Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Exploratory data analysis. Use when users upload .csv/.xlsx/.json/.parquet files or request "explore data", "analyze dataset", "EDA", "profile data". Small files get ydata-profiling HTML/JSON reports; large files (over 200MB or 5M rows) get fixed-memory DuckDB/sketch profiling. Also covers near-duplicate row detection, cross-file key overlap ("can these join?"), dataset drift vs a stored baseline, and time-series profiling.
A GEO (generative engine optimization) brand analysis tool. Automatically queries six AI search engines—Doubao, Kimi, DeepSeek, Yuanbao, Qianwen, and Baidu—to analyze brand mentions in AI responses, sentiment, source citations, and competitor comparisons, then generates an interactive HTML report. Use when analyzing a brand’s performance in AI search engines, GEO optimization, AI search brand monitoring, or brand visibility in AI. Trigger phrases: GEO analysis, brand AI search analysis, AI search engine optimization, brand visibility, GEO, geo analyzer
Comprehensive skill for interacting with Grafana's HTTP API to manage dashboards, data sources, folders, alerting, annotations, users, teams, and organizations. Use when Claude needs to (1) Create, read, update, or delete Grafana dashboards, (2) Manage data sources and connections, (3) Configure alerting rules, contact points, and notification policies, (4) Work with folders and permissions, (5) Manage users, teams, and service accounts, (6) Create or query annotations, (7) Execute queries against data sources, or any other Grafana automation task via API.
Author an IndyKite ContX IQ (CIQ) policy plus its Knowledge Query that sets one or more properties on an existing node in the IndyKite Graph (IKG), then run it via `POST /contx-iq/v1/execute`. Use when adding a brand-new property, overwriting an existing one, or attaching property metadata - no node creation, no relationship writes, no deletes.
Author an IndyKite ContX IQ (CIQ) policy and its Knowledge Query to set one or more properties on an existing relationship in the IndyKite Graph (IKG), then run it via `POST /contx-iq/v1/execute`. Use when adding a brand-new property or overwriting an existing one on a relationship that's already in the IKG. No relationship creation, node writes, deletes, or property metadata (relationship properties take none; metadata on node properties is indykite-ciq-add-property)
Author an IndyKite ContX IQ (CIQ) policy plus its Knowledge Query that creates a brand-new node AND links it to one or more existing nodes via new relationships in a single `POST /contx-iq/v1/execute` call. Use when ingesting a new entity that must be wired into the IKG atomically — combines node creation and relationship creation in one operation.
Author an IndyKite ContX IQ (CIQ) policy plus its Knowledge Query that deletes a node, a relationship, or one or more properties from the IndyKite Graph (IKG), then run it via `POST /contx-iq/v1/execute`. Use when removing data through CIQ — three modes (whole node, whole relationship, individual property) sharing the same policy/KQ shape.
Review Kafka schema changes (Avro, Protobuf, JSON Schema) for compatibility and evolution best practices using the Lenses MCP server. Detects breaking changes, missing defaults, schema drift and naming issues. Use when user says "review schema changes", "check schema compatibility", "will this schema break consumers" or asks about schema evolution. Do NOT use for creating new schemas from scratch or registering them in the cluster.
Write, validate and run KubeSense SPL — the piped log query language — via validate-spl and execute-spl. Covers the storage-name field contract that inverts every other KubeSense surface, log_processed attributes, the command and aggregation vocabulary, and why an SPL query can compile and still fail.
Read, write, and manipulate LAS (Log ASCII Standard) well log files for borehole geophysical and petrophysical data. Use when the agent needs to: (1) Read/parse LAS 1.2 or 2.0 files, (2) Extract well headers or curve data, (3) Convert LAS to DataFrame/CSV/Excel, (4) Create new LAS files from arrays, (5) Modify existing LAS files, (6) Handle problematic or malformed LAS files, (7) Batch process multiple well files.
When the user wants to pull local SEO data — SERP results, local pack rankings, business profile data, reviews, citations, audits, geogrid scans, keyword research, AI visibility, competitor analysis, or any local search intelligence. This is the DEFAULT data tool for LocalSEOSkills. Trigger on any data request before considering other tools. Also trigger on "LocalSEOData," "LSD," "run an audit," "check my rankings," "pull reviews," "citation check," "keyword opportunities," "AI visibility," or "geogrid scan."
Expert coding skill for the full MapTiler platform — Cloud REST APIs, MapTiler SDK JS (built on MapLibre GL JS), native mobile SDKs, on-premise infrastructure, and vector tile schemas. USE WHEN the user wants to add a map to a web or mobile app, show locations or routes, display geographic data, build a store locator, create data visualizations on maps, add geocoding or address search, do reverse geocoding, look up elevation, do IP geolocation, fetch weather data, transform coordinates between CRS/EPSG, embed static map images, work with vector tilesets (Planet v4, Buildings, Contours, Outdoor, Ocean, Landcover, Cadastre), write MapLibre style expressions or data-driven styling, render 3D terrain, globe view, or 3D buildings extrusion, use satellite imagery, add markers, popups, heatmaps, or clustering, integrate maps in React, Vue, Svelte, Angular, Next.js, Leaflet, OpenLayers, Cesium, or deck.gl, build native maps on iOS (Swift), Android (Kotlin), Flutter, or React Native, self-host with MapTiler Server or generate tiles with MapTiler Engine CLI, or upload/manage tilesets via the Admin API. Also USE WHEN the user mentions MapLibre GL JS — the SDK extends MapLibre with built-in cloud services, helpers, and session billing.
This skill should be used when the user asks to "use marimo", "create a marimo notebook", "debug a marimo notebook", "inspect cells", "understand reactive execution", "fix marimo errors", "convert from jupyter to marimo", or works with marimo reactive Python notebooks.
Always invoke for training, validating, tuning, benchmarking, or claiming readiness of a predictive model. Covers leakage audits, spatial and grouped splits, metrics, reproducibility, and honest reporting. Invoke especially when spatial dependence, split design, or deployment geography is unknown; uncertainty is a reason to use this skill. Do not trigger for descriptive EDA or non-predictive statistical inference.
Based on the East Money database, it supports natural language queries for global macroeconomic data, covering national economic accounting, price indices, monetary finance, fiscal revenue and expenditure, foreign trade, employment, industrial operation, and many other fields, and fits diverse professional scenarios such as macroeconomic research, market analysis, and policy interpretation. Results include data descriptions and a csv file. Natural language query for macroeconomic data from financial databases, covering national economic accounting, price indices, monetary finance, fiscal revenue and expenditure, foreign trade, employment, industrial operation, and other fields. It supports diverse scenarios including macroeconomic research, market analysis, and policy interpretation.
Use when setting up Node 24+ built-in `node:sqlite` with the loadable `sqlite-vec` extension for vector / RAG storage in TypeScript without `better-sqlite3`, or when debugging vec0 BigInt rowids, vitest hanging on sqlite-vec, `.ts` import errors under `node:sqlite`, or "sqlite extension not loadable". Covers extension loading, vitest incompatibility (use `node --test`), tsconfig flags, and CLI shebang. Trigger on `node:sqlite`, `sqlite-vec`, vec0 / vector storage even when the user does not name better-sqlite3.
Seismology data processing with ObsPy. Helps with reading seismic waveforms, filtering/processing time series, fetching data from FDSN services, and earthquake analysis. Use when the agent needs to: (1) Read seismic data formats (MiniSEED, SAC, GSE2, SEGY), (2) Filter or process waveforms, (3) Fetch data from IRIS/USGS/FDSN services, (4) Search for earthquakes by magnitude/location, (5) Plot seismograms or spectrograms, (6) Remove instrument response, (7) Analyze station metadata.
USE FOR extracting clean, LLM-ready content from one or more web page URLs, powered by Octen. Fetch 1-20 URLs in one call and get markdown/text content plus a page category, page-structure label, and (optionally) query-driven highlights. Use it for reading articles, scraping pages for RAG/grounding, summarization, or fact lookup from known URLs. It can also list the links on a page.
LiDAR and point cloud processing: PDAL pipelines, LAS/LAZ/COPC handling, ground classification, DTM/DSM/CHM generation, canopy and building metrics, and photogrammetric (SfM) point clouds. Use when the primary input is LAS, LAZ, COPC, LiDAR, or an unstructured 3D point cloud. This skill owns vertical datum agreement, co-registration and the vertical-accuracy budget when two acquisitions are differenced with comparability not yet established; once datum, geoid and accuracy are documented, a subsidence or elevation-change question is change-detection's. Route a derived DEM, DTM, DSM or CHM to terrain-hydrology unless point-level classification, comparability, or metrics remain in scope.
When the user wants to plan promotions, optimize trade spending, forecast promotional lift, or manage promotional supply chain. Also use when the user mentions "trade promotions," "promotional forecasting," "TPM," "TPO," "promotional uplift," "feature and display," "markdown optimization," or "promotional calendar." For pricing optimization, see markdown-optimization. For demand forecasting, see demand-forecasting.
Export your entire Prospeo people search to CSV. Build filters in Prospeo's UI, then use this skill to extract every result via the API — even searches over 25K. Handles pagination, rate limiting, deduplication, and state-by-state splitting automatically. Pair with /icp-prompt-builder on a 50-person sample to tune a qualification prompt BEFORE exporting 25K.
Produce an implementable PyTorch or PyTorch Lightning training recipe with dataset handling, optimization, logging, checkpointing, and debugging checks. Use when turning a paper idea into runnable training code — including new experiments, reproductions, fine-tuning setups, scaling recipes, and debugging unstable training.
Use when performing JSON transformations, manipulating nested JSON structures, filtering arrays, extracting values, validating JSON schemas, or composing multi-step JSON operations. This skill provides 60+ schema-driven jq transformations optimized for AI agent discoverability.
Expert in migrating Apache Solr collections to OpenSearch indexes. Translates Solr XML/JSON schemas to OpenSearch mappings and converts Solr syntax (Standard, DisMax, eDisMax) into OpenSearch DSL. Provides sizing for nodes, shards, and JVM heap. Provides guidance auf authentication migration from Solr to OpenSearch. Uses the AWS Knowledge MCP Server for accurate, up-to-date OpenSearch and AWS service information.
Use when writing SpacetimeDB procedures, returning values, making HTTP requests from server code, accessing the database from procedures, calling reducers from procedures, or integrating external APIs. Triggers on: procedure, procedures, HTTP request, return value, external API, AI API, call reducer from procedure.
Predict market/tech/business-model trends and market-entry timing (enter/wait/avoid) by analyzing 2-3 years of signals to forecast 1-2 years ahead; use for questions like market timing, trend trajectory (rising/peaking/declining), adoption curve stage, or what comes next.
Implements Syncfusion Vue DataManager for local/remote binding, CRUD, querying, caching, and middleware. Supports JsonAdaptor, ODataAdaptor, ODataV4Adaptor, UrlAdaptor, WebApiAdaptor, WebMethodAdaptor, RemoteSaveAdaptor, GraphQLAdaptor, CustomDataAdaptor, and CustomAdaptor. Covers Query class, filtering, sorting, paging, grouping, persistence, offline mode, caching, and error handling.
Reactive collection guidance for live queries, optimistic mutations, persistence, sync engines, and framework adapters. Use when a project uses TanStack DB or when the task needs its setup, implementation, debugging, testing, migration, or integration guidance.
Operate and troubleshoot the MT5 tick collection system. HOST MOVED 2026-08-07 - MT5 now runs on the FXView VPS (Windows scheduled tasks, C:\odb-tickrings), NOT <gpu-host>/Linux-Wine/systemd. EA, ring format, and gap-detection reasoning are unchanged. Covers gap detection, restart recovery, and daily ops
Retrieve a country's average applied tariff over time — the MFN rate on all products, or the rate it applies on goods from one partner and/or in one product group — plus the optional US effective tariff rate. Use when the user asks how a country's tariffs have changed, or what it charges another country on average. For one product between two countries, use lookup-bilateral-tariff.
Store and retrieve customer context using Twilio Conversation Memory. Covers Memory Store provisioning, profile management, traits, observations, conversation summaries, and semantic Recall. Use this skill to give AI agents or human agents persistent memory of customer interactions across sessions and channels.
Generate a beautiful dark-mode analytics dashboard for Xiaohongshu (Little Red Book / RED) creator data. Use when the user wants to: (1) create a data dashboard for their Xiaohongshu account, (2) visualize their Xiaohongshu/RED post performance data, (3) analyze their content metrics including impressions, CTR, likes, followers, keyword analysis, etc. Triggers on mentions of "xiaohongshu dashboard", "xiaohongshu analytics", "RED analytics", or similar requests in Chinese like "xiaohongshu kanban", "xiaohongshu shuju fenxi".
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.