Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Extract structured data from Axure prototypes using Playwright — screenshots, design tokens, interaction maps, annotations, and page text. Use this skill whenever the user wants to extract data from an Axure prototype, reconstruct or clone an Axure page, analyze Axure design tokens, export Axure content, or work with Axure prototype URLs (even if they don't say "Axure" explicitly — look for AxShare links, /start.html#p= URLs, /start.html?id=...&p= URLs, or mentions of wireframes/prototypes hosted online).
Ports HDInsight Spark and Hive workloads to Fabric, converting HiveContext and SparkContext to SparkSession, WASB and ABFS paths to OneLake shortcuts, Hive DDL to Delta tables in a Lakehouse, and Oozie coordinators and actions to pipeline activities and triggers. Use when the source workload is HDInsight.
Query Huawei Cloud MaaS (Model as a Service) tokens usage statistics, including total tokens, prompt tokens, completion tokens, total requests, and total errors. Supports preset service, my service, and custom endpoint with time range queries (last 7/14/30 days or custom). Data source is MaaS ShowStatistics API, consistent with console. Use this skill when the user wants to: (1) query MaaS token consumption statistics, (2) check MaaS service request counts and error rates, (3) analyze token usage for preset service or my service, (4) monitor MaaS usage over a specific time period. Trigger: user mentions "MaaS", "Model as a Service", "tokens usage", "token consumption", "request count", "error count", "MaaS usage", "preset service usage", "completion tokens", "prompt tokens", "MaaS statistics", "模型服务", "令牌用量", "token统计", "token用量", "词元用量", "请求次数", "MaaS监控", "华为云MaaS"
Use when uploading locally trained model weights (YOLO, RF-DETR, YOLO-NAS, PaliGemma, Florence-2) to Roboflow—covering the client-side Python SDK upload flow, safe API key handling, per-family packaging requirements, and upload verification.
Create Tufte-inspired data reports and infographic dashboards as standalone HTML files. Uses EB Garamond for text, Monaspace Argon for numbers, Chart.js for interactive charts, and inline SVG sparklines. Produces publication-quality reports with 2-column narrative+data layouts, status dashboards, scroll animations, and responsive mobile support. Use this skill whenever the user wants to create a data report, activity dashboard, infographic, personal analytics page, health tracker visualization, or any document that combines narrative text with interactive charts and tables. Also triggers for "make a report like Tufte", "create an infographic", "build a dashboard", "visualize my data", or requests for beautiful data-driven documents.
Use this skill when users need to search across multiple platforms, including GitHub (repositories, code, issues), Reddit (posts, subreddits, users), Xiaohongshu, Douyin, Bilibili, YouTube, Twitter, WeChat (official account articles), Google, Tavily, Metaso Search, Volcano Engine, and general search engines (DuckDuckGo, Brave, Yahoo, Bing, Wikipedia, Anna's Archive), or download images from 18 image platforms (Baidu, Bing, Google, Pixabay, Unsplash, Volcano Engine, and others). Provides a unified search interface with structured output formats, result filtering and sorting, automatic response archiving, and batch image downloads with metadata preserved.
Generates executable quantitative strategy code for the akquant framework, covering data interfaces, event-driven execution, risk control, and optimization. Use when developing quantitative strategies, configuring backtesting environments, setting risk rules, optimizing parameters, implementing cross-sectional rotation strategies, or mentioning akquant.
Comprehensive cryptocurrency market research and analysis using specialized AI agents. Analyzes market data, price trends, news sentiment, technical indicators, macro correlations, and investment opportunities. Use when researching cryptocurrencies, analyzing crypto markets, evaluating digital assets, or investigating blockchain projects like Bitcoin, Ethereum, Solana, etc.
Build and deploy a Coralogix dashboard for a given service from its logs, spans, metrics, and service specs. Discovers telemetry via cx CLI commands, emits importable Coralogix JSON, verifies every PromQL and DataPrime query live through the `cx` CLI, and creates the dashboard via `cx dashboards create`. Use whenever the user asks to create, build, generate, or deploy a Coralogix dashboard, monitoring dashboard, or observability dashboard for a service, app, or pipeline.
Investigates a single PostHog error tracking issue end-to-end. Use when the user provides an issue ID or pastes an issue URL (`/error-tracking/<id>`) and wants to understand the error — who it affects, what triggers it, when it started, whether it correlates with a release, browser, OS, or feature flag, and what the next step should be. Pulls aggregated metrics, sample exception events, segment breakdowns, linked replays, and synthesizes a hypothesis-grade summary in one pass
Apply runtime filters to embedded Domo dashboards/cards from the host page via the JS API (MessagePort). Covers dynamic filtering, drill events, filter change listeners, iframe resize, pfilter URL params, overrideFilters, and App Studio appData. Use for any client-side Domo embed interaction. Not for server-side programmatic filters (use programmatic-filters).
Complete guide to Python strategy development for QMT (迅投极速策略交易系统). Covers strategy writing, backtesting, live trading, API references, and code examples. Use when the user needs to develop QMT quantitative strategies, look up the QMT API, migrate from JoinQuant to QMT, write live trading programs, or mentions QMT, 迅投策略, or QMT backtesting.
Use when implementing 'CloudKit sync', 'CKSyncEngine', 'CKRecord', 'CKDatabase', 'SwiftData CloudKit', 'shared database', 'public database', 'CloudKit zones', 'conflict resolution' - comprehensive CloudKit database APIs and modern sync patterns reference
Expert knowledge for Azure Table Storage development, including best practices, architecture and design patterns, limits and quotas, security, configuration, integrations, and coding patterns. Use when securing Table Storage, tuning telemetry, planning scale limits, designing keys, scripting with PowerShell, or handling other Azure Table Storage development tasks. Not for Azure Cosmos DB (use azure-cosmos-db), Azure Blob Storage (use azure-blob-storage), or Azure Queue Storage (use azure-queue-storage).
Database security auditor specialized in Row Level Security (RLS) enforcement, Zero-Trust database architecture, and forensic audit trails. Covers Supabase RLS policies, Postgres security, Convex auth guards, PGAudit configuration, JIT access controls, and database-specific compliance validation. Use when auditing database access policies, implementing RLS in Supabase or Postgres, configuring Convex auth guards, setting up audit logging, reviewing database security, or validating database-level compliance requirements
Use this skill when the user wants to add or update metadata in DataHub: descriptions, tags, glossary terms, ownership, deprecation, domains, data products, structured properties, documents, or field-level metadata. Triggers on: "add tag to X", "update description for X", "set owner of X", "add glossary term", "deprecate X", "create a domain", "create a glossary term", "add a document", or any request to modify DataHub metadata.
Use this skill when the user wants to manage data quality in DataHub: create or run assertions, check assertion outcomes, raise or resolve incidents, create notification subscriptions, or diagnose health problems across their estate. Triggers on: "create assertion", "run assertion", "check quality", "data quality", "health check", "raise incident", "resolve incident", "subscribe to", "failing assertions", "active incidents", or any request involving data quality, assertions, incidents, or quality notifications
Master fine-tuning of large language models for specific domains and tasks. Covers data preparation, training techniques, optimization strategies, and evaluation methods. Use when adapting models for specialized applications, reducing inference costs, or improving domain-specific performance.
Designs and implements data layer architecture for Magento 2. Use when creating data models, designing database schemas, implementing repositories, or working with EAV/flat table structures. Masters entity design, repository patterns, collections, and database optimization.
Plan, design, author, preview, publish, and manage Power BI reports across requirements, page design, local PBIR/PBIP edits, validation, screenshots, Fabric upload/download, and rebinding. Use for report lifecycle work; use semantic-model-authoring for model or DAX changes and fabriciq for data questions. Triggers: plan Power BI report, design report page, edit PBIR, preview PBIP, publish report, rebind report
Alibaba Cloud MaxCompute Cost Analysis Skill. Analyze MaxCompute pay-as-you-go costs including billing, storage metrics, and compute metrics. Triggers: "maxcompute cost", "odps cost", "maxcompute billing", "maxcompute费用", "成本分析", "费用分析", "存储用量", "计算用量", "费用突增", "SQL签名", "SQL signature", "重复SQL", "扫描量最大", "daily billing details", "每日账单明细", "按计费项", "billing by fee item".
Create AppDB collections via CLI-first workflows where collection creation also provisions the required datastore, then returns collection identifiers for manifest wiring and document-write follow-up. Use when an agent must initialize new AppDB storage for a Domo app, not just list/get collections or create documents.
Query ESPN's public API for live scores, standings, rosters, player stats, odds, play-by-play, injuries, transactions, news, and more across 17 sports and 139 leagues. Use when the user needs sports data from ESPN, wants to build a sports app, fetch scores or schedules, look up player or team stats, get betting odds, or pull any structured sports data. Triggers on mentions of ESPN, sports scores, standings, box scores, player stats, game data, or league data
Retrieve and analyze Amazon product reviews by ASIN across 15 marketplaces, including the US, with filtering by star rating. Triggers when users mention Amazon reviews, US reviews, Amazon.com reviews, product feedback, buyer complaints, negative or positive reviews, star ratings, review analysis or sentiment, product improvement suggestions, Vine reviews, verified purchase reviews, competitor review research, or customer feedback. Also trigger when a request involves reading, filtering, or analyzing Amazon product reviews, even if the user does not explicitly say “reviews”.
Xiyou keyword research (Xiyou Insights) for Amazon ASIN and keyword analysis, routed through the LinkFox gateway to the Xiyou OpenAPI. Covers 17 endpoints, including ASIN traffic scores, reverse keyword lookup, keyword ranking/traffic trends, BSR, ABA weekly trends, keyword competition, and suggested bids; supports 13 marketplaces, including US/UK/DE. Triggers when users mention 西柚找词, 西柚洞察, Xiyou, reverse ASIN keyword lookup, keyword analysis, ABA weekly search volume, traffic scores, keyword ranking trends, xiyou keyword research, ASIN traffic score, reverse ASIN lookup, or search term analysis. Trigger even if the user does not mention “西柚” when they want to use Xiyou keyword research to retrieve Amazon ASIN/keyword traffic and ranking data. Before use, configure LINKFOXAGENT_API_KEY and the XIYOU_CLIENT_ID and XIYOU_CLIENT_SECRET environment variables.
Control which data each viewer sees in an embedded Domo dashboard/card via server-side programmatic filters and dataset switching. Covers the OAuth → embed token flow, standard filters, SQL filters (OR/BETWEEN/LIKE), per-dataset targeting, datasetRedirects for multi-tenant architectures, and token size limits. Use for any per-viewer, per-role, or per-tenant data restrictions at embed time. Not for client-side JS API filtering (use jsapi-filters).
Use for Bitrix SQL and ORM patterns: raw SQL or Connection queries, DataManager maps or field definitions, Objectify objects or collections, ORM queries or filters, and ORM writes or batch persistence. Use when designing, reviewing, or implementing database reads, writes, schemas, or data access code.
**Custom Domo connector authorship** — invoke when someone is writing the JavaScript code that defines a custom Domo connector. Primary signals: questions about authentication.js, dataProcessing.js, or Domo's connector APIs (datagrid, httprequest, auth, metadata). Covers all connector coding topics: auth credential validation, API pagination loops, writeback connectors, column consistency, connector README docs. The user is *building* a connector in Connector Dev Studio, not using a pre-built one. Skip for: pre-built connectors (Salesforce, Postgres, Snowflake), Python connector, Domo App Platform cards/apps, Workflows, Federated Connectors.
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.