Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Use this skill whenever the user mentions IP geolocation feeds, RFC 8805, geofeeds, or wants help creating, tuning, validating, or publishing a self-published IP geolocation feed in CSV format. Intended user audience is a network operator, ISP, mobile carrier, cloud provider, hosting company, IXP, or satellite provider asking about IP geolocation accuracy, or geofeed authoring best practices. Helps create, refine, and improve CSV-format IP geolocation feeds with opinionated recommendations beyond RFC 8805 compliance. Do NOT use for private or internal IP address management — applies only to publicly routable IP addresses.
Product review analysis and customer feedback intelligence. Pain point identification, praise pattern analysis, feature request extraction, sentiment analysis, and product improvement insights. Use when the user asks about review analysis, customer feedback, product reviews, or sentiment analysis.
Audit any eval, metric, experiment, or benchmark for leakage: does external ground truth enter independently, or are the model, scorer, and designer just confirming a result no outside truth ever produced? Use before trusting any 'how we'll know it worked' — an A/B, a holdout, a score, a validation — and whenever a result feels too clean or self-confirming. Walks an 8-pattern leakage taxonomy and returns only the patterns that fire, each with an independence fix. Read-only.
Use this skill when working with CSV files to create interactive data visualizations, generate statistical plots, analyze data distributions, create dashboards, or perform automatic data profiling. It provides comprehensive tools for exploratory data analysis using Plotly for interactive visualizations.
Provision a zero-config, no-signup, temporary Upstash Redis database for an AI agent with a single POST to https://upstash.com/start-redis, with no account, API key, or SDK setup required. Use when an agent needs scratch Redis right now and the user has not provided credentials, for short-term memory across tool calls, conversation history, a sub-agent work queue, ranked recall, or a quick prototype or demo. Covers idempotent creation and re-fetching credentials, calling the database through the body-style REST API or the official SDKs, and telling the user how to claim it. The database lives 3 days unless the user claims it; not for production data, PII, or secrets.
Create, edit, analyze, and recalculate Excel workbooks (.xlsx, .xlsm) with live formulas, formatting, and charts. Use when a task produces or modifies a spreadsheet file, turns CSV/TSV data into one, or needs values, formulas, or formatting read from one.
Deep Amazon review analysis for competitive intelligence and product improvement. Extract sentiment patterns, recurring complaints, feature requests, and competitive insights from customer feedback. Turn reviews into actionable product development and marketing strategies. Use when the user asks about review analysis, customer feedback, product complaints, sentiment analysis, or what customers think about products
Best practices for building and maintaining applications with PowerSync: Cloud and self-hosted setup, sync configuration, client SDK usage, backend integration (Supabase, custom Postgres, MongoDB, Azure DocumentDB, MySQL, MSSQL), schema changes, watch and reactive queries (useQuery), attachments, the upload queue, and debugging. Use this skill whenever the user mentions PowerSync, a @powersync/* package (@powersync/web, @powersync/react-native, @powersync/node), the powersync Flutter/Dart package, the powersync Rust crate, wa-sqlite, offline-first sync, local-first architecture, sync rules, sync streams, uploadData, fetchCredentials, disconnectAndClear, logout or user switching in a synced app, real-time data replication, Electric Cloud migration, Electric Shapes, an app stuck on Syncing, data not syncing, or wants to add offline-capable sync to a mobile or web app, even if they do not explicitly name PowerSync.
Use when the user asks to “generate an SEO report”, “出月报”, “set SEO alerts”, or “排名掉了提醒我”; two modes—report builds multi-metric traffic/ranking/authority/content dashboards, and alert configures threshold notifications for future ranking, traffic, technical, backlink, competitor, and AI-visibility changes. Not for raw position-by-position deltas—use rank-tracker. SEO报告/绩效仪表盘/SEO预警/排名监控
USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity. Supports Goggles, local/POI. For AI answers use answers. Recommended for anyone building AI/agentic applications.
Use when the user wants to evaluate a creator, influencer, or brand audience using public profile signals, TikTok audience demographics, follower/following data, comments, geography, language, and content fit. Helps judge sponsorship and market fit.
Work with the @upstash/vector TypeScript/JavaScript SDK, a serverless vector database for embeddings, similarity search, semantic search, and RAG (retrieval-augmented generation). Use when upserting, querying, fetching, ranging, or deleting vectors, upserting raw text against an index with a built-in embedding model, choosing dense, sparse, or hybrid indexes, filtering by metadata, organizing data with namespaces, running resumable queries, or connecting Upstash Vector to an AI or LLM application. Also use when the user asks for a vector store, vector search, nearest-neighbor or kNN search, embeddings storage, semantic cache, recommendations or similarity features, or a hosted vector index that needs no infrastructure.
Expert knowledge for Azure SQL Database development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when choosing DTU/vCore tiers, configuring serverless or Hyperscale, geo-replication/DR, CI/CD, or Terraform, and other Azure SQL Database related development tasks. Not for Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines), Azure Cosmos DB (use azure-cosmos-db), Azure Data Factory (use azure-data-factory).
Work with the @upstash/search TypeScript/JavaScript SDK, a serverless full-text and semantic search database with built-in reranking. Use when adding search to an app or site, creating a search index, upserting documents with searchable content and filterable metadata, running keyword, semantic, or hybrid search queries, reranking results, filtering with SQL-like or structured filter syntax, paginating with range, fetching or deleting documents, resetting an index, or checking index info. Also use when the user asks for site search, product, document, or knowledge-base search, or a managed search service that needs no cluster to run.
Writes and executes SQL queries from simple SELECTs to complex multi-table JOINs, aggregations, and subqueries. Use when the user asks to query a database, write SQL, run a SELECT statement, retrieve data, filter records, or generate reports from database tables.
Lists tables, describes columns and data types, identifies foreign key relationships, and maps entity relationships in a database. Use when the user asks about database schema, table structure, column types, what tables exist, ERD, foreign keys, or how entities relate.
Create agents for financial analysis, investment research, and portfolio management. Covers financial data processing, risk analysis, and recommendation generation. Use when building investment analysis tools, robo-advisors, portfolio trackers, or financial intelligence systems.
Ancient text restoration, attribution, dating, contextualization, and embedding via Aeneas (Latin) / Ithaca (Ancient Greek). Use when asked to "restore", "attribute", "date", "contextualize", "find parallels", "where was it written", "when was it written", "embed", or "analyze" an ancient text, inscription, or epigraphic document, or when the user mentions "Aeneas", or "Ithaca".
Agentforce session tracing extraction and analysis. TRIGGER when: user extracts STDM data from Data Cloud, analyzes agent session traces, debugs agent conversations via telemetry, or works with .parquet files from Agentforce. DO NOT TRIGGER when: testing agents (use sf-ai-agentforce-testing), Apex debug logs (use sf-debug), or building agents (use sf-ai-agentforce).
Seller storefront analysis and competitive intelligence for Amazon. Analyzes seller revenue estimation, product portfolio strategy, growth trajectory, and market positioning. Reverse-engineer successful seller strategies and identify expansion opportunities. Use when the user asks about analyzing sellers, competitor seller analysis, seller revenue estimation, storefront analysis, seller strategy, or learning from successful Amazon sellers.
Competitor pricing strategy analysis and market positioning. Price mapping, pricing gaps identification, elasticity signals evaluation, and strategic pricing optimization. Use when the user asks about competitor pricing, price analysis, pricing strategy, or competitive pricing research.
Workflow and best practices for writing Apache Airflow DAGs. Use when creating a new DAG, write pipeline code, handling questions about DAG patterns and conventions or extending an existing DAG with a follow-up/downstream task. ANY request shaped like 'add a DAG named X', 'write a pipeline', 'add a task that runs after Y', or 'extend the DAG'. For testing and debugging DAGs, see the testing-dags skill.
Use when working with MasterData v2 entities, schemas, or MasterDataClient in VTEX IO apps, or when anyone designing or implementing a solution must scrutinize whether Master Data is the correct storage. The skill prompts hard questions: native Catalog or other VTEX stores, OMS, or an external database may be better; do not default to MD because it is convenient. Covers JSON Schema, CRUD, triggers, search and scroll, schema lifecycle, purchase-path avoidance, single source of truth, and BFF handoffs. Use for justified custom persistence while avoiding the 60-schema limit.
Amazon sales volume estimator for sellers and product researchers. Estimate monthly sales and revenue from BSR (Best Seller Rank), ASIN, or keyword. Three modes: (A) BSR Calculator — input BSR + marketplace + price + category to get instant sales estimate, (B) ASIN Lookup — input ASIN to auto-fetch data and estimate sales, (C) Keyword Market Analysis — input keyword to analyze total market size and competition. Works on 12 Amazon marketplaces. No API key required. Use when: (1) estimating how many units a product sells per month, (2) sizing a market or niche opportunity, (3) analyzing competitor sales performance, (4) comparing sales across price points, (5) identifying top sellers vs long-tail distribution.
Analyzes Google Cloud BigQuery slot consumption, query costs, and execution bottlenecks using INFORMATION_SCHEMA. Use when diagnosing slow BigQuery queries, slot starvation, high on-demand query costs, unpartitioned table scans, or join performance issues. Don't use for generic BigQuery administration (use bigquery-basics), BigQuery ML (use bigquery-ai-ml), or DataFrame operations (use bigquery-bigframes)
OCR skill using the PaddleOCR model via SiliconFlow API. Use this skill when the user asks to “recognize text from an image,” “extract text from a photo,” “OCR this image,” “read text from screenshot,” or mentions “PaddleOCR,” “image text recognition,” or “text extraction from images.”
Trending products and rising categories discovery for Amazon sellers. Analyzes Best Seller Rank patterns, seasonal trends, new release momentum, and emerging niches. Identifies product opportunities before they peak. Use when the user asks about what's trending on Amazon, hot products, rising categories, seasonal opportunities, viral products, what to sell next, emerging niches, or early-mover opportunities. Also trigger for questions like 'what should I sell now?', 'what products are doing well?', 'find me trending niches', or 'what's hot on Amazon?'.
Use when modelling designer-authored game data in C++ and loading it: data assets, data tables, curve tables, soft references and asset streaming. Also use when the user mentions 'UDataAsset', 'UPrimaryDataAsset', 'UDataTable', 'FTableRowBase', 'FindRow', 'FDataTableRowHandle', 'TSoftObjectPtr', 'TSoftClassPtr', 'FSoftObjectPath', 'UAssetManager', 'LoadPrimaryAsset', 'FStreamableManager', 'RequestAsyncLoad', 'asset bundles', 'PrimaryAssetTypesToScan', 'IAssetRegistry', 'CSV import', or 'hard vs soft reference'. For save games, see ue-serialization-savegames; for UPROPERTY basics, see ue-cpp-foundations; for level streaming, see ue-world-level-streaming.
Comprehensive DAG failure diagnosis and root-cause analysis with structured investigation and prevention recommendations. Use when deep failure investigation is needed, a DAG fails to import/parse or 'airflow dags list' errors on a file; a task or run is failing and must be diagnosed and fixed; requests like 'why did X fail', 'my dag keeps failing — find and fix it', or fixing a broken DAG so it loads cleanly. For simple 'why did it fail / show logs', the airflow skill handles it directly.
Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.
Amazon negative keyword management and optimization. Search term analysis, waste reduction, savings estimation, and automated negative keyword strategies. Use when the user asks about negative keywords, search term analysis, ad waste reduction, or PPC optimization
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.