Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Find web sources with query-relevant page excerpts and optional full-page content, and discover workflows, data APIs, and indexes. Use for web research or finding structured records, listings, transcripts, and datasets. Supports semantic tool discovery, domain matching, and progressive catalogue browsing.
Builds or changes a saved network enrichment workflow from connections or followers, with enriched people, their current companies, and links in both directions. Triggers on requests such as "enrich my network", "build a workflow for my followers", or "enrich these connections and their employers". Not for retrieving a list without enrichment, generic lead enrichment, one-off prospect qualification, or running an unchanged saved workflow, which belongs to gtm-workflow.
Analyze construction labor productivity using data analytics. Track worker performance, identify inefficiencies, predict resource needs, and optimize crew allocation for maximum efficiency.
Look up public product details on TikTok Shop. Enter a full product URL or a 19-digit product ID, optionally specifying major sites in the US, UK, Southeast Asia and Europe, and it returns grouped data such as product title, category, price, sales, SKU inventory, images, shop, review overview, logistics and promotions. Triggered when the user mentions TikTok Shop product details, TikTok product link parsing, product ID lookup, price and inventory verification, SKU variants, competitor page breakdown, TikTok product details, or TikTok Shop listing lookup. Even if the user does not explicitly say "product details", this skill should also trigger when they want to read the current public product page data from a TikTok Shop product URL or a 19-digit product ID.
Core MyBatis ORM skill. Covers choosing between XML and annotation SQL, ResultMap reuse (extends), association queries (association/collection join vs nested select / N+1 decisions), pagination plugin configuration, SQL injection protection for # and $, dynamic SQL (if/where/set/foreach/choose) best practices, and using columnPrefix to handle multiple JOINs on the same table. Use when the user writes MyBatis Mapper XML, handles association queries, configures pagination, or guards against SQL injection.
Run PostgreSQL queries for testing, debugging, and performance analysis. Use when you need to query the database directly, run EXPLAIN ANALYZE, compare query results, or test SQL optimizations. Always pass a target — `--prod` or `--dev` — because prod and dev are different databases and the default is prod. Always uses read-only connections unless explicitly directed otherwise.
Build and optimize SOQL queries including relationship queries, aggregate functions, polymorphic TYPEOF, and selective filters. Use when asked to write queries, debug slow queries, optimize existing SOQL, or enforce query security. Activate on mentions of "SOQL", "query", "SELECT", "WHERE", "aggregate", "relationship query", or "query optimization".
Diagnose failed Spark jobs, unhealthy Livy sessions, and performance bottlenecks in Microsoft Fabric via read-only CLI triage. Use ONLY for FAILED/unhealthy runs; running a notebook and reporting its success status is `spark-authoring-cli`. Use when the user wants to: (1) diagnose why a Spark job, notebook run, or Lakehouse job failed, (2) triage stuck or dead Livy sessions, (3) identify OOM, shuffle spill, or data skew, (4) retrieve driver/executor logs or Spark Advisor findings, (5) copy event logs and start a local Spark History Server, (6) diagnose Spark activities in a failed pipeline run. Triggers: "diagnose my failed notebook", "why did my spark job fail", "triage spark failure", "diagnose pipeline run failure", "why did my pipeline fail", "livy session stuck in starting", "spark executor OOM", "check spark advisor findings", "shuffle spill diagnosis", "why did my lakehouse job fail", "diagnose lakehouse table load", "data skew diagnosis", "open spark history server locally", "spark job triage".
Apply storytelling principles to create, review, and improve data visualisations and data-driven communications. Use when the message or story of a data communication (chart, dashboard, infographic, data-driven deck or report) needs structuring or review, or when structuring narrative arcs, hooks, or aha moments in data-driven communications.
Working with the Yandex Metrica API: analytics, reports, goals, logs. Use when the user needs web analytics data from Yandex Metrica — traffic stats, conversion reports, goal management, raw log exports, counter management, segments, filters, or grants. Triggers: метрика, metrica, аналитика, счётчик, визиты, конверсии, отчёт по трафику, источники трафика, Logs API, экспорт логов.
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
End-to-end analytics implementation for web and SaaS: GA4, Google Tag Manager, event taxonomy, conversion tracking, and UTM strategy. Use when building a tracking plan, debugging missing events, setting up GTM, or auditing existing analytics.
Access CoinMarketCap data via x402 pay-per-request protocol with USDC payments on Base. Use when users mention x402, want CMC data without API keys, ask about pay-per-request APIs, or need to integrate CMC with on-chain payments. Also use for any Coinbase x402 protocol questions. Trigger: "x402", "pay per request", "no API key", "USDC payment", "CMC without subscription", "/cmc-x402"
ElectricSQL real-time Postgres sync engine using Shapes for partial replication. Covers ShapeStream API, React hooks, where clause filtering, column selection, auth proxy patterns, and progressive write strategies from online-only to through-the-database. Use when setting up ElectricSQL, configuring Postgres sync, implementing shape-based data loading, building auth proxies for shapes, or choosing write patterns for local-first apps with Electric.
Authors and queries Fabric Eventhouse and KQL databases: tables, functions, policies, materialized views, ingestion, and read-only KQL for real-time and time-series analytics. All KQL database work belongs here, table creation and simple queries included. An Eventstream item is eventstream-cli; an Event Schema Set is eventschemaset-cli.
Reference for fandhe-db-engine / fandhe-db-wire-server, the Rust-built local-first, vector-focused query database fandhe-db (compatible with PostgreSQL wire protocol v3). Covers USING PLAN / USING OPERATION_ID syntax, DDL / JOIN / CTE / window functions, extended queries, COPY and transactions, TLS 1.3 / SCRAM-SHA-256, the NoSQL HTTP layer, precision and recall modes, HNSW / BM25 / RRF hybrid / rerank, redb persistence, tenant / RLS, SIMD / wgpu, and the wire_code error contract.
Diagnose post-triage, multi-component Splunk incidents from a supplied privacy-reviewed diagnostic packet. Use to align clocks and symptoms, preserve impact and contradictions, map dependencies, rank and test competing causal hypotheses, request the smallest safe read-only discriminator, validate bounded findings, and hand confirmed component failures to exact specialists. Do not use to collect raw diagnostics, troubleshoot or remediate one component, configure, restart, mutate, stress test, or claim an unverified cause or recovery.
Analyses a third-party system's API or file specification against Factorial's integrations framework and produces a detailed integration mapping document — the integration domain (payroll or finance), every capability in that domain with its verdict (fully, partially or not supported), the vendor endpoints to use for each, and the field-by-field mapping between Factorial's API and the vendor's. Use whenever someone shares a vendor API spec, OpenAPI/Swagger file, developer-portal link, integration guide or file layout and wants to know what we could build against it, how to map it, whether an integration is feasible, or asks for integration scoping, a fit-gap assessment or a field mapping. Use it even for informal asks ("can we integrate with this?", "how would new hires map to their API?") and partial specs.
Query a single Shopee public product detail. Input a product direct link containing -i.numeric shop ID.numeric item ID, supporting the Singapore, Indonesia, Malaysia, Philippines, Thailand, Taiwan, Vietnam and Brazil sites, and returns structured data currently available from the source, such as price, discount, sales, stock, SKU variants, images, brand, category, shop and rating. Triggered when the user mentions Shopee product details, Shopee product link parsing, price and stock checks, SKU variants, competitor page breakdown, Shopee product details, Shopee listing lookup. Even if the user does not explicitly say "product details", trigger this skill whenever they provide a Shopee product direct link and want to read the current public page data.
Expert in Machine Learning Operations bridging data science and DevOps. Use when building ML pipelines, model versioning, feature stores, or production ML serving. Triggers include "MLOps", "ML pipeline", "model deployment", "feature store", "model versioning", "ML monitoring", "Kubeflow", "MLflow".
Query Web3 blockchain data from Moralis API. Use when user asks about wallet data (balances, tokens, NFTs, transaction history, profitability, net worth), token data (prices, metadata, DEX pairs, analytics, security scores), NFT data (metadata, transfers, traits, rarity, floor prices), DeFi positions, entity/label data for exchanges and funds, or block and transaction data. Supports EVM chains (Ethereum, Polygon, BSC, Arbitrum, Base, Optimism, Avalanche, etc.) and Solana. NOT for real-time streaming - use moralis-streams-api instead.
This skill should be used when the user asks to "get data from a website", "scrape a website", "extract product details", "compare prices across stores", "pull data from Amazon or Walmart", "generate a web scraper", "build a data extraction pipeline", or mentions Nimble. Covers discovering existing extraction agents, running them interactively, generating scripts for large-scale extraction, and creating new custom agents.
Oracle PL/SQL procedural language. Covers stored procedures, functions, packages, triggers, cursors, collections, and exception handling. Use for Oracle database server-side programming. USE WHEN: user mentions "plsql", "Oracle procedures", "Oracle packages", "Oracle triggers", "BULK COLLECT", "FORALL", "DBMS_OUTPUT", "Oracle functions" DO NOT USE FOR: basic Oracle SQL - use `oracle` instead, PostgreSQL - use `plpgsql` instead, T-SQL - use `tsql` instead
Provides comprehensive guidance for PostgreSQL including SQL syntax, advanced features (JSONB/CTE/Full-text), functions, indexing, performance tuning, replication, and backup. Use when the user asks about PostgreSQL, needs to work with PostgreSQL features, write complex queries, or optimize PostgreSQL databases.
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.