Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Stealth Chromium browser automation that bypasses bot detection. Use this skill whenever the user wants to scrape, screenshot, PDF, or automate a site that blocks normal headless browsers — Cloudflare Turnstile, reCAPTCHA v3, FingerprintJS, ShieldSquare, BrowserScan, "Access Denied" responses, suspicious 403/429s on plain `curl`, or any site where Playwright/Puppeteer get caught. Also use when the user mentions CloakBrowser, stealth Chromium, anti-bot bypass, "headless detection", "real Chrome fingerprint", or wants a one-off "what does this page actually render" check. Prefer this skill over raw `curl`/`fetch` for any site behind a CDN or bot-detection layer.
Use this skill when you need to inspect, query, maintain, or carefully modify the MoviePilot database. This skill uses the bundled scripts/mp-db.py helper, which reads MoviePilot local settings itself and never requires database passwords or full PostgreSQL DSNs in the agent prompt. Applicable scenarios include data statistics, counts, aggregations, inspecting or fixing records, cleanup requests, and questions like "how many downloads", "show site stats", "delete old records", or "why is this subscription stuck".
Design, audit, or reframe data-heavy dashboards, admin tools, operations consoles, analytics products, and enterprise interfaces as decision interfaces rather than metric collections. Use when a user asks to build or improve a dashboard, KPI page, BI view, analytics UI, operational console, monitoring interface, data visualization, or other screen where a person must prioritize, diagnose, compare, decide, or act.
Guides application developers in designing correct and performant transaction patterns for CockroachDB, covering transaction lifetime, implicit vs explicit transactions, retry handling with exponential backoff, pushing invariants into SQL, selective pessimistic locking, set-based operations, connection pooling, prepared statements, keyset pagination, follower reads, and separating business logic from database logic. Use when building applications on CockroachDB, designing transaction workflows, handling retries, optimizing application-layer database interactions, or configuring connection pools.
Institutional-grade equity research report generation skill. Covers listed companies on China A-shares, Hong Kong stocks, and US stocks. Output modes: 1) Investment snapshot: 3-5 pages, including company overview, core financial metrics, valuation multiples, investment thesis, and risk factors; 2) In-depth research report: ≥25 pages, including industry analysis, industry chain mapping, three-statement model, DCF valuation, scenario analysis, and sensitivity testing. Trigger conditions: 1) Direct requests: analyze/look at/research/investigate/introduce + company name or stock; 2) Investment inquiries: what do you think/can I buy/is it worth investing/help me look/dig into + company or stock; 3) Keywords: research report, investment brief, investment snapshot, company one-pager, in-depth research report, in-depth research, in-depth analysis, individual stock analysis, one-pager, snapshot, company snapshot, equity research report; 4) Stock tickers: standard formats (e.g. 600519.SH, 0700.HK, AAPL, TSLA, BYD). When the intent is unclear, proactively ask for the output mode; never infer by default.
Perform systematic exploratory data analysis to understand dataset structure, distributions, relationships, and anomalies before modeling. Use when a dataset is new, its quality is unknown, or the user requests open-ended profiling; use data-analysis instead for a defined hypothesis or decision question.
Huawei Cloud MRS Hive SQL specification checking skill. Checks SQL statements against defined syntax and specification rules using the automated checker engine. No extra manual analysis beyond defined rules. Trigger: "Hive SQL优化", "检查Hive SQL", "Hive SQL检查", "Hive SQL规范", "Hive SQL语法", "Hive SQL review"
Low-level Python plotting for scientific figures: publication-quality line, scatter, bar, heatmap, contour, 3D; multi-panel layouts; fine control of every element. PNG/PDF/SVG export. Use seaborn for quick stats, plotly for interactive.
Use when the user has a list of names or companies and wants their job, employer, work history, LinkedIn URLs or company profiles looked up, or wants to find people or companies matching criteria — trigger on phrases like \"enrich these contacts\", \"find their LinkedIn\", \"look up these people\", \"who works at X\", \"find directors at Y\", \"enrich these companies\", or \"get firmographics for\". Enrich and search People Data Labs (PDL) Person and Company data, writing results to .xlsx. Five operations: enrich named PEOPLE into a profile, employment history and LinkedIn URL; IDENTIFY an ambiguous person as several scored candidates; SEARCH people by criteria (company, title, location); enrich COMPANIES into firmographics (industry, size, employees, HQ, founded, LinkedIn); and SEARCH companies by criteria. Do not scrape LinkedIn directly — this uses a licensed data aggregator (PDL) instead, for legal and reliability reasons.
Ingest MCAP files into Rerun chunk streams with rerun.chunk.McapReader. Read when converting an MCAP recording, selecting topics or decoders, decoding custom protobuf messages, or when an MCAP-derived stream comes out empty. Builds on rerun-chunk-processing (stream mechanics) and rerun-data-model (what the topics should become).
Performs a comprehensive health check of a CockroachDB cluster. Gathers deployment context first, then provides tier-appropriate diagnostics. Self-Hosted uses SQL against node-level system tables and CLI. Advanced/BYOC use Cloud Console and SQL with node visibility. Standard monitors provisioned compute and workload via Cloud Console. Basic monitors Request Unit consumption and connectivity. Use for daily checks, pre-maintenance validation, post-incident verification, or production readiness assessment.
Implements Syncfusion Essential Grouping for WPF, a data organization engine that works without UI controls. Use this when working with GroupingEngine, TableDescriptor, or organizing tabular data with hierarchical grouping, custom sorting, and filtering. Supports binary tree data structures, expression fields, summary calculations, and aggregate operations for WPF data analysis applications.
Analyze and update 68 US economic and social indicators from five government APIs (FRED, EIA, Treasury, BLS, Census) across 10 categories: GDP, Inflation, Employment, Housing, Consumer Finance, Markets, Trade, Government/Fiscal, Demographics, Health. Two workflows: UpdateData, GetCurrentState (10y/5y/2y/1y trend analysis). USE WHEN GDP, inflation, unemployment, economic metrics, gas prices, how is the economy, refresh data, FRED, US metrics, economic trends. NOT FOR pathogen surveillance.
Use when writing nodes to Искрон—phenomena, kriyas, vimarshas, contours, and roles. Triggers: “запиши”, “зафиксируй”, “добавь узел”, “создай крию”, “положи в граф”, create phenomenon, add to graph, iskron_add—and always before iskron_add_*, iskron_batch, and iskron_update when appending to a body. Also use when it's unclear which node type, given_as, or modes to choose. Even for a single entry, one wrong type propagates across the entire graph. Distinct from design (paths from goals), weaving (repairing existing structure), and methodology-work (evolving the methodology itself).
When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," or "hypothesis." For tracking implementation, see analytics-tracking.
ADBPG Knowledge Base Management: Create knowledge bases, upload documents, search, Q&A. Triggers: "knowledge base", "document library", "document upload", "knowledge search", "RAG", "Q&A", "embedding", "ADBPG", "AnalyticDB PostgreSQL"
Use when adding or changing a Bagisto import — an Importer class, a file source, the importers registry, the queued import pipeline, or a stuck or failing import job. Trigger phrases include "import", "importer", "data transfer", "CSV", "XLSX", "XML", "bulk upload", "import batch", "queued import", "validate rows".
Data visualization with chart selection, color theory, and annotation best practices. Covers chart types (bar, line, scatter, heatmap), axes rules, and storytelling with data. Use for: charts, graphs, dashboards, reports, presentations, infographics, data stories. Triggers: data visualization, chart, graph, data chart, bar chart, line chart, scatter plot, data viz, visualization, dashboard chart, infographic data, data presentation, chart design, plot, heatmap, pie chart alternative
Django backend patterns for recommendation services (AWS Personalize, Databricks Model Serving, internal microservices) and OpenSearch-backed search/feed endpoints. Covers fan-out orchestration (asyncio.gather, deadline propagation, partial results, async client reuse), external service protection (timeouts, circuit breakers, jittered retry, bulkheads, rate limits), OpenSearch query patterns (search_after, _source filtering, function_score, aliases, routing, bool.filter), result blending (score normalization, MMR, dedup, cold-start), Redis caching (stampede protection, model-versioned keys, two-tier, negative), resilience (partial-response envelope, stale-on-error, graceful degradation), async (sync_to_async, async ORM, uvicorn, contextvars, disconnect cancellation), and DRF response shape (cursor pagination, ETag, throttling). Use when building, reviewing, or refactoring such a Django backend. Triggers even without explicit "scale" cues. Includes 5 scaffolding templates.
How to explore and make sense of PostHog Signals scouts — the scheduled agents that scan a project and write reports into the Signals inbox. Use when a user wants to understand what scouts they have, how each one is behaving, and whether the fleet is actually working. Covers surveying the fleet and its schedules, reading recent scout runs and drilling into a single run's reasoning, inspecting the durable scratchpad memory the fleet has built up, tracing a run to the reports it wrote or edited, reading the follow-up checks still measuring a report, and assessing a scout's health and performance over time (cadence, success rate, report rate, signal-to-noise). Read-only and exploratory — to write or tune a scout, use `authoring-scouts` instead. Trigger on "what are my scouts doing", "how is my <x> scout performing", "show me recent scout runs", "why did this scout find/report nothing", "what has the fleet learned", "explore scout run <id>", "is my scout working".
Macro-driven crypto via Gate-Info and Gate-News MCP. Use this skill whenever macro (CPI, NFP, Fed, rates, payrolls) ties to crypto, calendar, or indicator-price links. Trigger phrases include CPI and BTC, macro today, Fed, NFP, rates. Route: price/technicals → gate-info-coinanalysis or gate-info-trendanalysis; headlines → gate-news-briefing; attribution → gate-news-eventexplain. Tools: info_macro_* (calendar, indicator, summary), news_feed_search_news, info_marketsnapshot_get_market_snapshot.
Agent-callable Google Sheets tools — read and write spreadsheet data as rows or raw cells, manage worksheets and columns, and apply formatting, sorting, and validation. Use when the user mentions Google Sheets or wants to read, add, update, look up, or organize spreadsheet data, even if they don't name Sheets explicitly.
Using the dbt-materialize adapter to manage Materialize streaming pipelines with dbt. Covers materializations (source, source_table, view, materialized_view, sink, table, seed), profile configuration, index creation, blue/green deployments (deploy_init, deploy_promote, deploy_cleanup), cluster management, strict mode, and testing. Use this skill whenever the user asks about writing dbt models for Materialize, configuring dbt profiles for Materialize, running dbt against Materialize, blue/green or zero-downtime deployments with dbt, creating sources or sinks in dbt, troubleshooting dbt-materialize issues, or migrating existing dbt projects to Materialize. Also trigger when the user mentions dbt-materialize, materialized_view materialization, deploy_init, deploy_promote, deploy_await, strict_mode, refresh_interval, retain_history, or partition_by in a dbt context.
Convert an Omni Analytics topic into a Snowflake Semantic View YAML definition. Use this skill whenever someone wants to export Omni metrics to Snowflake, create a Semantic View from an Omni topic, harden BI metrics into the warehouse, or bridge Omni's semantic layer with Snowflake Cortex Analyst.
Ranks and analyzes statement fingerprints using aggregated SQL statistics from crdb_internal.statement_statistics to identify slow, resource-intensive, or error-prone query patterns. Use when investigating historical performance trends, identifying optimization opportunities, or diagnosing recurring slowness without DB Console access.
Analyzes transaction fingerprints using aggregated statistics from crdb_internal.transaction_statistics to identify high-retry transactions, contention patterns, and commit latency issues. Provides historical transaction-level analysis to understand which statement combinations are causing retries, contention, or performance degradation. Use when investigating transaction retry storms, analyzing commit latency trends, or understanding statement composition of problematic transactions without DB Console access.
Drive the Rerun URDF API (rerun.urdf.UrdfTree) to ingest a URDF as a Transform3D layer on a robot recording. Read when logging a robot model, running forward kinematics from joint states, composing a fixed chain for sensor extrinsics, or when the transform tree will not connect from the data alone. Builds on rerun-chunk-processing (stream/lens mechanics) and rerun-data-model (entity paths, timeline, base-vs-layer).
Comprehensive guide for implementing Syncfusion WPF PivotGrid control, a powerful pivot table component for cross-tabulated data analysis. Use this when working with WPF pivot tables, PivotGridControl, or cross-tabulated data scenarios. Covers pivot rows/columns configuration, PivotSchemaDesigner, grouping bar, pivot field list, pivot calculations, filtering, sorting, and data binding for business intelligence applications.
Extract article bodies from blogs, news sites, WeChat public accounts and other web pages using an isolated Chrome DevTools MCP, returning structured content or saving Markdown and remote images. Use when the user asks to extract an article, scrape a page's article body, save it as Markdown, download article images, or debug the article-body selector.
Implement AI Coaching best practices on AnalyticDB for PostgreSQL (ADBPG): Leverage Supabase projects (training data management) + ADBPG instances with vector optimization to build RAG-driven coaching systems that guide users through domain-specific workflows, decision-making, or skill development. Use when: User wants to create Supabase projects (spb-xxx), ADBPG instances (gp-xxx), vector knowledge bases, or RAG-driven coaching systems on ADBPG. Triggers: "Supabase", "ADBPG", "vector database", "knowledge base", "RAG", "AI coaching", "coaching system", "spb-xxx", "gp-xxx"
Audit the health of a PostHog project's data warehouse sources and syncs — find every broken or degraded source connection, sync schema, and webhook channel. Use when the user asks "why are my imports failing?", "what's broken with my sources?", "why is my warehouse data stale?", or wants a one-shot triage of source/sync health before deciding where to dig in. Produces a prioritized report grouped by severity, with recommended next steps. For materialized-view health use `auditing-warehouse-view-health`; for a single failing sync use `diagnosing-failed-warehouse-syncs`.
Builds Nango Functions without a checked-out Nango project by using the Nango /functions compile, dryrun, dryrun status, and deployment APIs with NANGO_SERVER_URL and NANGO_SECRET_KEY. Use when creating, updating, validating, testing, or deploying Nango actions or syncs remotely via API or single-file payloads. This content overlaps with building-nango-functions but adds remote API workflow details, so load this instead of building-nango-functions whenever remote, API, /functions/compile, /functions/dryruns, /functions/deployments, or no local project workflow is indicated.
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.