Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
A process-based discrete-event simulation framework. Use for modeling queuing systems, supply chains, manufacturing processes, network simulation, project management, and any system where events occur at specific points in time. Load when working with discrete event simulation, process modeling, resource allocation, virtual time, simpy.Environment, simpy.Resource, or event-driven simulation.
Overall diagnosis and competitor benchmarking for Xiaohongshu accounts. Runs a quantitative checkup on one or more Xiaohongshu accounts — scoring eight dimensions: positioning clarity, content verticality, cover consistency, title hook rate, posting cadence, engagement rate, hit rate, and follower conversion efficiency — pinpoints bottlenecks, and gives actionable changes. Triggered when the user says "account diagnosis", "take a look at my account", "my account isn't taking off / isn't gaining followers / traffic is dropping", "profile checkup", "is something wrong with my positioning", "competitor account analysis", "benchmark account breakdown", "why did this creator succeed", or "compare me with competitors", or pastes a Xiaohongshu profile link/screenshot for analysis. Supports two paths: quantitative analysis with data sources (GUAIKEI_API_TOKEN / SOCIALDATAX_API_KEY) and qualitative screenshot-based diagnosis without data sources. It only acts as an analytical advisor — no publishing, no engagement farming, no bulk account creation.
Collecting Xiaohongshu hotspots and judging topic choices. Pull recent high-engagement posts by keyword or niche, and output a hotspot table, trend judgments, and topic suggestions ready to write. Triggered when the user says "Xiaohongshu hotspots", "what's trending on Xiaohongshu", "look up the hits in the XX niche", "Xiaohongshu topic ideas", "find Xiaohongshu material", "is this term hot on Xiaohongshu", "Xiaohongshu trending/hot posts/viral posts", or "help me look at Xiaohongshu data". Also applies when the user names a niche term (e.g. "fat-loss meals", "commuter outfits", "AI tools") and asks "can I write about it". Automatic fallback across multiple data sources: 红狐 API / socialdatax CLI / 怪壳 CLI, and manual fallback via WebSearch when none are configured.
Use when writing SpacetimeDB C# or Unity clients, generated C# bindings, connection setup, subscriptions, cache access, reducer invocation, callbacks, or identity handling. Triggers on: C#, CSharp, Unity, C# SDK, generated C# bindings, Unity SDK, C# subscription, C# reducer call.
Spring Batch for batch processing in Spring Boot 3.x. Covers Job, Step, ItemReader/Processor/Writer, chunk processing, job parameters, restart, skip/retry, partitioning, and monitoring. USE WHEN: user mentions "spring batch", "batch job", "ETL Spring", "ItemReader", "ItemWriter", "chunk processing", "job scheduling Spring" DO NOT USE FOR: real-time processing - use streaming, simple scheduled tasks - use `spring-scheduling` instead
When the user wants to model inventory systems with uncertain demand, optimize safety stock levels, implement (s,S) or (Q,r) policies, or analyze service levels under uncertainty. Also use when the user mentions "stochastic inventory," "probabilistic inventory," "(Q,r) policy," "(s,S) policy," "base stock policy," "safety stock optimization," "service level constraints," "lead time demand distribution," "fill rate calculation," or "inventory with demand uncertainty." For deterministic models, see economic-order-quantity or lot-sizing-problems. For single-period uncertainty, see newsvendor-problem.
When the user wants to optimize under uncertainty, handle probabilistic constraints, or solve stochastic programming problems. Also use when the user mentions "stochastic optimization," "chance constraints," "two-stage stochastic programming," "scenario-based optimization," "robust optimization under uncertainty," "stochastic demand," "uncertainty modeling," or "probabilistic optimization." For deterministic optimization, see optimization-modeling. For robust optimization, see metaheuristic-optimization.
Deep expertise in securing Supabase applications. Covers Row Level Security (RLS) patterns, auth token validation, storage security, multi-tenant isolation. Use when "supabase security, rls policy, row level security, service role key, multi-tenant rls, supabase, security, rls, postgres" mentioned.
Create interactive 3D Circular Charts with Syncfusion ASP.NET Core. Implement pie/donut series, data labels, legends, tooltips, custom styling, titles, empty point handling, and print/export functionality. Use this skill when the user needs to build or configure pie charts, donut charts, circular data visualizations, or charts showing proportional data in ASP.NET Core applications.
Creating and customizing Syncfusion Circular Gauge - a circular data visualization component for displaying numeric values. ALWAYS use this skill when users need to implement circular gauges, display metrics on a circular scale, configure gauge axes, add pointers or ranges, create data visualization gauges, customize gauge appearance, handle user interactions with gauges, or build dashboards with circular gauge components.
Implementing Syncfusion HeatMap Chart component for ASP.NET Core Razor Pages. Use this skill ALWAYS when the user needs to create heat maps to visualize two-dimensional data, customize cells with gradients or fixed colors, configure axes with multiple types, add legends with flexible positioning, bind array or JSON data, enable tooltips and cell selection, create bubble heat maps, or customize appearance and styling. Essential for data visualization, pattern detection, and matrix visualization use cases.
Implement Syncfusion RangeNavigator (Range Selector) in ASP.NET Core applications for interactive data range selection and navigation. Use this skill when user needs to select data ranges, visualize time-series data with interactive sliders, add period selectors, customize range appearance, export range visualizations, or integrate range selection into dashboards and charts.
Build interactive Sankey Chart visualizations showing weighted flows and relationships between categories using nodes and links. Use this skill whenever the user mentions Sankey diagrams, flow visualization, process flows, value flows between categories, node and link styling, or wants to create diagrams that display the magnitude and direction of flows across stages or systems. The Sankey Chart is perfect for visualizing supply chains, energy flows, revenue streams, customer journeys, and data transformations.
Implement Smith Chart visualization for RF and transmission line analysis. Use this skill when building high-frequency circuit applications, impedance/admittance series plots, or transmission line parameter visualizations. Perfect for network analysis dashboards, component testing interfaces, or technical engineering applications requiring Smith chart data representation.
When user needs to create sparklines (compact data visualizations) in ASP.NET Core applications, always use this skill to implement sparkline components, configure chart types (line, column, area, win-loss, pie), bind data, customize appearance, add markers and data labels, enable user interactions (tooltips, track lines), and ensure accessibility compliance immediately.
Implements Syncfusion Flutter Funnel Chart (SfFunnelChart) for proportional and stage-based data visualization in Flutter apps. Use when working with conversion funnels, sales pipelines, or process-stage visualizations. This skill covers series configuration, segment exploding, gap ratio, data labels, legends, tooltips, and customization.
Design and improve human annotation programs for machine-learning training, validation, and evaluation data, including task and label schemas, active acquisition, annotator guidance, calibration, disagreement, adjudication, provenance, and cost-quality stopping. Do not use for general statistical inference, data storage pipelines, model training, or annotation-interface implementation; route those concerns to data-scientist, data-engineering, ml-engineering, or product-design-and-ux.
Track and analyze US government shutdown liquidity impacts by monitoring TGA (Treasury General Account), bank reserves, EFFR, and SOFR data from FRED API. Use when user wants to (1) analyze current or past government shutdown effects on financial markets, (2) track liquidity conditions during fiscal policy disruptions, (3) assess "stealth tightening" effects, (4) compare shutdown episodes across different monetary policy regimes (QE vs QT), or (5) generate liquidity stress reports with historical context. Recommended usage frequency is weekly on Wednesdays after TGA/reserve data releases.
Analyzes medical education content ideas from PDFs/DOCX files to predict viral potential (views, likes, shares, AVD) and provides actionable insights. Use when the user needs to evaluate content ideas for engagement potential, get predictive analytics on video performance, research trending topics in medical/health niches, analyze YouTube comments and audience sentiment, identify knowledge gaps and myths, or prioritize content ideas based on viral likelihood.
Analyze Solana wallets and multichain portfolios with Zerion API. Use for Solana portfolio value, token positions, transaction history, wallet charts, and PnL. Prefer direct REST API integration, with hosted MCP and x402 on Solana as no-key alternatives for agent workflows.
A standalone Skill for crawling, filtering and exporting public WeChat Official Account articles. Use when the user mentions WeChat Official Account, Official Account articles, mp.weixin, wcx, searching Official Accounts, exporting the last N days or a given year of articles, batch crawling, resumable crawling, full-text completion, tutorial article filtering, or saving WeChat article links. Supports Markdown/JSON/CSV, uses wcx to fetch the index and Playwright to extract the body by default; the paid Metaso fallback requires explicit authorization.
This skill should be used when the user asks about "survey design", "questionnaire construction", "Likert scale", "question wording", "response bias", "survey tool", "Google Forms", "Qualtrics", "SurveyMonkey", "Typeform", "pilot testing", "survey distribution", "act as a survey builder", "survey builder mode", "survey instrument", "closed-ended questions", "open-ended questions", "rating scale", "semantic differential", "survey flow", "skip logic", "branching logic", "response rate", "survey fatigue", "questionnaire validation", "pre-test survey", "online survey", "survey analysis", "Cronbach's alpha", "factor analysis", "survey consent form", "demographic questions", or needs expertise in designing, building, distributing, and validating survey instruments. Part of the AlterLab FC Skills collection (Research Methods & Academic Writing department).
This skill helps users extract structured product details from Amazon using a specific ASIN (Amazon Standard Identification Number). Use this skill when the user asks to get Amazon product details by ASIN, lookup Amazon product title and price using ASIN, extract Amazon product ratings and reviews count for a specific ASIN, check Amazon product availability and current price, get Amazon product description and features via ASIN, enrich product catalog with Amazon data using ASIN, monitor Amazon product price changes for specific ASINs, retrieve Amazon product brand and material information, fetch Amazon product images and specifications by ASIN, validate Amazon ASIN and get product metadata.
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
Automated quantitative trading strategy generator. Input a strategy requirement (clear or vague) → in-depth analysis → generate runnable strategy code + backtest validation → automatic optimization. Core innovation: STRATEGY_DESIGN.md serves as the "system blueprint", and AI strictly translates it when generating code rather than improvising. Four entry points: (1) clear strategy requirement → direct analysis (2) vague requirement → diagnosis and recommendation → then analysis (3) existing strategy → optimization and iteration (4) influencer/blogger → internet research → distilled strategy. Trigger words: 「量化策略」「制定策略」「写个策略」「回测」「autostrategy」「策略生成」「量化XX」「XX投资策略」「XX的投资逻辑」. Scenario triggers: 「帮我设计一个均线交叉策略」「我想做一个A股量化策略」「这个策略回测一下」「优化这个策略的回测结果」. Applicable markets: A-shares / HK stocks / US stocks (futures and options not yet supported; to be added gradually in later versions). Persona-style strategies also trigger: 「写一个巴菲特投资策略」「段永平的投资逻辑量化一下」「帮我用索罗斯的反身性做个策略」. Blogger strategies trigger: 「根据XX博主的投资观点做个策略」「按XX大V的思路写个策略」「帮我量化XX的炒股方法」「XX博主的投资逻辑做策略」.
Anti-detect stealth browser automation using Camoufox (Firefox-based, C++-level fingerprint spoofing). Use this skill for ANY browser automation that must avoid bot detection — social media logins, persistent sessions, humanized interaction, or scraping protected sites. Covers 2026-current Camoufox API, known instability warnings, async/sync patterns, persistent context, and humanization config. ALWAYS use this over raw Playwright when stealth is required.
Triage the last N production call logs for a Cekura agent against a set of KPIs / issues / goals, report the call IDs that hit each failure WITH the percentage of overall call logs affected, and distribute the remaining calls into a mutually-exclusive outcome taxonomy (e.g. not-answered / vetted / non-vetted caller-side / non-vetted agent-issue) with per-bucket percentages. Use when the user says "flag call log failures", "analyze the last N calls for issues", "what % of calls have <problem>", "which calls broke and how often", "find failing calls", "give me the breakdown of call outcomes", "what % of answered calls can be improved", or pastes an agent / project ID and lists the problems or KPIs to measure. Applies attribution rules so caller-side endings and recovered calls are NOT counted as agent failures. This is the upstream triage step that feeds `cekura-generate-scenarios` — it does NOT create scenarios.
When the user wants to solve large-scale optimization problems using column generation, decomposition methods, or Dantzig-Wolfe decomposition. Also use when the user mentions "column generation," "master problem," "pricing problem," "cutting stock," "crew scheduling," "vehicle routing with column gen," "branch-and-price," or when the problem has exponentially many variables. For general optimization, see optimization-modeling. For metaheuristics, see metaheuristic-optimization.
Build and deploy the Goldsky Compose bitcoin-oracle example under the user's own account — a cron task that fetches BTC/USD from CoinGecko and writes `(timestamp, price)` as `bytes32` values to an on-chain `PriceOracle` contract via a Compose-managed wallet, appending each price to a durable collection. Triggers on: 'build a bitcoin price oracle', 'BTC/USD oracle onchain', 'push a price feed onchain', 'cron price oracle', 'set up / deploy the bitcoin-oracle example', 'compose price oracle'. Recommends the shared fully-unpermissioned oracle on Base Sepolia so there's nothing to deploy. Scaffolds the example from goldsky-io/documentation-examples, walks CLI install, contract choice (reuse shared / deploy own), wiring, optional GitHub publish, and a log-tailing smoke test. For a custom/novel Compose app that isn't this oracle, use /compose. For debugging an already-deployed app, use /compose-doctor. For manifest/CLI/API field lookups, use /compose-reference.
When the user wants to solve complex scheduling, allocation, or combinatorial problems using constraint programming (CP). Also use when the user mentions "constraint programming," "CP-SAT," "constraint satisfaction," "all-different constraint," "global constraints," "propagation," "search strategies," or when the problem has complex logical constraints, scheduling with disjunctive resources, or allocation problems. For MIP, see optimization-modeling. For metaheuristics, see metaheuristic-optimization.
Count how many independent origins are behind news coverage of a claim, instead of counting URLs. Queries GDELT for matching articles, collapses reprints and wire copy into single origins, and flags publication bursts that indicate syndication. Use when a claim appears to be confirmed by many outlets and you need to know whether that's many sources or one source many times.
Create interactive data visualizations using d3.js. Use this skill when creating custom charts, graphs, network diagrams, geographic visualizations, or any complex SVG-based data visualization that requires fine-grained control over visual elements, transitions, or interactions. Use it for bespoke visualizations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.
Interpret the three core financial statements (income statement, balance sheet, cash flow statement) to assess business health and performance. Use this skill when the user needs to read financial statements, understand profitability vs cash flow, evaluate a company's financial position, or prepare for investor/board meetings — even if they say 'explain these financials', 'are we making money', 'read this annual report', or 'what do these numbers mean'.
Database performance optimization, schema design, query analysis, and connection management across PostgreSQL, MySQL, MongoDB, and SQLite with ORM integration. Use this skill for queries, indexes, connection pooling, transactions, and database architecture decisions.
Execute database migrations across ORMs and platforms with zero-downtime strategies, data transformation, and rollback procedures. Use when migrating databases, changing schemas, performing data transformations, or implementing zero-downtime deployment strategies.
Analyse Datadog observability data including metrics, logs, monitors, incidents, SLOs, APM traces, RUM, security signals, and more. Use when asked to investigate infrastructure health, query metrics, search logs, check monitors, diagnose errors, or analyse any Datadog data.
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.