Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Queries patent citation data from PatSnap, including citation counts and details of citing patents. Triggered when users mention patent citations, citation analysis, patent influence, citation frequency, citations of a patent family, forward citations, or ask which patents cite a given patent; also for patent citations, citation count, patent influence, citation analysis, or PatSnap. Use even if “PatSnap” is not explicitly mentioned, as long as the user wants to find how often a patent is cited or which patents cite it.
Queries forward citation details for patents from the PatSnap patent database. Use when users ask about patent citations, cited patents, cited literature, patent references, forward citations, prior-art citations, or which patents and non-patent literature a specific patent cited during its application; also trigger for patent cited references, forward citations, patent references, citation analysis, or PatSnap. Apply to any request for references cited by a patent when the user provides a patent ID or publication number, even if they do not explicitly say “forward citations.”
Use the `nb` CLI for all Jupyter notebook (`.ipynb`) operations, including reading, inspecting, creating, editing cells, deleting cells, clearing outputs, searching, executing, and working with connected JupyterLab sessions or remote kernel gateways. Required when an agent needs deterministic notebook manipulation without directly reading or writing raw notebook JSON.
Production-grade web scraping with automatic anti-bot bypass, structured JSON parsing for 40+ targets, and geo-targeting. Use when the user needs to scrape web pages, extract product data, get search results, or collect structured data from supported e-commerce and search platforms without worrying about getting blocked and when geo targeting is required.
HLA gene-family analysis and MHC-peptide binding for transplant compatibility, vaccine epitope coverage, and cancer immunotherapy. Uses IMGT (HLA polymorphism), IEDB (epitope-MHC binding), UniProt (annotation), DGIdb (druggability). Use for HLA typing/imputation review, vaccine HLA coverage, and immunotherapy prediction biomarkers (HLA-LOH, neoantigen presentation).
Cross-species genetic analysis using model organism databases (MGI mouse, IMPC systematic knockout phenotyping, ZFIN zebrafish, FlyBase fruit fly, WormBase worm, SGD budding yeast plus protein-domain/PTM/literature detail, PomBase fission yeast, RGD rat, GeneNetwork systems-genetics/eQTL panels, HumanMine/MouseMine cross-species data-warehouse search, GBIF taxonomy) plus VEuPathDB for eukaryotic pathogens (Plasmodium, Toxoplasma, fungi, vectors). Maps human genes to orthologs, retrieves phenotype/expression/functional data, assesses gene function conservation, and identifies the best animal model for studying a human gene or disease.
Production-grade web scraping with automatic anti-bot bypass, structured JSON parsing for 40+ targets, and geo-targeting. Use when the user needs to scrape web pages, extract product data, get search results, or collect structured data from supported e-commerce and search platforms without worrying about getting blocked and when geo targeting is required.
Alibaba Cloud Elasticsearch Instance & Config Management Skill. Use for managing the lifecycle of an Elasticsearch instance (create, query, list, restart, upgrade/downgrade, node info) and for managing instance-side config such as snapshot backup and analyzer dictionaries. Triggers: "elasticsearch", "ES instance", "elasticsearch instance", "create ES", "query ES instance", "restart ES", "ES node", "cluster node", "upgrade ES", "downgrade ES", "scale ES", "resize ES", "ES snapshot", "ES backup", "snapshot setting", "create snapshot", "ES dict", "IK dict", "hot dict", "synonyms dict", "aliws dict", "analyzer dictionary"
Set up an LLM-judge evaluation that extracts canonical use cases for a PostHog feature at scale and streams the results to a Slack channel as a live feed. Use when someone wants to understand how users are actually using a specific AI/LLM-powered feature in production — what they're investigating, what questions they're trying to answer, and what patterns surface — without manually reading hundreds of traces. Assumes the feature emits `$ai_generation` and `$ai_evaluation` events with `$session_id` linkage to the trigger user's recording (the standard setup post the session-summary linkage PRs).
Amazon niche market review analysis and consumer sentiment insights. Trigger this skill when the user mentions niche market review analysis, consumer sentiment, customer pain points, customer feedback insights, review topic analysis, positive/negative review breakdowns, niche market opinion mining, product review sentiment analysis, niche market reviews, consumer sentiment, customer pain points, review topic analysis, positive/negative reviews, opinion mining, or Jiimore data. Trigger even if the user does not explicitly mention “niche market reviews,” as long as they want to analyze consumer reviews in an Amazon niche market or understand customer sentiment at the niche-market level.
Seerfar Ozon product detail lookup: retrieves complete details for a single product by Ozon product SKU, including title, price (rubles), rating, review count, QA count, total and average daily sales within the statistical window, revenue, stock, category rank, daily sales trend, brand, seller, fulfillment method (FBO/FBS/OZON), weight, and listing time/days/months. Use for in-depth single-product analysis, competitor product breakdowns, Ozon product selection evaluation, Listing diagnostics, and tracking sales trends and category rankings. Triggers when the user mentions Ozon product details, Ozon single-product analysis, Ozon SKU lookup, competitor product data, Ozon sales trends, Ozon category ranking, Ozon inventory, Ozon listing time, Seerfar Ozon product search, Ozon product detail, Ozon SKU lookup, single product analysis, competitor product teardown, Ozon sales trend, or category rank. Trigger this skill even if the user does not explicitly mention “Seerfar” when they intend to view detailed data for an Ozon product.
Filter Shopify independent-store products by multiple criteria, including keyword/URL, price, weekly sales, listing date, Facebook ads, competition, product sourcing availability, and shipping country. Trigger when the user mentions Shopify products, Shopify product selection, independent-store product selection, Shopify bestsellers, Shopify dropshipping, stocking an independent store, Facebook ad products, Shopify product query, or shopify items. Trigger even if the user does not mention the tool name, as long as they want to search products on a Shopify store, check weekly sales/revenue or competition, or filter products.
Filter Temu stores by multiple criteria, including store name/ID, country site, backend category, full or semi-managed status, total/weekly/monthly sales and revenue, ratings, reviews, followers, product count, and opening date. Trigger when the user mentions Temu stores, Temu store analysis, Temu seller, Temu store rankings, Temu semi-managed stores, Temu sales revenue, temu stores, or Temu store query. Trigger even if the user does not mention the tool name, as long as they want to find stores on Temu, filter store data, or analyze store performance.
Loads all 22 DataHub connector golden standards into context. Use before starting connector development or review work to ensure the full set of standards is available for reference. Triggers on: "load standards", "show standards", "what are the connector standards", "load golden standards", "review standards", or any request to load DataHub connector development guidelines.
Design, implement, and review Supabase solutions — Postgres, Auth, Row Level Security, Storage, Realtime, Edge Functions, and local environments. Use when `supabase/config.toml`, Supabase migrations, or `@supabase/*` clients are involved; do not use as a substitute for in-depth Postgres analysis of schemas, indexes, or plans — combine with `specsfy-specialist-postgres` for that.
Tongdaxin quantitative data retrieval skill. Use when the user mentions tdxquant, Tongdaxin, TdxQuant, or tqcenter and needs A-share data (market snapshots, K-lines, financials, sectors, convertible bonds, new stocks, trading data, etc.), trading calendar lookups, Tongdaxin formula execution, market data subscriptions, or order placement
Translate free-text tumor descriptions to OncoTree codes and resolve cancer subtypes/tissue hierarchy. Cross-references UMLS/NCI vocabularies. Use for standardizing cancer-type nomenclature in EHR free-text, building cohorts in OncoKB or GDC, mapping tumor-board notes to ontology codes, and ensuring consistent terminology across cancer-genomics pipelines.
End-to-end variant-to-mechanism analysis — trace a variant (rsID/coordinates) through regulatory context, target gene(s), molecular pathway(s), and phenotypic consequences. Integrates 7+ databases across 3 evidence layers (regulatory, molecular, disease) for a mechanistic model. Use for GWAS-hit-to-mechanism, eQTL-causal-gene tracing, and full causal-chain reports.
Profile and explore datasets to understand their shape, quality, and patterns before analysis. Use when encountering a new dataset, assessing data quality, discovering column distributions, identifying nulls and outliers, or deciding which dimensions to analyze.
Use when the user wants to discover, evaluate, or research creators/KOLs/influencers on YouTube, TikTok, or Instagram. Covers creator discovery (natural-language search, lookalikes), creator profiling, audience analysis (age/gender/region/fake-follower rate), bulk email extraction, video analysis, and account setup. Use when the user mentions finding influencers, checking a creator’s audience, getting creator emails, analyzing a video, or setting up EasyKOL access
Seerfar Ozon keyword reverse lookup: Reverse-search Ozon (and Wildberries) search keywords for a list of up to 20 product SKUs, showing which search terms these products appear under (organic/advertising). Filter by multiple dimensions, including search popularity, growth, product count, seller count, competitor count, organic rank, ad rank, impressions, conversions, and add-to-cart conversion. Each keyword includes a market profile with monthly search popularity, growth, market potential, competitor/seller counts, average price, add-to-cart conversion, top products, and organic/ad channels, rankings, impressions, and conversions (dimension). Use for Ozon keyword reverse lookup, Listing keyword optimization, competitor traffic keyword discovery, and ad keyword analysis. Trigger this skill when the user mentions Ozon keyword reverse lookup, Ozon reverse keyword lookup, Ozon SKU reverse lookup, Ozon product traffic keywords, Ozon competitor-converting keywords, Ozon organic/ad keyword lookup, Seerfar Ozon, Ozon keyword back search, Ozon reverse keyword lookup, or Ozon SKU keyword reverse. Even if the user does not explicitly mention “Seerfar,” trigger this skill whenever they intend to reverse-search Ozon search keywords by product SKU and view market profiles.
Solve quantitative problems in biophysics — pharmacokinetics (PK volume of distribution, clearance, half-life), epidemiology (R0, attack rate), toxicology (LD50, NOAEL), population genetics (Hardy-Weinberg, Fst), enzyme kinetics (Michaelis-Menten), thermodynamics. Use for first-principles quantitative biology calculations, dose calculations, exposure assessment, and biophysical-property estimation.
Non-coding/regulatory variant interpretation — GWAS association lookup, eQTL evidence (GTEx), chromatin state (ENCODE), regulatory variant scoring (RegulomeDB, CADD), TF-binding disruption, and sequence-based deep-learning prediction (AlphaGenome/AlphaGenome Atlas) for when annotation databases are silent. Use for non-coding GWAS hit interpretation, eQTL-based gene assignment, and regulatory mechanism reasoning. Distinct from coding-variant tools.
Use when generating, testing, submitting, reviewing, or publishing governed project semantic candidates from AE project asset packages. This skill owns progressive asset-scope consent, recommendation quality gates, evidence authority, topic-domain grouping, candidate JSON generation, CLI closed-loop validation, and frontend review acceptance. Do not use it for ordinary analysis questions that only consume already published semantics.
Comprehensive guide for building full-stack applications with Convex and TanStack Start. This skill should be used when working on projects that use Convex as the backend database with TanStack Start (React meta-framework). Covers schema design, queries, mutations, actions, authentication with Better Auth, routing, data fetching patterns, SSR, file storage, scheduling, AI agents, and frontend patterns. Use this when implementing features, debugging issues, or needing guidance on Convex + TanStack Start best practices.
Use this skill when the user wants to build tools or scripts, or complete a task that could benefit from Hugging Face API data. Especially useful for chaining or combining API calls, or when a task will be repeated or automated. This skill creates a reusable script to fetch, enrich, or process data.
Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for automation
Investigates a session recording by gathering metadata, person profile, same-session events, and linked error tracking issues in one pass. Use when a user provides a recording or session ID and wants to understand what happened — who the user was, what they did, what errors occurred, and whether there are related error tracking issues. Replaces the manual chain of session-recording-get, persons-retrieve, execute-sql, and query-error-tracking-issues-list.
Query and analyze Jiimore data on Amazon niche market insights, including market metrics, buyer reviews, competitive landscape, price trends, and growth trends. Trigger this skill when the user mentions niche market analysis, market insights, niche market data, market competition analysis, brand concentration, new product launch success rate, out-of-stock rate, price trends, review insights, market demand score, niche market insights, market metrics, competition analysis, price trends, growth trends, Jiimore data, market intelligence, or out-of-stock rate. Even if the user does not explicitly mention “Jiimore” or “niche market,” trigger this skill whenever their request involves querying market-level intelligence for a specific Amazon niche using a market ID.
Find competing Amazon products in the same niche by ASIN, with potential competitors filterable by click-through conversion rate, overall conversion rate, clicks, sales, reviews, ratings, price, gross margin, and other dimensions. Trigger this skill when the user mentions same-niche competitors, ASIN competitor discovery, Niche competitor analysis, comparable products, ASIN benchmarking, niche competitor lists, high-conversion competitor screening, Jiimore product discovery, niche competitor by ASIN, ASIN competitor analysis, same niche products, similar products discovery, conversion rate comparison, potential competitor screening, or Jiimore ASIN mining. Even if the user does not explicitly mention “niche market” or “Niche,” trigger this skill whenever their request involves finding a list of competitors in the same niche or screening potential competitors based on an ASIN.
Filter independent Shopify stores by multiple dimensions, including store name/domain, country, age, product count, ad count, monthly visits, monthly orders, and social media followers. Trigger when the user mentions Shopify stores, Shopify store analysis, independent stores, Shopify seller, competing independent stores, Shopify monthly visits, independent store ad libraries, shopify stores, or Shopify store query. Even if the user does not mention the tool, trigger this skill when they want to find Shopify stores, filter store data, or analyze store performance.
Break down traffic sources for all competing ASINs under a given keyword, including organic search, SP ads, SB brand ads, SBV video ads, SP recommendations, and recommendation placements such as AC/ER/TR. Filter by ASIN, date range, new traffic keywords, and other criteria. Trigger when the user mentions keyword traffic sources, which competitors are competing for traffic under a keyword, organic versus paid traffic share, SP ad impressions, brand ad share, SP recommendations, ad/non-ad recommendation placement breakdown, search display analysis, Amazon's Choice or editorial recommendation impressions, keyword competition landscape, ASIN traffic composition, keyword traffic, traffic structure analysis, search share, ad share, traffic source distribution, SIF, traffic analysis, SP recommendation, or recommend position breakdown. Even if the user does not explicitly mention “SIF,” trigger this skill whenever their request involves analyzing traffic source distribution for competing ASINs under a keyword.
Systematic ACMG/AMP germline variant classification with all 28 criteria (PVS1, PS1-4, PM1-6, PP1-5, BA1, BS1-4, BP1-7) for clinical significance. Produces 5-tier verdict (Pathogenic / Likely Pathogenic / VUS / Likely Benign / Benign) with cited evidence per criterion. Use for variant interpretation, VUS resolution, and pathogenicity assessment. Combines ClinVar, gnomAD, computational predictors, and gene-mechanism context.
Analyze actual Azure spend, bill changes, and AKS or AI costs. WHEN: "Azure cost breakdown", "most expensive resources", "why did my bill increase", "cost spike", "unexpected charge", "Cosmos DB charges", "Foundry model costs", "AKS cluster cost", "namespace cost", "enable AKS cost analysis", "idle AKS capacity". DO NOT USE FOR: forecasts, pricing estimates, rightsizing, commitments, or budgets.
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.
Answers natural-language business questions over existing Power BI reports and semantic models through the FabricIQ MCP endpoint, discovering artifacts, resolving entities, generating the DAX itself, and returning a plain-language answer. Use when the user asks a data question, including one that says to query the model directly. For DAX the user supplies, or measures to save, use semantic-model-authoring.
Use when accelerating existing genomics workflows with NVIDIA Parabricks, improving runtime or price/performance, converting pipeline steps to GPUs, or comparing CPU and GPU workflow outputs. Adds optional GPU steps in-place with runtime toggles (default off). Do NOT use for individual pbrun command routing — use parabricks.
Build HTML data explorers for CSV, JSON, log, and event data — filterable tables, faceted search, inline charts, timeline scrubbing, A/B test result dashboards. Use whenever the user has a dataset to explore, browse, filter, chart, facet, or analyze — especially for ad-hoc analysis where opening a heavy BI tool is overkill. Reach for this when the user pastes data, mentions a CSV/JSON/log file, or asks to "look at" or "analyze" a dataset. Always runs a secret-redaction pass before embedding data — credential-shaped values (API keys, tokens, cookies, passwords) are replaced with placeholders unless the user explicitly opts in to embedding them.
Build structured semantic layer documentation for metrics, dimensions, and entities. Activate when you need to define a business metric, document a data model, or create YAML definitions compatible with dbt Semantic Layer or similar frameworks.
Aging biology, cellular senescence, and longevity research. Covers senescence markers (p16/CDKN2A, SASP, SA-beta-gal), aging hallmarks, senolytic drug discovery (dasatinib+quercetin, fisetin, navitoclax), epigenetic clocks, telomere biology, and longevity GWAS. Use for senescence-pathway analysis, age-related disease genetics, senolytic-target discovery, and centenarian-genetics queries. Distinguishes correlative from causal evidence (knockout, intervention).
Rare disease genomics — disease identification (Orphanet), causative gene discovery, gene-disease validity (GenCC), variant interpretation (ClinVar), and translational research (ClinicalTrials.gov, drug repurposing for orphans). Use for rare-disease-gene curation, novel-gene-discovery analysis, and rare-disease drug-development support
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.