Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Implement Syncfusion Blazor Stock Chart (SfStockChart) for financial data visualization. Use this when working with stock charts, candlestick displays, OHLC data, or technical indicators like SMA, EMA, MACD, and Bollinger Bands. This skill covers period selectors, range navigation, and financial time-series data visualization in Blazor applications.
A four-dimensional quantitative assessment tool for diagnosing any WeChat Official Account. It scores content health, user activity, core content metrics, and operational compliance against industry averages, then provides actionable operational improvement suggestions.
A crawler for Xiaohongshu posts. Crawls popular Xiaohongshu post data by keyword, with filters for date range and sorting; results are shown in a structured table. Use when users need to crawl Xiaohongshu posts, look up popular content, or search for viral notes. Trigger terms: Xiaohongshu crawling, Xiaohongshu posts, Xiaohongshu viral posts, Xiaohongshu search, Xiaohongshu popular content, Xiaohongshu note lookup. If the API returns insufficient credits (code=3210), automatically open Alipay to top up and continue the query.
Market structure analysis with Wyckoff, SMC/ICT, Al Brooks, and classical price action — outputs structured trade scripts with levels, entry, stop, R:R. Use when the user wants real technical analysis on a ticker (e.g. "market structure analysis on NVDA", "Wyckoff phase for BTC", "where's the order block on SOL", "SMC analysis").
A spaced repetition learning coach for Metabase. Use this skill whenever the user wants to: learn Metabase, start a Metabase training session, do a Metabase review, practice Metabase concepts, check what they should study today, get quizzed on Metabase, run through active recall on BI tools, or follow a structured learning program for data analytics software. Trigger this skill even if the user just says "let's do my Metabase session", "quiz me on Metabase", or "what should I study today?" in a Metabase learning context.
Provides guidance for building and customizing Syncfusion Blazor 3D Charts. Trigger this skill whenever the user needs help with SfChart3D, 3D Column/Bar charts, axes, data binding, rotation, tilt, depth, legends, tooltips, or any configuration in Syncfusion.Blazor.Chart3D
Implements the Syncfusion Blazor HeatMap Chart component for multidimensional data visualization using color-coded grids. Use for heatmaps, data matrices, correlation displays, or bubble heatmap variants. Covers installation, data binding, axis configuration, color palettes, legends, tooltips, and accessibility features.
Implement Syncfusion Blazor Sparkline Charts for compact, inline trend visualizations in Blazor applications. Use for mini charts, KPI indicators, dashboard sparklines, or word-sized data visualizations. Covers line, area, column, WinLoss, and pie sparklines, including data labels, markers, special points (high/low/negative), range bands, tooltips, and appearance customization. Ideal for dashboards, data tables with inline trends, email reports, and mobile data visualization scenarios requiring compact trend indicators.
Identify performance issues in WooCommerce PHP code. Use when writing or reviewing code that loads collections of post-based objects (products, orders), renders product lists with images, reads multiple options in a loop or method, or writes SQL queries involving joins, aggregates, meta lookups, or range queries
Comprehensive CSV data analysis and visualization tool. Use this skill when analyzing CSV files, generating data summaries, creating visualizations from data, detecting outliers, finding correlations, assessing data quality, or creating data reports. Triggers on CSV analysis, data exploration, data visualization, data profiling, statistical analysis, or data quality assessment requests
Assesses what a page's heatmap is telling you and recommends concrete changes. Pulls click / rageclick / scroll-depth data for a URL, names the hot elements by cross-referencing autocapture events on the same page, and can create a saved heatmap the user opens in PostHog, then summarizes the behavior and proposes improvements. TRIGGER when: user asks what a heatmap shows, why people aren't clicking something, where users rage-click, how far they scroll, what to change on a page based on heatmap/click data, or to 'analyze/assess/review the heatmap' for a URL. DO NOT TRIGGER when: the user only wants to create a saved heatmap screenshot with no analysis (use heatmaps-saved-create directly), or is asking about session replay in general (use investigating-replay).
Query, audit, and optimize Google Ads campaigns. Use an attached browser or the Google Ads API for campaign, keyword, budget, conversion-tracking, and wasted-spend analysis, or when the user explicitly requests a reviewed account change. Defaults to read-only reporting; account mutations require a bounded preview and action-time approval.
Expert guidance on ParadeDB text and vector search, hybrid search (BM25 + semantic), filters, facets, joins, and aggregations in Postgres. Use when writing ParadeDB queries, creating ParadeDB indexes, indexing vectors, configuring tokenizers, or implementing Elasticsearch-quality search in Postgres.
Comprehensive guide for implementing the Syncfusion Blazor Sankey Diagram (SfSankey) component for flow visualization in Blazor applications. Use this when working with Sankey diagrams, flow visualization, or process flows. This skill covers node and link configuration, data binding, flow magnitude representation, and diagram customization. Ideal for visualizing energy flows, supply chain relationships, user journey maps, traffic analysis, and any scenario involving flows between categories or stages
Academic backtesting framework for quantitative research. ~30 risk and performance ratios, 10 classes of indicators, event-driven engine with 6+ strategies, MPT optimizer, forward-looking simulation with Johnson SU + t-Copula, walk-forward CV, stress testing, fundamental analysis (Altman Z, Piotroski, DuPont). All flat Python + numpy.
This skill should be used when the user asks about the "CAP theorem", "PACELC", a "consistency model", "eventual vs strong consistency", "read-your-writes", "causal consistency", "quorum" or "R+W>N", "consensus", "Raft / Paxos", "leader election", "consistent hashing", a "distributed transaction", "2PC", or "saga". Use it whenever a design has multiple copies of data or coordinating nodes and a decision hinges on what a reader is guaranteed to see during replication lag, a network partition, or a node failure — even if the user doesn't say "consistency".
Comprehensive equity research analyst skill that orchestrates all Octagon financial analysis skills. Use when conducting full company analysis, writing initiation of coverage reports, performing due diligence, or creating investment recommendations with quantitative support.
Query data on TikTok product-linked promotional videos, including views, likes, comments, shares, video sales, and GMV, to analyze product video marketing performance and creator content effectiveness. Trigger this skill when the user mentions TikTok product videos, TikTok promotional videos, product-linked videos, video marketing analysis, creator video performance, TikTok video sales, product video analysis, influencer video performance, TikTok promotional videos, or product marketing videos. Even if the user does not explicitly mention “EchoTik” or “product videos,” trigger this skill whenever their request involves viewing the promotional videos for a TikTok product or the videos’ view and conversion data
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.
Implement Syncfusion Blazor Smith Chart for RF circuit analysis and transmission line impedance matching. Use this when visualizing impedance/admittance data, reflection coefficients, S-parameters, or antenna tuning in Blazor applications. This skill covers circular grid representations and RF network parameter analysis.
Implement and configure the Syncfusion Blazor TreeMap component (SfTreeMap) for hierarchical data visualization. Use this when working with treemaps, area-proportional visualizations, or heat-map-like block displays. This skill covers TreeMap setup, layout configuration, data binding, color mapping, drill-down navigation, and accessibility features.
This skill should be used when the user asks to "analyze a competitor", "compare pricing", "competitive landscape", "market research", "what do customers think", "review intelligence", "hiring signals", "content strategy", "SEO battle", "build a battlecard", "competitive analysis", "who are the players", "who competes with", "market intelligence", "competitive positioning", "deep dive on a company", "board prep", "SWOT analysis", "how does [X] compare to [Y]", or mentions competitor analysis, pricing comparison, customer sentiment, or market landscape research. Requires Apify CLI or Apify MCP server.
Translates SQL queries, DDL schemas, and stored procedures from legacy database dialects (Teradata, Oracle, Redshift, Snowflake, SparkSQL, HiveQL) to BigQuery GoogleSQL using the BigQuery Migration Service (BQMS) MCP server. Use when translating legacy SQL queries, migrating schemas or metadata zip archives, or configuring BigQuery Migration Service (BQMS) YAML translation settings. Don't use for executing BigQuery queries or managing datasets and tables (use bigquery-basics), diagnosing runtime job errors (use bigquery-troubleshooting), or tuning slot reservations (use bigquery-optimization).
Use Databricks built-in AI Functions (ai_classify, ai_extract, ai_summarize, ai_mask, ai_translate, ai_fix_grammar, ai_gen, ai_analyze_sentiment, ai_similarity, ai_parse_document, ai_prep_search, ai_query, ai_forecast) to add AI capabilities directly to SQL and PySpark pipelines without managing model endpoints. Also covers document parsing and building custom RAG pipelines (parse → prep_search → index → query).
Design the UX of custom-code Databricks Apps (AppKit/React) data screens — KPI/overview pages, reports, charts, tables, and Genie/chat data assistants — mapped to concrete AppKit components. Use when BUILDING or reviewing the UI of an AppKit/React app that displays data or answers data questions: choosing genre, layout, charts, KPIs, semantic color, required states (loading/empty/error), IBCS notation, and AI-result trust (showing generated SQL/sources for Genie/chat). A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, NOT this skill. Also NOT for non-data frontend (forms, settings, auth, marketing) or scaffolding/build/deploy (→ databricks-apps). Complements databricks-apps; use it alongside whenever a custom app has a chart, table, KPI, report, or Genie/chat/AI surface.
Build document Q&A with Gemini File Search—a fully managed RAG system with automatic chunking, embeddings, and citations. Upload 100+ file formats and query using natural language. Use for document Q&A, searchable knowledge bases, and semantic search. Troubleshoot document immutability, storage quota (3x), chunking config, metadata limits (20 max), polling timeouts, displayName dropped (Blob uploads), grounding lost (JSON mode), and tool conflicts (googleSearch + fileSearch).
Catalyst QuickML — no/low-code ML, Generative AI, and ready-to-use AI platform. Covers (1) Prediction: ML pipelines, classification/regression, text analytics, recommendation, forecasting, clustering, anomaly detection, AutoML, prediction endpoints; (2) Generative AI: LLM Serving (chat, VLM), RAG, Knowledge Base, GenAI endpoints; (3) Zia Model Library: pre-built no-training models; (4) QuickML pricing — subscription plans and pay-as-you-go rates. Trigger on 'QuickML', 'AutoML', 'ML pipeline', 'train a model', 'model endpoint', 'LLM Serving', 'RAG', 'Knowledge Base', 'no-code ML', 'MLOps', or QuickML pricing/cost/billing/plan questions. DC availability: Prediction models all DCs; Generative AI (LLM Serving, RAG, Knowledge Base) NOT in AU, SA, or CA; Zia Model Library IN only.
Unity Catalog metric views: define, create, query, and manage governed business metrics in YAML. Use when building standardized KPIs, revenue metrics, order analytics, or any reusable business metrics that need consistent definitions across teams and tools.
Use this skill when designing “distributed logging,” “log aggregation,” “centralized logs,” an “ELK” or “EFK” stack, “log shipping,” “structured logging,” a “correlation ID” or “trace ID” in logs, “log retention,” or “high-volume log ingest.” It covers the collect → buffer → ship → index → store → retain pipeline, sampling, ordering, and cold-storage tiering. Use it whenever many services emit logs that must be searchable in one place under load, even if the user doesn’t say “logging pipeline.”
This skill should be used when the user designs a "search system", needs "full-text search", asks about an "inverted index", "Elasticsearch / OpenSearch", "relevance ranking" (TF-IDF/BM25), "search autocomplete / typeahead", an "indexing pipeline", or "faceted search". It gives the crawl/index/search architecture, index sharding and replication, ranking, and near-real-time indexing. Use it whenever users must query text by relevance rather than fetch rows by key, even if they don't say "search engine".
Datos de mercado de TradingView via APIs publicas internas sin auth: Scanner (~300 columnas con quote/indicadores tecnicos/financials/earnings/ratings/targets), Symbol Search v3 (ISIN/CUSIP/CIK), News Headlines, scraping HTML de subpages (technicals/financials/forecast/options/ideas). Cobertura GLOBAL: 100k+ stocks, 50k+ cryptos, indices, forex, bonos. 24 modos CLI.
Build semantic search with Cloudflare Vectorize V2. Covers async mutations, 5M vectors/index, 31ms latency, returnMetadata enum changes, and V1 deprecation. Prevents 14 errors, including dimension mismatches, TypeScript types, and testing setup. Use when building RAG or semantic search, or troubleshooting returnMetadata, V2 timing, metadata index, dimension errors, vitest setup, or wrangler --json output.
Expert in event sourcing, CQRS, and event-driven architecture patterns. Masters event store design, projection building, saga orchestration, and eventual consistency patterns. Use proactively for event-sourced systems, audit trail requirements, or complex domain modeling with temporal queries
Analyze pipeline health, identify stalled deals, predict close probability, and suggest actions to move deals forward. Improves forecast accuracy and prevents revenue leakage. Use when deals get stuck or forecast accuracy is poor.
Query and export data from seekdb vector database. Supports two search modes: (1) Scalar search - metadata filtering only, (2) Hybrid search - fulltext + semantic search combined. The --query-text parameter is used for BOTH fulltext ($contains) and semantic (query_texts) search simultaneously. Can export results to CSV/Excel.
Build on Snowflake's AI Data Cloud with snow CLI, Cortex AI (COMPLETE, SUMMARIZE, AI_FILTER), Native Apps, and Snowpark. Covers JWT auth, account identifiers, and Marketplace publishing. Prevents 11 documented errors. Use for Snowflake apps, Cortex AI SQL, and Native App publishing. Troubleshoot JWT auth failures, account locator confusion, memory leaks, and AI throttling.
Use when designing or revisiting product pricing — selecting a pricing model (subscription seat-based, usage-based, value-based, freemium, or hybrid), running Van Westendorp Price Sensitivity Meter analysis on WTP survey data, or designing Good/Better/Best packaging tiers. Recommends a model and a price range with trade-offs, never a single number. For Commercial leads, Product Marketing, and CMOs at the pricing-design moment — not deal-by-deal discounting, not brand positioning.
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).
Look up seekdb database documentation. Use when users ask about seekdb features, SQL syntax, vector search, hybrid search, integrations, deployment, or any seekdb-related topics. Automatically finds relevant docs through catalog-based semantic search.
This skill should be used when the user wants a "blob store" or "object storage", names "S3" or an S3-compatible store, needs to "store images / video / files", asks about "multipart upload" or "resumable upload", "signed / presigned URLs", "media storage", "unstructured data at scale", object "versioning", storage "tiering" (hot/cold/archive), or "erasure coding" vs replication for durability. Use it whenever a design must hold large unstructured objects (photos, video, backups, logs, ML datasets) and serve them cheaply and durably, even if the user just says "where do we put the files".
A topic research tool for Chinese social media. Searches real discussions from the past 30 days across Xiaohongshu, Douyin, and WeChat Official Accounts, and compares public opinion trends across platforms. Use when users want to research Chinese social media topics, analyze public opinion trends, or compare brand reputation. Trigger terms: Xiaohongshu trends, Douyin trends, WeChat Official Accounts public opinion, cross-platform analysis, social media research, topic analysis, public opinion monitoring
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.