Skills.

Give your AI a better way to work.

A skill is a set of written instructions that teaches an AI how to do one job the way it should be done: review a pull request, plan a migration, write the release notes.

Install one here and it travels with your account into Claude, Claude Code, Cursor and every other client you sign in with.

Category: Databases & data

2,457 results · page 44 of 82

  • optimize-loopSkillDatabases & data

    Use when the user wants to iteratively improve an artifact under a hard correctness bound while minimizing a measured cost — refactoring a code module to cut complexity while its test suite stays green, OR speeding up a SQL query while it returns the same rows. Each iteration applies one focused cha

    Ready to connect★ 169

    github.com/gaasher/agent-loop-skills169 stars

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  • scientific-writerSkillDatabases & data

    Use when the user has a scientific draft (with its dataset, figures, and optional analysis code) and wants it iteratively revised until it clears a quality bar. Five specialist judges (figures, scientific content, style, formatting, code) critique the draft; a fresh, independent peer_reviewer grades

    Ready to connect★ 169

    github.com/gaasher/agent-loop-skills169 stars

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  • comprehensive-variant-annotationSkillDatabases & data

    Given an rsID, query multiple databases (dbSNP, FAVOR, GWAS Catalog, ClinVar, gnomAD, PharmGKB, ClinGen) for comprehensive annotation. Use when user asks a general question about a variant without specifying which aspect.

    Ready to connect★ 167

    github.com/internscience/scp166 stars

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  • gene-knowledge-integrationSkillDatabases & data

    Given a gene symbol (e.g. TPMT), query 3 public databases (ClinGen CAR, PharmGKB, Monarch) to obtain gene registry info, FDA drug labels, clinical annotations, and gene-phenotype associations. Save all results into a JSON file.

    Ready to connect★ 167

    github.com/internscience/scp166 stars

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  • dbSkillDatabases & data

    Use when inspecting, debugging, or understanding the GOAT PostgreSQL database — querying projects, layers, users, orgs, teams, roles, scenarios, jobs, or checking data state during local dev.

    Ready to connect★ 165

    github.com/plan4better/goat164 stars

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  • windmillSkillDatabases & data

    Use when working with GOAT's Windmill instance — running or syncing analytics tools, inspecting job execution, adding a new tool, or checking which f/goat/tools/* scripts exist. Use the Windmill MCP tools for API calls.

    Ready to connect★ 165

    github.com/plan4better/goat164 stars

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  • chem-db-mofSkillDatabases & data

    Query multiple MOF databases (QMOF via MPContribs; ARC-MOF DB7/Majumdar et al. via Zenodo) and download CIF structures with optional element or identifier filters.

    Ready to connect★ 164

    github.com/learningmatter-mit/atomisticskills158 stars

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  • chem-db-qmofSkillDatabases & data

    Query the Quantum MOF (QMOF) database via Materials Project's MPContribs platform for DFT-computed properties (bandgap) and optimized crystal structures of Metal-Organic Frameworks.

    Ready to connect★ 164

    github.com/learningmatter-mit/atomisticskills158 stars

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  • chem-spectrum-matcherSkillDatabases & data

    Match an experimental spectrum (1H NMR, 13C NMR, IR) against predicted or database reference spectra for candidate ranking and structure confirmation. Supports local catalog lookup, public database fallback, and pluggable similarity metrics.

    Ready to connect★ 164

    github.com/learningmatter-mit/atomisticskills158 stars

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  • general-query-literature-databaseSkillDatabases & data

    Find relevant simulation workflows in the in-house literature database.

    Ready to connect★ 164

    github.com/learningmatter-mit/atomisticskills158 stars

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  • mat-calphad-phase-diagramSkillDatabases & data

    Calculate and plot multi-component temperature-composition phase diagrams from Thermodynamic Database (.tdb) files using CALPHAD methods.

    Ready to connect★ 164

    github.com/learningmatter-mit/atomisticskills158 stars

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  • mat-db-mpSkillDatabases & data

    Query Materials Project database for crystal structures, computed properties, elastic/magnetic data, and structurally similar materials using the MP API.

    Ready to connect★ 164

    github.com/learningmatter-mit/atomisticskills158 stars

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  • mat-db-optimadeSkillDatabases & data

    Query the Crystallography Open Database (COD) and other OPTIMADE-compliant databases for experimental crystal structures.

    Ready to connect★ 164

    github.com/learningmatter-mit/atomisticskills158 stars

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  • mat-synthesis-recommendationSkillDatabases & data

    Query and rank synthesis recipes from Materials Project's text-mined literature database with precursors, procedures, and journal references.

    Ready to connect★ 164

    github.com/learningmatter-mit/atomisticskills158 stars

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  • ml-fairchem-finetuneSkillDatabases & data

    Fine-tune Fairchem machine learning interatomic potentials (UMA, ESEN) on custom datasets.

    Ready to connect★ 164

    github.com/learningmatter-mit/atomisticskills158 stars

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  • ml-mace-finetuneSkillDatabases & data

    Fine-tune MACE machine learning interatomic potentials on custom datasets.

    Ready to connect★ 164

    github.com/learningmatter-mit/atomisticskills158 stars

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  • ml-matgl-finetuneSkillDatabases & data

    Fine-tune MatGL machine learning interatomic potentials on custom datasets.

    Ready to connect★ 164

    github.com/learningmatter-mit/atomisticskills158 stars

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  • ml-mlip-benchmarkSkillDatabases & data

    Benchmark MLIP accuracy against a labeled dataset — compute MAE/RMSE for energy/atom and forces, and generate parity plots.

    Ready to connect★ 164

    github.com/learningmatter-mit/atomisticskills158 stars

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  • agricultural-data-scientistSkillDatabases & data

    Expert agricultural data scientist with 12+ years in precision agriculture, remote sensing, and farm analytics. Specializes in yield prediction, variable rate application, satellite imagery analysis, and decision support systems. Use when: precision-agriculture, remote-sensing, yield-prediction, ag-

    Ready to connect★ 163

    github.com/theneoai/awesome-skills158 stars

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  • ai-application-engineerSkillDatabases & data

    Expert-level AI Application Engineer with deep knowledge of RAG systems, LangChain, LlamaIndex, vector databases, prompt engineering, LLM API integration, and agent frameworks

    Ready to connect★ 163

    github.com/theneoai/awesome-skills158 stars

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  • end-to-end-autonomous-researcherSkillDatabases & data

    Expert-level End-to-End Autonomous Driving Researcher specializing in UniAD/VAD/DriveLM architectures, BEV perception, transformer-based world models, and rigorous closed-loop evaluation on nuScenes and Waymo Open Dataset benchmarks. Use when: e2e-autonomous, bev-perception, imitation-learning, worl

    Ready to connect★ 163

    github.com/theneoai/awesome-skills158 stars

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  • kmp-starter-dataSkillDatabases & data

    Data layer on the KMP Starter Template — repositories and data sources, Logics guidance, DataStore persistence, Room database, StarterFileManager, and the Calf file picker.

    Ready to connect★ 162

    github.com/devatrii/kmp-starter-template162 stars

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  • kmp-starter-feature-analyticsSkillDatabases & data

    The KMP Starter Template analytics system — AppEvent/EventsTracker, Analytics routing, Mixpanel + Firebase providers, combining providers, and runtime swaps.

    Ready to connect★ 162

    github.com/devatrii/kmp-starter-template162 stars

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  • kmp-starter-feature-databaseSkillDatabases & data

    The KMP Starter Template Room database — entities, DAOs, migrations, and DB configuration in features/database. How to add tables and bump versions safely.

    Ready to connect★ 162

    github.com/devatrii/kmp-starter-template162 stars

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  • kmp-starter-featuresSkillDatabases & data

    How to reuse the KMP Starter Template's built-in feature modules — Analytics, Remote Config, Purchases, Database, Store Reviews & Updates, Splash/Onboarding, Notifications, and Locale. Each feature has a dedicated child skill.

    Ready to connect★ 162

    github.com/devatrii/kmp-starter-template162 stars

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  • piper-tts-trainingSkillDatabases & data

    Train custom TTS voices for Piper (ONNX format) using fine-tuning or from-scratch approaches. Use when creating new synthetic voices, fine-tuning existing Piper checkpoints, preparing audio datasets for TTS training, or deploying voice models to devices like Raspberry Pi or Home Assistant. Covers da

    Ready to connect★ 160

    github.com/sammcj/agentic-coding159 stars

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  • concept-rediscovery-walkSkillDatabases & data

    Guides a learner to invent a math or ML concept themselves through a Socratic walk — a sequence of small guessable questions that ends with the learner stating the formal definition unprompted. The 3Blue1Brown signature move. Use when the learner is meeting a foundational concept (eigenvectors, grad

    Ready to connect★ 159

    github.com/lyndonkl/claude151 stars

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  • data-schema-knowledge-modelingSkillDatabases & data

    Creates rigorous, validated models of entities, relationships, and constraints for database schemas (SQL, NoSQL, graph), knowledge graphs, ontologies, API data models, and taxonomies. Covers relational, document, graph, event/time-series, and dimensional schema patterns with lifecycle modeling, soft

    Ready to connect★ 159

    github.com/lyndonkl/claude151 stars

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  • financial-data-sourcingSkillDatabases & data

    Maps every input a company analysis needs to where it comes from — filing line items, market data, Damodaran reference datasets, macro series — with units, update frequency, acceptable fallbacks and the consistency rules that bind them. Use when gathering data for a valuation, when an input is missi

    Ready to connect★ 159

    github.com/lyndonkl/claude151 stars

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  • graphrag-system-designSkillDatabases & data

    Designs complete GraphRAG systems integrating graph databases, vector stores, orchestration frameworks, and LLM reasoning. Guides through pattern selection, technology stack decisions, integration pipeline design, and domain-specific customizations. Use when designing GraphRAG systems, choosing tech

    Ready to connect★ 159

    github.com/lyndonkl/claude151 stars

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What is a skill?

A skill is plain text, usually a SKILL.md file and the scripts it refers to, written for an AI rather than for a person. It carries the steps, the house rules and the examples a good answer needs, so you stop pasting the same briefing into every new chat.

55,111 of the 55,543 skills listed here can be served through ahel today, and they come from public repositories. Each one has its own page with the instructions themselves on it, so you can read what a skill will tell your AI to do before you install it.

Install one and every AI you use gets it

Installing a skill adds it to your gateway and turns it on in the same step. Claude Code surfaces it as a slash command; any client can read the full instructions with the skill_read tool.

Nothing is copied into a project folder. The instructions are served from your account, so the same skill is there in every AI you connect, and turning it off removes it from all of them at once.

See how to connect your AI