Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
MOEX ISS and ISS+ mechanics for raw REST endpoints, public iss.moex.com access, authenticated apim.moex.com access, output formats, iss.only, iss.json, start pagination by returned row count, response block normalization, discovery and history routes, calendars, boardgroups, and websocket/STOMP concepts.
Use when discovering niche signals, auditing ICP or won/lost evidence, rescoring accounts, or building account and lead scoring Plays. Triggers on fit scoring, engagement scoring, external proxies, and scoring leakage. Skip pure outreach copy or contributor skill installation tasks.
Powerful web scraping, crawling, and data extraction with stealth anti-bot bypass (Cloudflare Turnstile, CAPTCHAs). Use when: (1) scraping websites that block normal requests, (2) extracting structured data from web pages, (3) crawling multiple pages with concurrency, (4) taking screenshots of web pages, (5) extracting links, (6) any web scraping task that needs stealth/anti-detection, (7) user asks to scrape/crawl/extract from URLs, (8) need to bypass Cloudflare or other bot protection. Supports CSS/XPath selectors, adaptive element tracking (survives site redesigns), multi-session spiders, pause/resume crawls, proxy rotation, and async operations. Powered by MyClaw.ai.
Get PostHog data into a canvas correctly: the host-injected `ph` SDK (loadInsight, query, capture, state, connectors, openExternal, navigate), the data hierarchy (saved insights first, typed query nodes second, inline HogQL last), verifiability (insight-backed metrics link their saved insight in PostHog; ad-hoc queries expose the exact query that ran), per-insight-type result shapes, progressive per-query loading, date-range wiring, live third-party data through the viewer's own connections (ph.connectors), and event capture from a canvas. Use whenever a canvas shows metrics, charts, tables, any PostHog data, or data from GitHub or an MCP server, or needs to send analytics events.
Open-source cheminformatics and machine learning toolkit for drug discovery, molecular manipulation, and chemical property calculation. RDKit handles SMILES, molecular fingerprints, substructure searching, 3D conformer generation, pharmacophore modeling, and QSAR. Use when working with chemical structures, drug-like properties, molecular similarity, virtual screening, or computational chemistry workflows.
Ingest .mp4 video into Rerun chunk streams with rerun.experimental.Mp4Reader. Read when converting video into a VideoStream, choosing stream vs asset mode, transcoding (B-frames, output codec, GOP size) through FFmpeg, or aligning video PTS onto a recording's wall-clock timeline. Builds on rerun-chunk-processing (stream mechanics) and rerun-data-model (where the video belongs in the recording).
Guides users through implementing and optimizing ScyllaDB Vector Search for semantic similarity, RAG, and similar use cases. Use this skill when users need to store and query embeddings, build vector indexes (HNSW), run approximate nearest neighbour (ANN) queries, apply filtering (global/local secondary indexes), configure quantization, integrate with LLM frameworks (e.g. LangChain), or run Vector Search locally with Docker for testing. Schema design outside the vector column goes to scylladb-data-modeling. Triggers on "vector", "embeddings", "similarity search", "ANN", "nearest neighbor", "RAG", "semantic search", "recommendation system", "vector index", "HNSW", "vector-store"
Connect an arbitrary REST API to the PostHog data warehouse as a Custom source by authoring a JSON manifest, with no per-source code. Use when the user points at an API that has no built-in PostHog connector — "import data from this REST API", "sync my internal API", "connect this API from its docs", "build a custom data warehouse source" — and gives a docs URL or a natural-language description of the endpoints. Walks through drafting the RESTAPIConfig manifest (auth — bearer, API key, HTTP basic, or OAuth2 client credentials / refresh token — pagination, record path, incremental cursor, parent/child fan-out), validating it, test-reading live rows to verify the field mappings, and creating the source. If the API already has a native PostHog connector, use setting-up-a-data-warehouse-source instead — this skill checks the connector registry first and only handles APIs with no native connector.
Turn a data file (CSV/TSV/TXT/XLSX/XLS/JSON) into standalone interactive ECharts HTML charts - 26 chart types, 3 themes, fully offline with no CDN. Each chart ships with an embedded fact sheet (plot_stats plus data_preview) whose numbers are the only values an agent may quote in its caption: this is chart generation with traceable facts, not data analysis or report writing. TRIGGER: user supplies or points to a tabular data file and wants a chart; asks to 画图/出图/可视化/生成图表/generate a chart/make a graph; wants a table rendered as an interactive HTML chart. DO-NOT-TRIGGER: wants a written report, narrative analysis or slide deck; no data file is supplied; geo/map rendering; dashboards needing a backend; images, audio, video or other non-tabular content.
Monthly social media performance review for SMBs. Analyses post-level and account-level data from Instagram, LinkedIn, Facebook, or TikTok. Identifies what worked, what didn't, and why. Produces a client-ready report and specific recommendations that feed back into the content calendar. Accepts CSV exports, screenshots, or manual data input.
Use when migrating from SpacetimeDB 1.0 to 2.0 or fixing code affected by 2.0 breaking changes. Covers reducer callbacks, event tables, event type changes, subscription API, table accessor naming, database-name connections, `sender()` method, update methods, scheduled functions, private codegen, light mode, `CallReducerFlags`, and confirmed reads. Triggers on: upgrade, migrate, 1.0, 2.0, breaking changes.
SQL injection screening for host code (MoonBit / TS / Rust) plus secretlint setup notes. Flags single-line template-literal or string-concat SQL builders, regardless of value source — the scanner is line-based and does NOT trace data flow, so a clean scan is not proof of safety (multi-line template literals are missed) and every hit needs a manual review or an explicit `// sql-security: ok` opt-out.
Interactive naming convention standardization for TMDL-based Power BI semantic models. Automatically invoke when the user asks to "standardize naming conventions", "fix naming conventions", "clean up model names", "apply naming standards", "audit naming", "make names human readable", "rename fields", "fix abbreviations in model", or mentions renaming measures, columns, or tables for consistency across a model.
Fast, cheap market research using LLM-generated synthetic survey responses with Semantic Similarity Rating (SSR). Runs purchase intent, concept tests, and pricing research in minutes instead of weeks, at $0 per respondent. Based on PyMC Labs' validated methodology (90% correlation with real humans across 57 surveys). Triggers: synthetic research, market research, survey, purchase intent, concept test, consumer research, SSR, synthetic survey, product validation, pricing research, Likert scale.
The Stock Screener. Checks a list of companies against the user's own rules (revenue growth, margins, EPS, P/E, earnings yield, sector, anything in the metrics file), says exactly which rule each company passes or fails and by how much, and ranks the ones that pass into a shortlist. Reads the metrics /trader-analyst writes from SEC filings, or any CSV. Use when the user says "screen for stocks", "find me companies that", "filter my watchlist", "which of these pass my rules", "shortlist candidates", "rank these stocks", or "growing companies under 30 times earnings".
Converts engineering analytics (PR / CI) data into saved PostHog insights, dashboards, and subscriptions, and explains how to query the product data directly with SQL. Covers discovering per-team GitHub warehouse tables via engineering-analytics-sources, replicating curated column semantics in HogQL, reading exposed engineering_analytics_* warehouse views where product logic is involved (CI cost, fingerprinted failure lines, commit attribution), saving queries with insight-create, and scheduling delivery with subscriptions-create. Use when asked to "save this as an insight", "put CI health / merge times on a dashboard", "email me PR throughput weekly", "chart CI cost", "track time to first review", "subscribe to these numbers", "alert on CI success rate", or "what data/tables/views does engineering analytics read". For ad-hoc CI and merge questions use diagnosing-ci-and-merge-bottlenecks; to investigate one specific CI failure use investigating-ci-failures.
Synthesises user interview transcripts into structured research findings. Use when asked to analyse interview notes, synthesise qualitative research, identify themes from interviews, or turn raw interview data into actionable product insights. Produces a themed synthesis with supporting quotes per theme, 'so what' implications, and recommended next steps. For mixed sources beyond interviews (surveys, tickets, feedback) use user-research-synthesis instead.
Render inline interactive visuals — SVG diagrams, HTML widgets, charts, and explainers — directly in the conversation. Use this skill whenever the user asks to visualize, diagram, chart, illustrate, or explain something visually, or when an explanation would genuinely benefit from a spatial/interactive diagram rather than text. Also triggers for: flowcharts, architecture diagrams, data visualizations, interactive explainers, comparison layouts, UI mockups, and any request containing 'show me', 'draw', 'map out', 'visualize', or 'diagram'. Even when the user doesn't explicitly ask for a visual, use this skill proactively when the topic has spatial, sequential, or systemic relationships that a diagram would clarify better than prose.
Write Streamlit app source code that runs well in a PostHog sandbox — the posthog_apps.query() bridge for reading PostHog data, the packages baked into the sandbox image, caching and session state across Streamlit reruns, layout and chart patterns, and the app.py entry point with any helper modules and data files bundled beside it. Use when authoring or debugging the Python source of a PostHog Streamlit app, when a query inside an app fails, or when asked to "write a streamlit app that shows PostHog data".
A search tool for trending Xiaohongshu posts. Search by keyword to retrieve popular content data, then rank and recommend posts based on data scores, helping creators discover trends and find inspiration. Run only in the main Agent; do not delegate to subagents
Alibaba Cloud Realtime Compute for Flink expert assistant. Use when you need expert assistance with Alibaba Cloud Realtime Compute for Flink (阿里云实时计算 Flink 版), including product parameters, engine versions, billing information, general troubleshooting, Flink SQL generation (DDL/pipeline/risk-monitoring scenarios), and explicit file output requests. Covers: parameter/version/billing queries, problem diagnosis, SQL generation, file output.
Design and audit analytics event taxonomies for product funnels, SaaS, mobile apps, games, web apps, desktop utilities, marketplaces, notifications, payments, support, and launches. Use when defining events, properties, naming, identity, funnels, cohorts, attribution, guardrail metrics, dashboards, or analytics quality rules.
Chart GrowthBook product data, build Analytics dashboards, manage the metric catalog, or query the warehouse directly — run Product Analytics explorations, save charts together on a dashboard, search metrics and fact tables, create fact metrics and their fact tables, or fall back to ad-hoc SQL. Use for "show me signups by country", "chart daily active users", "how many orders last week", "build me a dashboard", "put these metrics on a dashboard", "add a chart to this dashboard", "set up reporting for X", "find our revenue metric", "what fact tables exist", "create a metric", "define a metric on the orders table", "what tables contain user data", "run a SQL query", or any "show me / chart / plot / how many" question about product data. For an A/B test's results or choosing experiment metrics, use experiments. For feature flags, use feature-flags. For first-time API key configuration, use gb-setup.
Use this skill any time the user wants financial analysis, earnings research, or investment-related reports. This includes: earnings call summaries, quarterly financial analysis, stock research, equity research reports, financial due diligence, company valuations, DCF models, balance sheet analysis, income statement breakdowns, cash flow analysis, SEC filing summaries, investor memos, portfolio analysis, IPO analysis, M&A research, and credit analysis. Also trigger when: user says 分析财报, 做个估值, 股票研究, 财务尽调, 现金流分析, 收入分析, 季度财务分析. If financial research or analysis is needed, use this skill.
Design backup, restore, sync, export, recovery, data durability, cloud/local storage, versioning, migration, deletion, and disaster recovery systems. Use when building or reviewing backup strategy for SaaS, mobile apps, desktop utilities, games, user-generated content, account data, or business-critical workflows.
Builds geocoding workflows in CARTO that convert street addresses or place names into geographic coordinates. Triggers when the user mentions geocoding, address to coordinates, address resolution, geolocate addresses, "add geometry from addresses", lat/lon from address, place name to point, address matching, forward geocoding, converting addresses to points, or has tabular data with address columns but no spatial geometry column and needs to create one.
Builds Geographically Weighted Regression (GWR) workflows in CARTO. Triggers when the user mentions GWR, geographically weighted regression, spatially varying relationships, local regression, local coefficients, spatial regression, "what drives X in different areas", "why do prices vary spatially", "local factors affecting Y", varying coefficients, coefficient maps, spatial non-stationarity, or wants to model how the relationship between a dependent variable and predictors changes across geography. Produces per-cell regression coefficients that reveal how predictor importance shifts from place to place.
Preview an existing saved CARTO Builder map inline in the chat via the CARTO MCP server — resolve the map with read_maps (by name or search), then render it with view_map by map ID. Use whenever the user references a saved Builder map — by URL, by ID, or by name. Renders a lightweight read-only preview (layers, basemap, viewport, popups, legend). Widgets, SQL parameters, map description, and other Builder-only features are NOT included; the user can click "Open in Builder" for the full experience. Triggers on "show me the X map", "open the Y map", "preview the Z map", and inline previews of a freshly-created map. Distinct from carto-create-builder-maps (authoring), carto-render-inline-map (ad-hoc deck.gl spec), and carto-develop-app (developer app).
Render an ad-hoc interactive map inline in the chat from a deck.gl declarative spec via the CARTO MCP server's view_map tool. Use whenever the user asks to map, visualize, or show the geographic distribution of points, polygons, hexagons, quadbins, clusters, density (heatmaps), or raster — and the map is exploratory or throwaway, not meant to be saved as a permanent CARTO Builder map. Triggers on "show me X on a map", "visualize Y", "make a heatmap of Z", "render the points/clusters/raster of W". Distinct from carto-create-builder-maps (authoring permanent maps), carto-preview-builder-map (loading an existing saved Builder map), and carto-develop-app (writing a from-scratch deck.gl app in TypeScript / JavaScript).
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.