Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
A local WeChat digital asset library: supports full local parsing on macOS and tested Windows environments, including full-library collection, authentication and decryption, chat history reading/search/export, and parsing Moments and Favorites content. Mac also supports incremental refresh and checks for missed messages or pending replies. WeChat 1 is the default; WeChat 2 must be explicitly specified. On Windows, local collection uses windows, offline chat queries use snapshot, and Moments/Favorites reuse the package's pure-function workflow; this does not trigger Mac configuration or workflows. When the latest chats are needed, refresh the corresponding source first; old records cannot substitute for the requested data. See the local collection reference for Windows versions and feature boundaries.
Audits a self-hosted CockroachDB cluster against the CIS CockroachDB Benchmark v1.0.0 Level 1 controls. Supports two audit depths — quick automated scans and full CIS audit procedures. Produces a structured PASS/FAIL/MANUAL report covering installation, system hardening, logging, user access, data protection, and CockroachDB settings. Use when preparing for CIS compliance assessments, hardening self-hosted deployments, or validating security posture against industry benchmarks.
Best practices for AutoML and hyperparameter search with Optuna, Ray Tune, and PyCaret, covering search-space design, validation splits, and leakage prevention. Use when tuning model hyperparameters, setting up a pruned or distributed hyperparameter search, designing a nested validation scheme, or evaluating whether an AutoML leaderboard result is production-ready.
Tonghuashun iFinD (51ifind.com) financial data queries. Supports 18 API endpoints for real-time quotes, historical quotes, financial indicators, macroeconomic data, and more across A-shares, funds, bonds, futures, and indices. Chinese financial data query skill powered by THS iFinD (51ifind.com) API. Covers real-time quotes, historical data, financial indicators, macro economics, fund valuation, and more across 18 API endpoints for A-shares, funds, bonds, futures, and indices.
Database Lookup provides unified programmatic access to 78+ scientific and public databases spanning chemistry (PubChem, ChEMBL), biology (UniProt, COSMIC, Ensembl), clinical (ClinicalTrials.gov, FDA), economics (FRED, World Bank), and intellectual property (USPTO, EPO).
Selects a base model and fine-tuning technique (SFT, DPO, or RLVR) for the user's use case by querying SageMaker Hub. Use when the user asks which model or technique to use, wants to start fine-tuning, or mentions a model name or family (e.g., "Llama", "Mistral") — always activate even for known model names because the exact Hub model ID must be resolved. Queries available models, validates technique compatibility, and confirms selections.
Gangtise open platform investment research data service. Provides knowledge base search (broker research reports, announcements, meeting minutes), company earnings forecasts, economic data indicator queries, conference call lists, and research report source download. Use when users ask about stocks, companies, industries, macroeconomic data, or research reports.
WeChat Official Account investment blogger distiller. From Official Account article data, it automatically extracts a seven-dimension DNA profile — trading system, market judgment, expression style, content depth, engagement features, hot-topic map, and persona genes — and outputs a structured style profile. Trigger words: distill investment blogger, distill influencer, distill Official Account influencer, analyze investment blogger style, extract trading system, style profile, investment blogger distillation.
Guide to KEGG pathway enrichment for DEG results. Covers ORA vs GSEA, mandatory directionality splitting, KEGG organism codes, API failure handling with offline fallbacks, cross-condition comparisons, and answer-first reporting. Consult when running enrichment with clusterProfiler or gseapy.
Integrates Apache ECharts into UniApp and UniAppX projects for cross-platform data visualization (H5, mini-programs, native App). Supports line, bar, pie, scatter, radar, gauge, funnel, heatmap, and more chart types. Use when the user needs to create ECharts charts in UniApp/UniAppX or configure interactive data visualizations for mobile and web.
lyt series e-commerce business data analysis skill. Use after the user provides text metrics, images/screenshots, CSV/XLSX tables, PDFs/reports, competitor data or backend exports: first do data health checks and metric-definition validation, then break down TikTok Shop, product cards, short videos, livestreams, GMV Max, ads, costs, profit and store operations issues. Suited to reviews, comparisons, problem finding, scaling/pausing decisions, profit estimates and report output; does not replace zero-based product selection, feasibility validation for existing products, explanations of platform traffic mechanics, or follow-up questioning on vague operational problems. Triggers: /lyt-data-analysis, /数据分析, /数据复盘, /经营复盘, "帮我看数据" "分析这个表格" "复盘这组截图"
Multi-modal single-cell analysis with muon/MuData. Joint RNA+ATAC (10x Multiome), CITE-seq (RNA+protein), other multi-omics. MuData holds per-modality AnnData with shared obs. WNN joint embedding, per-modality preprocessing, MOFA factor analysis. Use scanpy-scrna-seq for single-modality RNA; use muon when combining 2+ omics from the same cells.
Use when writing or running Nushell commands, scripts, or pipelines - via the Nushell MCP server (mcp__nushell__evaluate), via Bash (nu -c), or in .nu script files. Also use when working with structured data (JSON, YAML, TOML, CSV, Parquet, SQLite), doing ad-hoc data analysis or exploration, or when the user's shell is Nushell.
Create and edit Obsidian Bases (.base files) with views, filters, formulas, and summaries. Use when working with .base files, creating database-like views of notes, or when the user mentions Bases, table views, card views, filters, or formulas in Obsidian.
Build Solana trading and intelligence applications combining OKX DEX aggregation with Helius infrastructure. Integration-only layer — describes when and how to compose OKX tools with Helius tools for swaps, token discovery, smart money signals, meme token analysis, and portfolio intelligence.
Query OpenAlex REST API for 250M+ scholarly works, authors, institutions, journals, concepts. Search by keyword, author, DOI, ORCID, or ID; filter by year, OA, citations, field; retrieve citations, references, author disambiguation. Free, no auth. For PubMed use pubmed-database; preprints use biorxiv-database.
Pipeline skill for automating prior authorization decision workflows. Use when the user asks to parse PA request data (X12 278 or FHIR PAS bundles), extract clinical features for adjudication, build rules-based PA decision engines, train ML classifiers on historical PA decisions, analyze denial patterns, or generate SHAP explanations for PA outcomes. Triggers include "parse 278", "FHIR PAS bundle", "PA automation", "adjudication logic", "PA classifier", "denial analysis", "prior auth ML", "SHAP explainability", "PA feature extraction", "rules engine PA", "PA decision pipeline", "authorization workflow", "clinical criteria extraction", "denial pattern mining", "PA turnaround time".
Use when: you need to design product data metrics, plan data tracking, build a data monitoring system, or perform data analysis and trend forecasting. Do NOT use when: the data metrics are already clear, or only simple statistics are needed without a metric system.
Use when building, debugging, or evaluating CloudBase PostgreSQL / CloudBase PG / PG mode apps, including Postgres schema setup, queryPgDatabase/managePgDatabase, JS SDK v3 app.rdb() CRUD/RPC, PG HTTP API fallback, RLS-style permissions, username-password auth, and Web CMS/admin CRUD flows backed by CloudBase PG.
The full Supabase Management API (108 endpoints) plus a local SQLite cache of orgs, projects, functions, branches, and secret names — powering cross-project queries no live API answers in one call, with Auth Admin lookup, PostgREST schema introspection, and Storage usage rollup on top. Trigger phrases: `supabase auth admin lookup`, `supabase secret name audit`, `supabase branches drift`, `supabase project estate rollup`, `supabase storage usage`, `supabase pgrst schema`, `use supabase`, `run supabase`. Anti-triggers: `supabase start` (use the official supabase CLI), `supabase db push` (official CLI), `supabase gen types` (official CLI), supabase realtime subscribe (WebSocket — out of scope).
Guidance for an end-to-end Microsoft Purview information governance / information protection strategy - sequencing classification, labelling, protection, lifecycle, and risk into a coherent program aligned to the Zero Trust data pillar. Covers maturity-based rollout sequencing, ownership, and metrics. WHEN: information governance, information protection strategy, data protection program, sequence Purview rollout, MIP strategy, protect and govern data end to end, Zero Trust data pillar program, Purview roadmap, data security maturity.
Reason about quantitative proteomics experiment design and data analysis strategy. Use when the user asks to choose between LFQ, TMT, and DIA quantification; select an imputation method for missing values; pick a normalization strategy; interpret differential expression results from proteomics data; evaluate ratio compression; or design a proteomics study for biomarker discovery or validation. Triggers include "LFQ vs TMT", "DIA quantification", "proteomics normalization", "missing value imputation", "MNAR", "MinProb", "QRILC", "kNN imputation", "VSN normalization", "median centering", "quantile normalization", "limma proteomics", "ratio compression", "proteomics study design", "label-free quantification", "tandem mass tag", "data-independent acquisition", "DIA-NN", "Spectronaut", "MaxQuant LFQ", "proteomics differential expression", "empirical Bayes proteomics", "proteinGroups.txt", "MSFragger output", "TMT normalization code", "LFQ analysis", "proteomics pipeline R", "MaxQuant output".
Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.
Pipeline skill for CMS-HCC risk adjustment calculation and coding gap identification. Use when the user asks to apply the ICD-10-to-HCC crosswalk, calculate RAF scores, resolve disease hierarchies programmatically, identify coding gaps from Rx or lab proxies, project member-level risk scores, build a risk adjustment data pipeline, compute HCC coefficients, run hierarchy resolution code, or generate member risk score reports. Triggers include "calculate RAF score", "ICD-10 to HCC crosswalk", "hierarchy resolution code", "coding gap detection", "Rx proxy gap", "lab proxy gap", "risk score projection", "HCC pipeline", "member risk report", "risk adjustment Python", "risk adjustment SQL", "RAF calculation code", "CMS-HCC pipeline".
Reasoning skill for clinical risk stratification index selection and interpretation. Use when the user asks about LACE scores, Charlson Comorbidity Index, Elixhauser Index, readmission risk scoring, comorbidity weighting, SDOH Z-codes, Area Deprivation Index, or population health stratification methods.
Bulk RNA-seq analysis pipeline covering alignment (STAR), quantification (Salmon, featureCounts), and differential expression (DESeq2). Triggers on RNA-seq, STAR, Salmon, DESeq2, differential expression, gene expression, tximport, featureCounts, transcriptomics, "bulk RNA-seq", "STAR alignment", "Salmon quantification", "gene counts", "DESeq2 results", "shrinkage estimator", "volcano plot RNA-seq".
Explore an existing PostgreSQL database before answering questions about its data or writing SQL. Use this skill whenever a user asks for a query or a data-backed answer against an unfamiliar schema (counts, missing or failed records, recent changes), asks where a business concept lives, or asks how tables, joins, views, routines, triggers, RLS, or extensions work. Find the relevant objects with read-only pg_catalog queries, then request approval before inspecting data-derived statistics or rows. Not a schema-design or migration guide
Manipulation and analysis of planar geometric objects. Based on the widely deployed GEOS library. Provides data structures for points, curves, and surfaces, and standardized algorithms for geometric operations. Use for 2D geometry operations, spatial relationships, set-theoretic operations (intersection, union, difference), point-in-polygon queries, geometric calculations (area, distance, centroid), buffering, simplifying geometries, linear referencing, and cleaning invalid geometries. Essential for GIS operations, spatial analysis, and geometric computations.
Comprehensive Supabase expert with access to 2,616 official documentation files covering PostgreSQL database, authentication, real-time subscriptions, storage, edge functions, vector embeddings, and all platform features. Invoke when user mentions Supabase, PostgreSQL, database, auth, real-time, storage, edge functions, backend-as-a-service, or pgvector.
Provides empirical test protocols and metrics to validate whether hypothesized symmetries actually hold in data or models before committing to equivariant architecture. Includes invariance/equivariance testing, group structure verification, and distribution analysis under transforms. Use when testing invariance, validating equivariance, checking symmetry assumptions, debugging symmetry-related model failures, or needing data-driven validation before architecture decisions.
Guides advanced social science research methods — discourse analysis (Fairclough CDA, Gee), conversation analysis, quantitative content analysis, Qualitative Comparative Analysis (QCA), process tracing, archival research, participatory/community-based research (PAR, CBPR), Delphi and Q methodology, social network analysis (SNA), bibliometrics and scientometrics, systematic mapping reviews, and program/policy evaluation. Use when designing or conducting any of these studies — choosing a specialized method, building a coding scheme, establishing causal mechanisms in case studies, mapping relational or subjective data, or applying an evaluation framework. For interpretive coding (thematic analysis, grounded theory, IPA, ethnography) use alterlab-qualitative-methods; for qual+quant integration use alterlab-mixed-methods; to run QCA, SNA, or text-as-data analyses on data use alterlab-qca, alterlab-sna, or alterlab-text-as-data. Part of the AlterLab Academic Skills suite.
Use for analytical thinking, or when a question needs breaking down and evidence: "why did metric X drop?", "what drives this?", "break this down", "what data do we need?". Builds a tree, hypotheses and evidence, ends with an answer and key uncertainty. Skip for quick verdicts.
Work with raster and imagery data using ImageryLayer, ImageryTileLayer, pixel filtering, raster functions, multidimensional data, and oriented imagery. Use for satellite imagery, elevation data, and scientific raster datasets.
Runs integration tests against the Azure SQL Database container (Private Preview, local engine) in CI. Use when setting up GitHub Actions, Azure Pipelines, or GitLab CI to test against Azure SQL DB; when adding a database service container to a CI workflow; when tests need a real Azure SQL engine in the pipeline; or when you see "service container", "health-cmd", "ACR_USERNAME/ACR_PASSWORD", "MSSQL_SA_PASSWORD secret", or "integration test database". Also use when a workflow was about to pull the SQL Server image mcr.microsoft.com/mssql/server, in which case stop and use the Azure SQL Database engine image instead. Covers pulling from the private ACR with credentials, the service health check that runs sqlcmd inside the container so the runner needs no client tools, provisioning appdb before tests, and pointing the test connection string at the user database not master.
Proves that code built and tested against the local Azure SQL Database container runs unchanged against Azure SQL Database in the cloud, with only the connection string changing. Use when a user wants to develop locally then deploy to the cloud, asks "will this work in Azure", "same code local and cloud", "promote to Azure SQL", "swap the connection string", "dev/prod parity", "local to cloud", or is wiring SQL_CONNECTION_STRING for an app that must target both the container and a cloud server. Use this when an app uses local SA auth but needs Microsoft Entra auth in the cloud. Covers Node (mssql), .NET (Microsoft.Data.SqlClient), and Python (pyodbc). Reach for this skill before hand-editing app code to "make it work in Azure"; the rule is the code does not change, only the connection string does.
Turns exploration into decision-ready analysis: scores feature ideas on six viability criteria with KPI targets, converts open questions into A/B/C options with a recommended default, and produces executive-grade deliverables (KPI frameworks, forecasts, cohort/LTV-CAC models, A/B readouts, market sizing). Use during idea/PRD discovery to score or structure a decision, and whenever the task is quantitative decision support. Don't use for software implementation, UI work, or database migration.
Generate code to assign cell type labels to single-cell RNA-seq clusters using CellTypist, SingleR, marker-based annotation, or reference label transfer (scANVI/ingest). Triggers on requests to "annotate cell types", "label clusters", "run CellTypist", "SingleR annotation", "marker gene dotplot", "transfer labels from reference atlas", "cell identity", "automated annotation", "reference mapping", "scANVI label transfer", "canonical markers", "immune cell types", "hierarchical annotation", "majority voting CellTypist", "over-clustering annotation".
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.