buyers", "growth stalled after early adopters", or "our go-to-market plan". Also trigger when planning go-to-market for a technical product. Covers the D-Day analogy, bowling-pin strategy, the tornado, and positioning against incumbents. For product positioning, see obviously-awesome. For new market creation, see blue-ocean-strategy.MarketingNo warnings★ 2.6K↓ —Also in 2 other repos
- brainstormcodeaholicguy/ai-devkitAI DevKit · Use when the user asks to brainstorm, ideate, generate ideas, expand options, challenge ideas, pressure-test ideas, compare concepts, narrow choices, name something, plan content angles, explore strategy, evaluate product ideas, technical approaches, experiments, or decisions.PlanningNo warnings★ 1.7K↓ —
- dev-reviewcodeaholicguy/ai-devkitAI DevKit · Final code review phase guidance for holistic pre-push review. Use when the user wants code review, final lifecycle review, design alignment checks, integration risk review, or dev-lifecycle phase 9.EngineeringNo warnings★ 1.7K↓ —
- infographicsK-Dense-AI/scientific-agent-skillsCreates and reviews infographics with Nano Banana 2 via OpenRouter. Use for statistical summaries, timelines, comparisons, processes, and visual explanations with supplied data or optional Sonar research. Supports ten layouts, eight style presets, reference images, and accessible palette starting points.ScienceNo warnings★ 56.1K↓ —
- verwirkungKlotzkette/claude-fuer-deutsches-rechtFür Verwirkung von Handelsvertreter-Ansprüchen nach Paragraf 242 BGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- kaltstart-triageKlotzkette/claude-fuer-deutsches-rechtFür E-Commerce-Recht — Allgemein: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- einstieg-routingKlotzkette/claude-fuer-deutsches-rechtFür Einstieg und Routing: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Betreuungsrecht.OtherNo warnings★ 1.8K↓ —
- fehlzeiten-registerKlotzkette/claude-fuer-deutsches-rechtFür Fehlzeiten Register: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Einreichungsplan mit Form- und Nachweischeck.OtherNo warnings★ 1.8K↓ —
scvelo
K-Dense-AI/scientific-agent-skills
From the author
Performs RNA velocity analysis with scVelo from spliced and unspliced single-cell RNA counts. Fits deterministic or dynamical models, examines gene phase portraits, builds velocity graphs, estimates relative latent time, and ranks velocity-associated genes. Use for directional trajectory hypotheses and kinetic-model diagnostics alongside Scanpy; velocity alone does not establish cell fate or causal drivers.
Install
npx skills add K-Dense-AI/scientific-agent-skills --skill scvelo -a claude-code
Installs to .claude/skills/scvelo/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Safety checks on SKILL.md
- Ships scripts we have not reviewedLow
Why 89
Files (3)
- SKILL.md
- references/velocity_models.md
- scripts/rna_velocity_workflow.py