Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
A platform decision framework for experimentation. When to use Statsig vs PostHog vs GrowthBook vs Optimizely vs Amplitude vs Eppo vs Kameleoon. How to migrate between them. How to coordinate when multi-platform is genuinely warranted. The decisions that compound for years and the ones you can defer. Triggers on which experimentation platform, choose Statsig vs PostHog, evaluate experimentation tools, switch experimentation platform, migrate from Optimizely, consolidate experimentation tools, multi-platform experimentation, experimentation platform decision, ab test platform selection, feature flag platform vs experiment platform, warehouse-native experiments, vendor lock-in experimentation. Also triggers when a team is asking about cost, governance, or migration cost across experimentation tools, or when an evaluation is starting.
Discover popular new products in 16 TikTok Shop regional markets using EchoTik new product ranking data. Trigger this skill when users mention TikTok new product rankings, TikTok best-selling products, TikTok Shop hits, short-video e-commerce product selection, TikTok new product discovery, cross-border TikTok product selection, TikTok new product rankings, TikTok bestsellers, short-video product selection, TikTok viral products, new product ranking, or TikTok product trends. Trigger it even if the user does not explicitly mention “EchoTik” or “new product rankings”, as long as their request involves finding hot new products or emerging product trends on TikTok Shop.
Analyze LLM experiment results. Handles single or comparative experiments, exploratory or Q&A modes. Use when user says "analyze experiment", "compare experiments", "analyze against baseline", or provides one or two experiment IDs for analysis.
Automate cloud browsers using the Scrapfly Cloud Browser API with Python Playwright. Covers connection options, sessions, anti-bot fingerprinting, and file downloads, including streaming large files (up to 500 MB) out of the session with downloads_stream=1 and the CDP IO domain
Search and analyze electron microscopy data — cryo-EM density maps (EMDB), fitted atomic models (PDB), raw micrograph datasets (EMPIAR), and cryo-electron tomography volumes (CryoET Data Portal). Use for finding 3D structural data on a protein/complex, comparing experimental EM resolution to AlphaFold confidence, and accessing raw EM data for re-processing
Metabolomics pathway analysis — metabolite identification (HMDB, KEGG, ChEBI), pathway mapping (Reactome, KEGG, MetaCyc), disease associations, and enzyme/gene linkage. Use for metabolite-to-pathway-to-disease connections, BridgeDb-based ID conversion, and integrating metabolomics with gene-level pathway analyses.
Plant genomics and biology research — PlantReactome pathways, Ensembl Plants gene structure, POWO species taxonomy, UniProt annotation, KEGG plant pathways. Handles polyploidy (wheat hexaploidy etc.) and homeologous gene copies. Use for crop-gene annotation, plant secondary metabolism queries, and plant-disease/stress-response biology
Builds Nango Function implementation patterns for createAction() and createSync() without choosing a local CLI or remote API workflow. Use only when the user asks to create or update a Nango action or sync and it is unclear whether to work in a checked-out project via CLI or through Nango remote APIs. Do not load when building-nango-functions-locally or building-nango-functions-remotely applies; those skills overlap with this content and add workflow-specific validation and deployment details.
Etsy category data. Search category names, IDs, and parentIds to find category IDs for filtering products or shops. Trigger for Etsy categories, Etsy category IDs, the Etsy category tree, Etsy category lookup, syncEtsyCategory, or category searches. Also trigger when users search by keyword for category IDs in the locally synced Etsy category library, even if the tool is not named.
Retrieve Amazon product details by ASIN, including price, title, Item Highlights, main image, listing date, material, weight, monthly sales by variant, and monthly sales data for the past 12 months. Trigger for Amazon product details, ASIN lookups, Item Highlights, title supplements, pricing, sales rank history, monthly sales trends, dimensions, FBA fees, product specifications, batch ASIN lookups, or Keepa product details. Also trigger when users need structured product data for one or more Amazon ASINs, even if “Keepa” is not mentioned.
Use Sorftime data to query Amazon product details and historical trends by ASIN across 14 marketplaces. Trigger for Sorftime product details, ASIN lookups, sales trends, price curves or history, BSR ranking history or trends, profit analysis, FBA fee analysis, gross margin, product trend analysis, daily or monthly sales, revenue trends, Deal promotion history, or related requests. Also trigger for Amazon product details or historical trend data by ASIN, even if “Sorftime” is not mentioned.
Create, ingest into, and query a Pinecone full-text-search (FTS) document index using the graduated document-schema API (Python SDK 10.0.0, API version 2026-07). Use when the user or agent asks to build a text search index on Pinecone, add dense or sparse vector fields, ingest documents, construct score_by clauses (text / query_string / dense_vector / sparse_vector), or compose with text-match filters ($match_phrase / $match_all / $match_any). Ships `scripts/ingest.py` for safe bulk ingestion (batch_upsert + error inspection + readiness polling); query construction is documented inline in this skill — write `documents.search(...)` calls directly, validated against `pc.indexes.describe(...)` output
Use this skill for reinforcement learning tasks, including high-performance RL training, custom environment development, vectorized parallel simulation, multi-agent systems, or integration with existing RL environments (Gymnasium, PettingZoo, Atari, Procgen, etc.). Use it to implement PPO training, create PufferEnv environments, optimize RL performance, or develop policies with CNNs/LSTMs.
Cross-species gene comparison and ortholog analysis. Integrates Ensembl Compara orthologs, NCBI Gene, UniProt, OLS, Monarch, and OpenTargets to identify orthologs, paralogs, sequence conservation, functional conservation across species, and lineage-specific gene gains/losses. Use for phylogenetic gene tracing, model-organism mapping, and evolutionary-genomics queries.
Social listening and brand reputation research using Bright Data's web scraping infrastructure. Collects what real people are saying about a brand, product, or person across Reddit, X/Twitter, Instagram, TikTok, YouTube, news, and review sites — then classifies sentiment, clusters themes, and delivers a cited digest with actionable recommendations. Use this skill when the user wants to know what people are saying about their brand, monitor social media mentions, gauge public sentiment, track online reputation, find complaints or advocacy, measure buzz around a launch, or do social listening / brand monitoring / sentiment analysis. Also use when the user mentions brand mentions, brand health, reputation tracking, or "what's the internet saying about us".
Post-mortem analysis when a client churns. Takes client history, engagement data, support tickets, usage logs, and exit feedback to produce a comprehensive churn autopsy with root cause classification, timeline of decline, and preventive measures.
Search API configuration, boosting strategies, and processor patterns for Drupal. Covers index field types, custom boost processors, number-field and engagement-metric boosting, Solr field-type drift on config export, and reindexing workflows. Use when configuring or debugging a Search API index, tuning relevance or result ranking, writing a custom search processor, or when search results are missing, stale, or ordered unexpectedly.
Batch-query TikTok product details, including sales and GMV across multiple periods (1/7/15/30/60/90 days and total), livestream sales and GMV, shoppable video and creator data, views, prices, ratings, review counts, commission rates, and listing/fully managed status. Supports batch lookups by product ID or TikTok Shop product URL. Trigger for requests about TikTok product details, batch lookups, sales analysis, GMV, livestream sales, creator data, prices and ratings, or EchoTik product details. Also trigger when users need detailed sales and marketing data for multiple TikTok products by ID or URL, even if “EchoTik” is not mentioned.
Filter Etsy shops by multiple dimensions (sales, favorites, reviews, shop opening date, country, main category, Raving/starred, etc.). Trigger when users mention Etsy shops, Etsy shop search, Etsy seller, Etsy shop rankings, Etsy weekly-sales shops, etsy stores, or Etsy shop lookup. Trigger this skill even if the tool is not named, whenever users look for Etsy shops, filter shop data, or analyze shop performance.
Use FastMoss data to query best-selling product rankings in the global TikTok e-commerce market, with analysis by day, week, month, and category. Trigger for TikTok bestseller rankings, sales rankings, GMV rankings, category bestsellers, weekly product reports, or FastMoss. Also trigger when users want TikTok best-seller rankings or sales rankings by time period, even if “FastMoss” is not mentioned.
Query historical time-series data for Amazon products, including price trends, BSR (Best Sellers Rank) trends, rating changes, seller counts, and monthly sales. Supports any ASIN across multiple Amazon marketplaces. Trigger for price history or tracking, BSR history or trends, historical pricing, price fluctuations, Keepa data, ranking history, price-drop alerts, historical Lightning Deal prices, Buy Box price trends, coupon prices, FBA/FBM price comparisons, changes in seller counts, rating trends, sales history, or related requests. Also trigger for Amazon product-level historical trends in price, rank, or sales, even if “Keepa” or “time-series data” is not mentioned.
Filter Temu products by multiple criteria, including keyword/product ID/store ID, frontend and backend categories, price, rating, reviews, total/weekly/daily sales, listing date, full or semi-managed status, semi-managed region, and tags. Trigger when the user mentions Temu products, Temu product selection, Pinduoduo cross-border, Temu bestsellers, Temu semi-managed, fully managed products, Temu product query, or temu items. Trigger even if the user does not mention the tool name, as long as they want to search Temu products, check sales/ratings/prices, or filter products.
Map environmental and industrial chemicals to adverse outcome pathways (AOPs) — molecular initiating event to organ-level toxicity. Uses AOPWiki, GHS classification, IARC carcinogen status, and LD50 data. Use for environmental/industrial chemical risk assessment, regulatory-grade hazard characterization, and AOP stressor mapping. Distinct from drug-safety analysis (use tooluniverse-pharmacovigilance for drugs).
Lipid analysis and lipid-disease associations using LIPID MAPS classification, HMDB metabolite data, KEGG/Reactome lipid pathways (sphingolipid, eicosanoid, steroid, fatty acid), and PubChem chemical info. Use for lipid identification, lipid metabolism pathway mapping, and lipid-associated disease analysis (cardiovascular, diabetes, NAFLD).
When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," or "tracking plan." For A/B test measurement, see ab-test-setup.
Migrates LLM observability from Langfuse into Arize AX — historical trace import via OTLP (LF output→output.value, sessionId→session.id), datasets, and prompts (latest or versions + labels). Use when migrating from Langfuse to Arize or importing Langfuse observations into AX.
Migrates LLM observability from LangSmith into Arize AX — historical trace import via OTLP (LS outputs→output.value, session/thread→session.id), datasets, and Prompt Hub prompts (latest or versions). Use when migrating from LangSmith to Arize, importing LangSmith runs into AX, or replacing LangSmith with Arize.
Expert knowledge for Azure AI Search development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring data sources, skillsets, vector/semantic search, indexers, or multi-region search architectures, and other Azure AI Search related development tasks. Not for Azure Cosmos DB (use azure-cosmos-db), Azure Data Explorer (use azure-data-explorer), Azure Synapse Analytics (use azure-synapse-analytics).
Graph database schema design and data modeling expert. Use when designing, reviewing, or refactoring graph database schemas (Neo4j, Memgraph, Neptune, etc.). Triggers on graph modeling, node/relationship design, Cypher schema, property graph design, knowledge graph modeling, or when translating a domain into a graph structure. Focuses primarily on data modeling correctness — understanding the user's goal and translating it into the right graph structure — with performance as a secondary concern.
Deeply analyze Amazon niche markets by keyword, covering monopoly level, brand concentration, new product success rate, and market opportunity scores. Trigger this skill when the user mentions niche market analysis, keyword market research, monopoly assessment, brand concentration analysis, new product success rate, market demand score, competitive landscape, Amazon submarket exploration, niche market analysis, keyword market, monopoly level, brand concentration, new product success rate, market opportunity score, competitive landscape, or Jiimore data. Trigger it even if the user does not explicitly mention "niche market," as long as their request involves evaluating Amazon market competition, brand density, or opportunity potential for a keyword.
Seerfar Ozon category product search: retrieve the product list for an Ozon category by category ID, returning category-level aggregates (total sales volume, total sales revenue, average price, average rating, seasonality) and each product's sales volume, price, rating, review count, brand, seller, and delivery method. Use for category product selection, bestseller discovery, category capacity and price-band analysis, and seasonality assessment. Trigger this skill when the user mentions Ozon category products, Ozon category analysis, Ozon category product selection, Ozon category bestsellers, Ozon category total sales, Ozon category average price, Ozon category search, Ozon category products, category best-sellers, or category analysis. Trigger it even if the user does not explicitly mention "Seerfar" as long as they intend to view products and category-level summary data for an Ozon category.
Seerfar Ozon market keyword search: Filter Ozon (and Wildberries) market keywords by multiple metrics, including search popularity, growth, product count, seller count, competitor count, price, sales, and conversion concentration. Returns a market profile for each keyword, including monthly search popularity, growth, market potential, competitor/seller counts, average price, add-to-cart conversion, and top products. Use for Ozon keyword selection, blue-ocean keyword discovery, and market opportunity analysis. Trigger when the user mentions Ozon trending keywords, Ozon keyword market analysis, Ozon keyword selection, Ozon blue-ocean keywords, Ozon search popularity, Wildberries keywords, Seerfar Ozon, Ozon market keyword search, Ozon keyword research, or blue ocean keywords Ozon. Trigger this skill even if the user does not explicitly mention “Seerfar,” as long as they intend to filter Ozon market keywords by metrics and view market profiles.
Multidimensional Amazon product search and filtering based on Sorftime data, covering 14 marketplaces and historical monthly snapshots. Trigger when the user mentions Sorftime product search, Amazon product filtering, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshots, product search, monthly sales volume or revenue, finding products with ABA keywords, price-range filtering, new product discovery, multi-criteria filtering, product search, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, or historical snapshot. Trigger even if the user does not explicitly mention “Sorftime,” as long as they want to search, filter, compare, or explore Amazon products by category, brand, or seller.
Construct ObjectQL queries — filters, sorting, pagination, aggregation, relation expansion, and full-text search. Use when the user is writing a query DSL expression or picking a pagination strategy. Do not use for defining objects / fields / relationships (see objectstack-data), for designing the API endpoint that exposes a query (see objectstack-api), or for a list view's filter rules / dashboard datasets (see objectstack-ui).
KEGG-based disease-drug-variant network research. Connects diseases to causal genes, drugs to molecular targets, and variants to pathways using KEGG's editorially curated databases (KEGG Disease, Drug, Network, Variant, Pathway). Use for drug repurposing via shared pathways, mechanistic disease-gene-drug networks, and pathway-based target discovery. Distinguishes direct (binding) vs indirect (pathway co-membership) drug-target relationships.
Population genetics using the 1000 Genomes Project (IGSR) — superpopulation/population search, sample metadata, variant frequencies across AFR/AMR/EAS/EUR/SAS, ancestry-specific analyses. Use for ancestry comparison, population-aware allele frequency lookups, and 1000-Genomes-cohort-specific analyses (distinct from gnomAD, which has a different sample composition).
Migrates LLM observability from Braintrust into Arize AX — historical trace import via OTLP (BT output→output.value, span_parents, one AX trace per turn + session.id), datasets, and prompts (latest or versions). Use when migrating from Braintrust to Arize or importing Braintrust logs into AX.
Seerfar Ozon product report search: filters Ozon products by multiple metrics, including sales volume, revenue, sales/revenue growth rate, add-to-cart conversion, order conversion, price, rating, review count, QA count, variant count, views, gross margin, return/cancellation rate, advertising cost share, weight/volume, listing time, brand, seller, fulfillment method, and tags. Returns a complete product-level report for each item, including SKU, title, price (rubles), sales, revenue, lost revenue, conversion rate, rating, reviews, brand, seller, fulfillment method, and listing days/months. Use for Ozon product selection, competitor analysis, best-seller discovery, and filtering by price or conversion ranges. Triggers when the user mentions Ozon product reports, Ozon product selection, Ozon product filtering or analysis, Ozon best sellers, Ozon competitor analysis, Ozon product report, Ozon product screener, filtering Ozon products by sales, Ozon best-seller mining, or Seerfar Ozon product reports. Trigger even if “Seerfar” is not explicitly mentioned when the intent is to filter Ozon products by multiple metrics and view product-level reports.
Seerfar Ozon store product search: Retrieve a store’s product list by Ozon store (seller) ID. Returns each product’s sales over the past 30 days, price, rating, weight, shipping method (FBO/FBS), seller type (local/cross-border), return and cancellation rate, and the store’s total sales over the past 30 days. Use for competitor store product analysis, finding bestsellers, and breaking down a seller’s product mix. Trigger when the user mentions Ozon store products, Ozon seller product lists, competitor store analysis, Ozon store bestsellers, Ozon seller analysis, Seerfar Ozon store search, Ozon shop search, Ozon seller products, competitor shop analysis, or Ozon store products. Trigger even if the user does not explicitly mention “Seerfar,” as long as they intend to view product and sales data for an Ozon store or seller.
Shopee store Video (same series as linkfox-shopee-store-auth), forwarding all 15 endpoints in the Shopee Open API Video module through /shopee/developerProxy, including get_cover_list, post_video, get_video_list, get_video_detail, edit_video_info, get_overview_performance, and get_video_detail_performance. Trigger when the user mentions Shopee videos, store videos, uploading videos, post_video, video covers, video performance, video performance, or get_video_list. Trigger even without an explicit mention of “video” if the request involves publishing videos or analyzing their performance for an authorized Shopee store.
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.