Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Analyze one or more cycling, running, or hiking FIT/KML activity tracks, generate evidence-based single or aggregate reports, open the bundled local Ride Relief report page when the environment supports it, enrich results with user-confirmed public location context, and create shareable PNG or H.264 MP4 route stories on request. Use whenever a user wants to analyze, compare, visualize, or export .fit or .kml activities, including requests that mention a workout but do not yet include track files.
Google Ads data analysis and reporting via google-ads-open-cli. Use when the user wants to check Google Ads performance, pull campaign/ad group/keyword stats, explore account structure, audit conversions, or run custom GAQL queries. Triggers: "Google Ads", "ad performance", "campaign stats", "GAQL", "ad spend", "keyword report", "search terms", "conversion tracking", "impression share", "ad account".
Turn sales history and current stock counts into reorder points, order quantities, and a this-week purchase list -- so a product business stops stocking out of winners and stops burying cash in losers. Handles seasonality, supplier lead times, and the dead-stock cleanup.
Find out which clients and jobs actually make money -- allocate real costs (labor hours, materials, subs, overhead) against what each job billed, and rank every client by true margin. Most service businesses discover their biggest client is their least profitable.
Use for TikTok Shop market data: trending products, top creators, shop/product sales and revenue, viral videos, livestreams, category rankings, product selection, creator commerce, shop/product sales, viral videos, livestream commerce, and TikTok Shop data. Answers come from KaloData via the bundled `kalo` CLI (Python, zero install). Use whenever the user researches TikTok Shop, even if they never say "kalodata"
Kuaishou content search tool. Enter a keyword to find trending Kuaishou posts (broad index), with multi-dimensional filtering by sort order; titles, authors, play counts, likes, comments and favorites are all visible at a glance, and a link click opens the detail page. Video details and captions can also be extracted. Use when the user needs to search Kuaishou posts, find trending Kuaishou content, or look up Kuaishou post data. Trigger words: Kuaishou search, Kuaishou posts, Kuaishou trending, Kuaishou video lookup, search Kuaishou.
Uses EHunt Temu category search (gateway route `ehunt/temu/temuCategorySearch`) to search the EHunt Temu category data synced to the local database by keyword for category Chinese names, English names, and category IDs, which are used as the category IDs for product/shop filtering. Triggered when the user mentions EHunt Temu categories, Temu category id, Temu category tree, Temu backend categories, temu categories, syncing Temu categories with syncTemuCategory, then looking up categories, or Temu category search. Even if the user does not mention EHunt, this skill should still be triggered when searching the locally synced Temu category database by keyword for category IDs.
Discovers, enriches, and scores local businesses in any neighborhood using Nimble Web Search Agents (WSAs) and web data. Returns a structured, ranked list with confidence scores, reviews, social presence, and an interactive map. Use this skill when the user asks about local businesses, places, or neighborhood discovery. Common triggers: "find all coffee shops in", "map every bar in", "local businesses in", "discover gyms near", "what restaurants are in", "neighborhood guide for", "local places in", "find places near", "list all [business type] in [area]", "best [type] near [location]", "build a neighborhood guide", "local place search". Requires the Nimble CLI (nimble extract:templates run, nimble search, nimble extract) for live web data via WSAs and fallback search. Do NOT use for competitor analysis or monitoring (use competitor-intel), company research or deep dives (use company-deep-dive), general web search or extraction (use nimble-web-expert).
Full-dimension log analysis skill. Automatically identifies log types (Java application / MySQL Binlog / Nginx / Trace / alerting), extracts key entities (IP, thread_id, trace_id, user, table names, etc.), and performs root cause localization, alert analysis, and anomaly insights. Supports 100M+ large files. Trigger words: analyze logs, log troubleshooting, root cause localization, alert analysis, anomaly analysis.
Options trading strategy analysis and simulation tool. Provides theoretical pricing using the Black-Scholes model, Greeks calculations, strategy P/L simulations, and risk management guidance. Use when a user requests options strategy analysis, covered calls, protective puts, spreads, iron condors, earnings plays, or options risk management. Includes volatility analysis, position sizing, and earnings-based strategy recommendations. Educational focus with practical trade simulation.
Statistical arbitrage tool for identifying and analyzing pair trading opportunities. Detects cointegrated stock pairs within sectors, analyzes spread behavior, calculates z-scores, and provides entry/exit recommendations for market-neutral strategies. Use when the user requests pair trading opportunities, statistical arbitrage screening, mean-reversion strategies, or market-neutral portfolio construction. Supports correlation analysis, cointegration testing, and spread backtesting.
A/B experiment design skill. Starting from the experiment goal, output a complete experiment plan (hypothesis, groups, metric system, sample size estimation, stop-loss rules, decision rules). Triggers: the user mentions "A/B testing", "AB experiment", "experiment design", "controlled experiment", "traffic-split experiment", "gradual rollout plan", "experiment plan", "sample size calculation", "significance testing", "experiment evaluation", "p-value", "confidence interval", "MDE", "statistical power", "experiment duration", "stop-loss rules", and similar keywords. Also applies when: the user provides experiment goals / changeable points / data scale / duration constraints and requires an experiment plan; the user asks to evaluate whether an existing experiment design is reasonable; the user asks to define experiment decision criteria and decision rules. Typical input: experiment goal + changeable points + current data scale + acceptable experiment duration. Not suitable for: pure data analysis (use pm-analytics), pure tracking design (use tracking-spec-writer), pure PRD writing (use pm-prd-writer).
Oxylabs proxy networks: Residential, Mobile, shared Datacenter/ISP, and Dedicated Datacenter/ISP proxies with geo-targeting, IP rotation, session persistence, and port-based sticky IPs. Use when routing traffic through proxies, building scrapers with proxy auth, rotating or sticky sessions, whitelisting IPs, or accessing geo-restricted content.
This skill should be used when analyzing sector and industry performance charts to assess market positioning and rotation patterns. Use this skill when the user provides performance chart images (1-week or 1-month timeframes) for sectors or industries and requests market cycle assessment, sector rotation analysis, or strategic positioning recommendations based on performance data. All analysis and output are conducted in English.
Creator-facing social media analytics dashboard in a single HTML file. A platform switcher (X / LinkedIn / YouTube / Instagram), a row of KPI cards (followers, engagement rate, likes, reposts), a follower-growth chart, a "top post this week" preview, and a trending topics / top comments side panel. Use when the brief mentions a "social media dashboard", "creator analytics", "social analytics", or names specific platforms (X, Twitter, LinkedIn, YouTube, Instagram, TikTok) together with metrics like followers, engagement, likes, reposts.
Use when a Jackrabbit Oak/AEM JCR query is slow, logs a traversal warning, or you're adding/changing a query and need to check or update its property/Lucene index definition so the query is answered by the index instead of in-memory filtering or sorting.
TMDL and PBIR validation, linting, and pre-deployment testing. PROACTIVELY activate for: (1) validating TMDL syntax before deploy, (2) validating PBIR schema, (3) catching TmdlFormatException / TmdlSerializationException early, (4) Best Practice Analyzer (BPA) rules and BPA CLI, (5) Tabular Editor BPA scripting, (6) PBI-Inspector / PBI-InspectorV2 / Fab Inspector, (7) PBIR JSON schema validation, (8) pre-deployment validation in CI, (9) fabric-cicd parameter.yml validation, (10) catching breaking changes between TMDL versions. Provides: BPA rule library, validation CLI commands, CI integration for validation, error catalog (TmdlFormatException, etc.), and a pre-deploy validation playbook.
Manages Fabric Variable Library items, including definitions, libraryVariables and valueSets overrides. Covers which consumers can reference a variable and with what syntax -- pipelines, notebooks via notebookutils variableLibrary, Dataflow Gen2, Copy Jobs, shortcuts, UDFs and Plan items -- the active value set per workspace or deployment stage, and Git serialization for CI/CD.
Build a 13-week rolling cash flow forecast from bank exports, AR aging, AP bills, payroll, and recurring commitments -- the report that tells a small business whether it survives the quarter. Flags the crunch weeks early enough to act.
Track and analyze cross-border capital flows between mainland China and Hong Kong via Stock Connect (沪港通/深港通). Monitor northbound (北向资金) and southbound (南向资金) flows, identify trending stocks, and analyze institutional positioning. Use when user asks about 北向资金, 南向资金, 外资动向, Stock Connect flows, or cross-border investment trends.
Data analysis tool for Excel, CSV, Word, PDF, TXT, Markdown files. Use when user needs to analyze, summarize, or compare data from multiple files. Supports folder scanning, data aggregation, statistics, report generation in Markdown/Excel/Word/PDF. Multi-language support. 数据分析、文件夹分析、Excel分析。
Build a dense, data-heavy screen - an analytics console or a trading terminal - with real charts drawn from tokens: candlestick, volume, depth, stacked area, waterfall, scatter, correlation matrix, donut, gauge, sparklines, heatmaps and order books. Use when the request is a dashboard, terminal, monitoring view, data console, or any screen whose job is to show many numbers at once. Covers the layout sequence, the SVG geometry, the accessibility contract per chart type, and the contrast traps that only appear in dark mode.
Microsoft Fabric integration with Power BI semantic models. PROACTIVELY activate for: (1) Microsoft Fabric platform tasks, (2) Direct Lake mode and OneLake connectivity, (3) Fabric lakehouse, warehouse, KQL Database, Eventstream, Data Activator, (4) Dataflow Gen2 ETL, (5) Fabric notebooks (PySpark, Spark SQL, semantic-link), (6) Fabric workspace and capacity (F-SKU) management, (7) delta tables and V-Order optimization, (8) medallion architecture (bronze/silver/gold), (9) Semantic Link / sempy / semantic-link-labs Python workflows, (10) Direct Lake fallback rules and mixed mode. Provides: Direct Lake setup, Fabric capacity sizing, lakehouse-to-semantic-model patterns, sempy/semantic-link-labs recipes, and end-to-end medallion architecture templates.
When the user wants to analyze local ranking data using geogrid scans, interpret map pack rankings across a geographic area, or understand ARP/ATRP/SoLV metrics. Also use when the user mentions "geogrid," "rank grid," "local rank tracking," "Local Falcon," "grid scan," "map pack rankings," "ranking heatmap," or "where am I ranking." For broader local audit, see local-seo-audit. For competitor analysis, see local-competitor-analysis.
Filter independent-site Shopify products by multiple dimensions via EHunt Shopify product query (gateway route `ehunt/shopify/productQuery`) (keyword/URL, price, weekly sales, listing time, Facebook ads, competition level, supply availability, shipping country, etc.). Trigger when the user mentions EHunt Shopify product, Shopify product selection, independent-site product selection, Shopify bestsellers, Shopify dropshipping, independent-site product listing, Facebook ad products, Shopify product query, or shopify items. Even if the user does not write EHunt, as long as they are searching products, checking weekly sales/revenue/competition level, or filtering products on Shopify independent sites, this skill should also be triggered.
Filter independent-site Shopify stores by multiple dimensions via EHunt Shopify store query (gateway route `ehunt/shopify/storeQuery`) (store name/domain, country, years since creation, product count, ad count, monthly visits, monthly orders, social media followers, etc.). Trigger when the user mentions EHunt Shopify store, Shopify store analysis, independent-site stores, Shopify seller, independent-site competitor stores, Shopify monthly visits, independent-site ad library, shopify stores, or Shopify store query. Even if the user does not write EHunt, as long as they are finding stores, filtering store data, or analyzing store performance on Shopify independent sites, this skill should also be triggered.
Filter Temu products by multiple dimensions via EHunt Temu product query (gateway route `ehunt/temu/productQuery`) (keyword/product ID/store ID, front-end and back-end categories, price, rating, reviews, total/weekly/daily sales, listing time, fully managed/semi-managed, semi-managed region, tags, etc.). Trigger when the user mentions EHunt Temu product, Temu product selection, Pinduoduo cross-border, Temu bestsellers, Temu semi-managed, fully managed products, Temu product query, or temu items. Even if the user does not write EHunt, as long as they are searching products, checking sales/rating/price, or filtering products on Temu, this skill should also be triggered.
Filter Temu stores by multiple dimensions via EHunt Temu store query (gateway route `ehunt/temu/storeQuery`) (store name/ID, country site, back-end category, fully managed/semi-managed, total/weekly/monthly sales and revenue, rating, reviews, followers, product count, store opening time, etc.). Trigger when the user mentions EHunt Temu store, Temu store analysis, Temu seller, Temu store rankings, Temu semi-managed stores, Temu revenue, temu stores, or Temu store query. Even if the user does not write EHunt, as long as they are finding stores, filtering store data, or analyzing store performance on Temu, this skill should also be triggered.
Analyze microbiome and metagenomics data using MGnify, GTDB, ENA, and literature tools. Search studies by biome/keyword, retrieve taxonomic profiles and functional annotations, classify genomes with GTDB taxonomy, and find related publications. Use for human gut microbiome, soil/ocean metagenomics, and environmental microbiology research.
Build and query managed search indexes (Stores) using the Mixedbread Python and TypeScript SDKs. Use when creating knowledge bases, uploading documents, performing semantic or vector search, asking questions over documents, using agentic multi-step retrieval, combining store search with web results, filtering by metadata, reranking, or discovering metadata facets.
Data analysis domain (data): read-only statistical reports such as payment bills and bill summaries, traffic flow curves, top license plate distribution, real-time on-site statistics, daily vehicle exits/transaction counts, parking space usage (including echart heatmaps), and parking duration distribution. Use when the user wants parking lot business reports, trend analysis, or data health checks (aggregate statistics rather than per-vehicle details). Note: the three statistical interfaces for parking spaces/duration/echart are marked write in the platform contract and require --yes to call; for per-vehicle details/on-site vehicles see the parking domain (openydt-record).
Parking record domain (parking): query on-site/entry-exit/parking details/historical payments/arrears, perform supplementary entry correction/vehicle locking/self-service entry and exit, and semantically analyze business traffic, parking duration, evasion and passage types by exit events. Use when the user requests the above record-level tasks; for real-time fee queries and payments use openydt-billing, and for platform aggregate statistics use openydt-data.
Guides Oracle database development including SQL, PL/SQL stored procedures, triggers, EXPLAIN PLAN optimization, AWR analysis, RMAN backup, RAC clustering, and Data Guard. Use when the user needs to write Oracle SQL, create PL/SQL procedures, tune query performance, or manage Oracle database administration.
Configure DigitalOcean Managed Postgres with bindable variables or schema isolation. Use when setting up databases, creating users, managing permissions, configuring multi-tenant schemas, or troubleshooting database connectivity on App Platform.
Methodology playbook for analyzing tokenized real-world assets (RWA) on Allium—tokenized treasuries, money market funds, tokenized equities/pre-IPO stocks, commodities, and private credit. Use whenever a question touches RWA supply, AUM, market cap, holders, mint/burn activity, or classification—even if the user just says "tokenized treasuries," "BUIDL," "tokenized stocks," "money market fund AUM growth," or names a specific RWA product/issuer. Covers aggregation mistakes, classification pitfalls, and data-quality exclusions that commonly arise in real RWA questions before writing SQL
Designs, weight, and tune a lead scoring model for your sales funnel. Use when scores don't predict conversion, MQL/SQL threshold feels arbitrary, reps ignoring lead scores because they're inaccurate, too many unqualified leads passing to sales, or not sure which signals actually matter. Do NOT use for reading existing buying signals (use /sales-intent), building prospect lists (use /sales-prospect-list), or marketing-to-sales handoff process design (use /revops).
Record and analyze post-trade outcomes for signals generated by edge pipeline and other skills. Track false positives, missed opportunities, and regime mismatches. Feed results back to edge-signal-aggregator weights and skill improvement backlog
Methodology playbook for analyzing stablecoin volume, supply, holders, and geographic usage on Allium — USDC, USDT, DAI, USDS, RLUSD, USDG, JPYC, and other fiat/crypto/algorithmic-backed stablecoins. Use whenever a question touches stablecoin transfer volume, circulating supply, wallet/holder counts, geographic breakdowns, or cross-chain deployments—even if the user just names a specific stablecoin, asks for "adoption" or "usage" figures, or asks to compare volume with a chart/number they already have. Covers raw vs. adjusted volume, chain-specific double-counting mechanics, and address/case-sensitivity pitfalls that commonly arise before writing SQL
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.