Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Analyze production Agentforce agent behavior using session traces and Data Cloud. TRIGGER when: user queries STDM session data or Data Cloud trace records; investigates production agent failures, regressions, or performance issues; asks about session traces, conversation logs, or agent metrics; wants to reproduce a reported production issue in preview; runs findSessions or trace analysis queries. DO NOT TRIGGER when: user creates, modifies, or debugs .agent files during development (use developing-agentforce); writes or runs test specs (use testing-agentforce); uses sf agent preview for local development iteration; deploys or publishes agents.
Fetch social media, commerce, and research data through the SocialCrawl API: profiles, followers, posts, comments, reviews, search results, transcripts, ads, product catalogs, app-store listings, places, jobs, finance, news, trends, prediction markets (Polymarket), plus cross-platform Prism composites, scheduled Monitors, and audience Cohorts. Covers TikTok, Instagram, YouTube, Twitter/X, Facebook, LinkedIn, Reddit, Threads, Amazon, Walmart, Google, Trustpilot, Yelp, GitHub, Naver and many more behind one API key. Use when the user mentions SocialCrawl, or wants to collect social media data, creators or influencers, brand mentions, comments, reviews, or competitor data; scrape or crawl a web page via SocialCrawl; generate code that calls the API; check endpoints, pricing, or their credit balance; or run one search across many platforms.
Use whenever the user mentions Zenodo, depositing or publishing research artifacts (datasets, software, papers, posters) to Zenodo, minting a DOI for a dataset/code release, uploading files to a Zenodo record, creating a new version of a Zenodo deposit, or searching Zenodo records. Covers the full Zenodo REST API workflow — create deposition, upload files via the bucket API, set metadata, publish, version, and search — for both production (zenodo.org) and sandbox (sandbox.zenodo.org).
Audit the health of a PostHog project's data warehouse — find every broken or degraded pipeline item across sources, sync schemas, materialized views, batch exports, and transformations. Use when the user asks "what's broken in my warehouse?", "give me a health check", "audit my data pipeline", "why are some dashboards stale?", or wants a one-shot triage summary before deciding where to spend time. Produces a prioritized report of issues grouped by severity and type, with recommended next steps.
Migrates databases between providers (Postgres, MySQL, Supabase, PlanetScale, MongoDB). Reads source schema, generates migration scripts, handles data type mapping, foreign keys, indexes, triggers, stored procedures. Validates migration with row counts and checksums. Generates migration-plan.md with step-by-step execution guide, rollback procedures, estimated downtime.
Writes and curates business metadata in an AWS data catalog: the Amazon SageMaker Catalog (Amazon DataZone), or the AWS Glue Data Catalog. Detects which catalog platform an account uses before writing. Triggers on: add a description to a table, document a dataset, write a README, set an owner, add column comments, tag with a glossary term, create a business glossary, create a metadata form, publish an asset, create a data product, run the data source crawl, delete a catalog asset, attach a conventions document to a table as a catalog skill asset, which assets in my project are missing descriptions or owners and what to fix first, which catalog does this account use and what can I do with it. Not for: inventorying or listing tables (use exploring-data-catalog), locating one table (use finding-data-lake-assets), counting gaps domain-wide with SQL over the exported metadata snapshot (use querying-aws-sagemaker-catalog), or granting or revoking access (use managing-data-asset-access)
Morningstar Screener via public JSON API: bulk download 53 universes (102K+ listings, 39 countries, NYSE/Nasdaq/BCBA/etc) with 33 fields (price, market cap, ratios, returns 1d/1w/1m/3m/6m/12m/36m/60m/120m, debt, dividend yield, sector, industry). No API key, no auth.
Analyze 8-K filings to extract material events and corporate changes using Octagon MCP. Use when tracking real-time corporate disclosures, M&A announcements, leadership changes, earnings releases, and other material events requiring immediate investor attention.
SEC EDGAR filing analysis using EdgarTools. Use when user asks about SEC filings, company financials, 10-K/10-Q analysis, insider trading, revenue trends, or financial comparisons. Triggers include "SEC filing", "10-K", "10-Q", "8-K", "EDGAR", "company financials", "revenue", "earnings", "insider trading", "financial statements". Do NOT use for real-time stock prices or market data (use market-data skill instead).
Retrieve full historical end-of-day price data for market indices using Octagon MCP. Use when analyzing index performance over time, tracking market trends, calculating returns, and understanding market context for individual stock analysis.
Sets up vector databases for semantic search, including Pinecone, Chroma, pgvector, and Qdrant, with embedding generation and similarity search. Use when users request “vector database,” “semantic search,” “embeddings storage,” “Pinecone setup,” or “similarity search.”
Analyze VictoriaMetrics query trace JSON to diagnose slow queries and produce a structured performance report with time breakdown, bottleneck analysis, and optimization recommendations. ALWAYS use this skill when: (1) the user mentions a VictoriaMetrics or VM trace, query trace, or trace JSON, (2) the user provides or references a JSON file containing duration_msec/message/children fields, (3) the user asks why a VictoriaMetrics/VM query is slow and has trace output, (4) the user asks about vmstorage node distribution, cache misses, or rollup performance in the context of a trace, (5) the user mentions vmselect trace, trace=1, or query performance debugging with VictoriaMetrics. This skill provides a structured report template that ensures consistent, thorough analysis — do not attempt to analyze VM traces without it.
Analyze marketing performance with key metrics, trend analysis, and optimization recommendations. Use when building performance reports, reviewing campaign results, analyzing channel metrics (email, social, paid, SEO), or identifying what's working and what needs improvement.
Quicknode blockchain infrastructure for 80+ chains: Core RPC API, Streams, Webhooks, Blazar WSS, Solana gRPC, HyperCore gRPC, SQL Explorer, Metaplex DAS API, Blockbook, Ordinals & Runes API, Swap API, x402, MPP, Agent Subscriptions, CLI, and MCP. Use for any Quicknode product, blockchain data access, or wallet-paid agent access.
Build Retrieval-Augmented Generation (RAG) applications that combine LLM capabilities with external knowledge sources. Covers vector databases, embeddings, retrieval strategies, and response generation. Use when building document Q&A systems, knowledge base applications, enterprise search, or combining LLMs with custom data.
Expert-level research methodology, academic writing, statistical analysis, and scientific investigation. Use when the user mentions methodology, statistics, academic writing, or experimental design, or when the task involves Research Design, Statistical Analysis, or Data Analysis.
Audits database schemas for naming conventions, type consistency, nullability patterns, and missing constraints. Provides a violations report with recommended fixes. Use for “schema validation,” “database linting,” “schema standards,” or “consistency checks”
Analyze debt covenants and credit agreement terms from SEC filings using Octagon MCP. Use when researching financial covenants, leverage ratios, interest coverage requirements, credit facilities, debt maturity schedules, and covenant compliance from 10-K, 10-Q, and 8-K filings.
Analyze footnotes and accounting policies from SEC filings using Octagon MCP. Use when researching revenue recognition policies, critical estimates, lease obligations, pension assumptions, stock compensation, contingencies, and new accounting pronouncements.
Analyze Management Discussion and Analysis (MD&A) sections from SEC filings using Octagon MCP. Use when extracting strategic initiatives, financial performance commentary, macroeconomic challenges, and forward-looking statements from 10-K and 10-Q filings.
End-to-end observational epidemiology analysis — from research question (PECO Population/Exposure/Comparator/Outcome) to publication-ready statistical report. Covers cohort/case-control/cross-sectional design, regression with confounders, propensity scoring, sensitivity analysis. Writes Python code for every step. Use for epidemiology study analysis, NHANES/UK-Biobank-style analyses
Generate a Wren MDL project by exploring a database with available tools (SQLAlchemy, database drivers, MCP connectors, or raw SQL). Guides agents through schema discovery, type normalization, and MDL YAML generation using the wren CLI. Use when: user wants to create or set up a new MDL, onboard a new data source, or scaffold a project from an existing database.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Grants, requests, audits and removes access to data assets in an AWS data catalog (the Amazon SageMaker Catalog supported by Amazon DataZone) through catalog subscriptions over published listings. Covers requesting a subscription, approving or rejecting requests with a recorded decision, sharing a listing with a project, revoking one or many subscriptions, and confirming grant settlement. Triggers on: give another team access to a table, request access to a dataset, approve or reject an access request, share a listing with a project, who has access to this table, revoke access, bulk revoke, is the access actually gone, subscription grant status. Not for: IAM roles, policies or STS (use aws-iam), S3 bucket policies (use securing-s3-buckets), Clean Rooms permissions (use aws-cleanrooms), or writing catalog metadata, glossaries and forms, publishing listings, or retiring or deleting an asset that other teams are subscribed to and the order of operations that needs (use managing-data-catalog)
Guide for using Microsoft MarkItDown - a Python utility for converting files to Markdown. Use when converting PDF, Word, PowerPoint, Excel, images, audio, HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs, Jupyter notebooks, RSS feeds, or Wikipedia pages to Markdown format. Also use for document processing pipelines, LLM preprocessing, or text extraction tasks.
Python Optimization Modeling Objects. A high-level framework for formulating, solving, and analyzing optimization models. Supports Linear Programming (LP), Mixed-Integer Linear Programming (MILP), and Non-Linear Programming (NLP). Part of the COIN-OR project. Use for mathematical optimization, linear programming, mixed-integer programming, non-linear programming, strategic planning, process engineering, energy systems, supply chain optimization, stochastic programming, and solver integration with IPOPT, SCIP, Gurobi, CPLEX, or GLPK.
Implement Syncfusion Blazor Bullet Chart (SfBulletChart) for KPI and performance visualization. Use this when displaying target vs actual metrics, goal tracking, or performance dashboards. This skill covers actual/target bars, qualitative ranges, and comparative analysis for KPI visualization in Blazor applications.
Use when setting up or managing Adapty in-app subscriptions, paywalls, placements, or migrations via CLI, when reading an app's analytics (revenue, MRR, conversions, funnel, retention, LTV, cohorts) with `adapty analytics`, or when reading Attribution analytics (spend, installs, ROAS, cohort revenue, predictions) with `adapty attribution`
Pongfi Research is a cross-platform social media research skill for any industry. It dynamically discovers and invokes TikHub MCP / public social data tools to identify trends, break down subcategories, research competitors, audit accounts, analyze viral content, uncover needs in comments, identify content gaps, compare platforms, and develop data-driven topics for industries, categories, brands, products, people, accounts, or topics. Supports public social platform data from Douyin, TikTok, Xiaohongshu, Instagram, YouTube, X, Weibo, Bilibili, Reddit, Kuaishou, Zhihu, WeChat, LinkedIn, Threads, and more.
Generate deep research reports on prediction market events using the Octagon Prediction Markets Agent. Combines real-time Kalshi market data with AI-driven analysis to surface price drivers, compare market vs. model probabilities, and identify potential mispricings across 120+ active markets.
Build and run AI-generated Bright Data scrapers from the terminal via `bdata scraper create` and `bdata scraper run`. Use this skill whenever the user wants to generate a scraper from a natural-language description, build a custom scraper without writing code, turn a URL + plain-English description into a reusable scraper, run an existing Bright Data collector against a URL, or batch-scrape a list of URLs through one collector. Triggers on phrases like 'build me a scraper for', 'create a scraper that extracts', 'generate a scraper from a description', 'turn this URL into a scraper', 'run this scraper on', 'run my collector', 'batch scrape', 'scrape these URLs', 'scrape a list of URLs', 'competitive pricing table', 'scraper studio', `scraper create`, `scraper run`, `--urls`, `--input-file`, `collector_id`, `automate_template`, or `/dca/`. Covers the AI flow (template create → trigger AI generation → poll progress), the single-URL run flow (async + poll by default, `--sync` for fast pages), the multi-URL batch flow (`--urls` / `--input-file` → one `/dca/trigger` call with array body), and the silent auto-fallback to the batch endpoint when a URL expands past the realtime page limit. Requires the Bright Data CLI.
Analyze proxy statements (DEF 14A) to extract executive compensation, governance information, and shareholder voting matters using Octagon MCP. Use when researching CEO pay, board composition, say-on-pay votes, and corporate governance practices.
Implements the Syncfusion Blazor Chart Wizard for guided chart creation. Use this when building interactive chart builders that require step-by-step configuration, data binding, and export features. Covers chart customization, theming, and accessibility.
Microbiome and metagenomics analysis using MGnify, GTDB taxonomy, ENA sequencing data, and EuropePMC literature. Covers taxonomic classification, genome quality assessment, biome-clinical phenotype linkage, and pathway interpretation. Use for amplicon/shotgun metagenomics study analysis
Enterprise AI adoption platform for Claude Code — measures team usage via OpenTelemetry, syncs skills/MCP servers/hooks from a central dashboard, and delivers context-aware skill suggestions at prompt time. Solves the Intention-Action Gap: organizations that deploy Zeude see 3x adoption improvement (6% → 18%). Requires Supabase (config) and ClickHouse (analytics). Triggers on: zeude, ai adoption, claude code adoption, enterprise claude, opentelemetry claude, skill sync, team claude management.
Search the web and read page contents without API keys. Use when you need to search via DuckDuckGo/Brave/Google (multi-page), extract readable text from URLs, browse interactively with a persistent visible browser (with tabs, click, screenshot, text search), download files/PDFs, or dismiss cookie banners. Supports JSON/markdown/text output. Powered by Playwright + Chromium.
Wren Engine CLI workflow guide for AI agents. Answer data questions end-to-end using the wren CLI: gather schema context, recall past queries, write SQL through the MDL semantic layer, execute, and learn from confirmed results. Use when: user asks a data question, requests a report or analysis, asks about metrics, revenue, customers, orders, trends, or any business data; user says 'how many', 'show me', 'what is the', 'top N', 'compare', 'trend', 'growth', 'breakdown'; user wants to explore, analyze, filter, aggregate, or summarize data from a database; agent needs to query data, connect a data source, handle errors, or manage MDL changes via the wren CLI.
Multi-baseline counterfactual cost analysis. Compares actual session spend to hypothetical always-haiku / always-sonnet / always-opus routing baselines. Answers "is the routing earning its keep?" Negative savings flag over-escalation; positive savings quantify the router's win.
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.