Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Other
Market signals → daily digest delivered before market open. Scans watchlist tickers for regime changes, technical setups, options flow anomalies, and IBKR position health — then delivers a prioritized action list. No IBKR distraction during 50-call BDR days. Use when: 'market digest', 'trading alerts', 'pre-market scan', 'watchlist check', 'what's setting up', 'trading morning brief', 'market open prep'.
Get current weather and forecasts via wttr.in or Open-Meteo. Use when: user asks about weather, temperature, or forecasts for any location. NOT for: historical weather data, severe weather alerts, or detailed meteorological analysis. No API key needed.
Reasoning skill for healthcare claims billing rules and fraud detection logic. Use when the user asks about CMS billing rules, place of service codes, global surgery periods, modifier usage (25 59 76 77), NCCI edit logic, column 1 column 2 code pairs, mutually exclusive procedures, modifier indicators, fraud waste and abuse patterns, E&M upcoding, unbundling, phantom billing, impossible day detection, coding error versus fraud distinction, FWA investigation methodology, or claims audit logic. Triggers include "CMS billing rules", "NCCI edits", "modifier 25", "modifier 59", "global surgery period", "upcoding", "unbundling", "phantom billing", "impossible day", "FWA", "fraud waste abuse", "coding error vs fraud", "claims audit", "billing compliance", "E&M level selection".
Reviews the legality of draft contracts and business conduct, comparing against regulations such as civil law, labor standards law, personal data protection law and company law, flagging high-, medium- and low-risk clauses and offering amendment suggestions.
Production-grade AI trading agent for cryptocurrency markets with advanced mathematical modeling, multi-layer validation, probabilistic analysis, and zero-hallucination tolerance. Implements Bayesian inference, Monte Carlo simulations, advanced risk metrics (VaR, CVaR, Sharpe), chart pattern recognition, and comprehensive cross-verification for real-world trading application.
Use this skill for Elfa API crypto social intelligence and Auto condition-engine workflows: API v3 events, positions and rankings (crypto, equities), trending tokens, narratives, mentions, smart account stats, token news, trending contract addresses, AI market chat (JSON and SSE streaming), curl/code snippets, automated alerts, EQL queries, trigger pipelines, and agent workflows that react to market conditions. Auto can trigger on X/Twitter posts, Telegram channels, events (news), one trader's calls, token or stock mindshare, SEC filings, Kalshi and Polymarket prediction markets, funding rates, liquidation cascades, the Fear & Greed index, and X follow-graph moves (new followers, new follows, accounts converging); re-fire recurring plans via `repeat`, run calendar schedules via `cron.schedule`, and monitor crypto plus HIP-3 assets (equities, indices, commodities, FX, pre-IPO — 24/7). Supports API-key calls and x402 pay-per-request USDC on Base, Arbitrum, Polygon, Avalanche, or Solana
Find roll options for existing short positions OR find best covered call/put to open against long stock. Use when user asks about rolling shorts, finding roll candidates, writing covered calls, or managing option positions. Requires TWS or IB Gateway running locally.
Search the JLCPCB electronic components database (~7 million parts) for hardware/electronics projects. Use when the user needs to: (1) Find electronic components (resistors, capacitors, inductors, ICs, connectors, diodes, transistors, MOSFETs, op-amps, microcontrollers, sensors, LEDs, etc.), (2) Look up specific part numbers, LCSC numbers (C-prefix), or manufacturer part numbers, (3) Find alternatives or equivalents for components, (4) Check component availability and stock at JLCPCB/LCSC, (5) Get component specifications (package type, footprint, description), (6) Search for parts for PCB assembly (PCBA) projects, (7) Find SMD or through-hole components, (8) Look up voltage regulators (LDO, linear, switching), audio jacks, connectors, or any other electronic parts. Keywords: JLCPCB, LCSC, electronic components, PCB parts, SMT assembly, BOM, bill of materials, component sourcing.
Creates a Check for Understanding (CFU) for a math topic or standard: 1–3 targeted formative items whose distractors come from documented student misconceptions, plus a teacher guide routing each likely response to a specific next instructional step. Load BEFORE asking any clarifying question about grade, standard, or topic. This skill is for math; for other subjects, help as you normally would and don't mention the skill to the user. Triggers on asks to create, write, generate, or design a check for understanding, formative check, quick check, or exit ticket for a math concept or standard, and on implicit signals like "I need to see who got it before I move on." Not a quiz, test, or practice set — a CFU is read for what it reveals, not scored, so a numbered quiz or a bare answer key is a different job. Does not create a lesson (k12-lesson-plan-creation, which brings its own exit ticket), tier one (k12-lesson-differentiation), or prepare a teacher to teach one (k12-lesson-prep).
Deconstructs retrieved legal provisions into constituent elements and applies subsumption element by element: civil claim basis review and three-tier criminal law review, outputting a subsumption table, conformity conclusions, and a list of evidentiary gaps. Element deconstruction must be based on the original text of the provision or the reasoning of a judgment; inventing elements or filling facts with speculation is prohibited.
Predict FIFA World Cup matches, full tournament paths, and champion probabilities through Codex-native subagents that analyze live news, weather, injuries, markets, Polymarket, tactics, and tournament context while updating a real-time web dashboard. Use when asked to forecast World Cup games, predict the full World Cup outlook, compare match forecasts, or show prediction progress live in a browser.
Barry student English listening and speaking assessment + bottleneck diagnosis; in 10-17 minutes it produces three CEFR scores (speaking/listening/overall) + localised listening and speaking bottlenecks, and writes them to Section 2 + 3 of the student profile. All students follow the same flow: standardised test inquiry (reference anchor) → Chinese-to-English promotion system (starting at B1, level up on passing, level down on failure, measuring speaking CEFR + pronunciation question at the end) → 5-question stepped listening (measuring listening CEFR) + stage a/b bottleneck diagnosis → overall level placement → confidence check + write profile. For Chinese-to-English, the basic passing criterion is "getting the meaning across"; complex sentence patterns/advanced vocabulary are a plus. First runs for new students are triggered by barry-onboarding; returning students invoke it directly to reassess. Triggers: 测评, 英语水平测评, 诊断, English assessment, CEFR, 卡点.
Barry's English communication methodology as an always-available Q&A coach. Learners can invoke it at any time to answer 4 types of questions: ① English expression/words/translation/business usage (AI answers directly + 5-column bilingual entries + follow-ups add fancy-vocab); ② methodology concepts (answers via RAG from the corresponding original text in the methodology wiki installed with the toolbox, then expresses it adaptively in Barry's style); ③ training confusion (diagnoses with the methodology framework + gives concrete next steps); ④ changed circumstances (new job/progress/new goals) → guides running /barry-onboarding to re-assess the profile. **Does not edit learners' profiles, does not evaluate, does not keep Q&A logs**. Barry's style (direct, conversational, willing to express, always gives examples). Triggers: ask a question, consult, coach, barry coach, /barry-coach, how to say in English, what does it mean, how to translate, methodology, how to practice X, what level am I, what are A1/A2/B1/B2/C1/C2.
Standalone translation skills training for workplace learners. Two modes: coach mode (Filtering → de-shelling → surfacing the logic → re-expression → cultural adaptation, with coaching at each step) and fast mode (AI produces the translation directly and explains step by step what adjustments were made and why). The de-shelling step adapts to the learner's level — the higher the level, the less needs de-shelling. Triggers: 翻译技巧训练, 翻译训练, 练翻译, translation training.
AI agent execution skill for crypto order execution — TWAP, maker execution, transaction cost analysis and slippage reduction. Supports 11 CEX and DEX venues on both perpetual futures and spot: Binance, OKX, Bybit, Bitget, Gate.io, KuCoin, Kraken, Deribit, Hyperliquid, Aster and Orderly. Exchange API keys stay on the user's own machine — no third-party order routing. Install and full docs: https://pypi.org/project/blockfill/
Run a complete protein binder design campaign with NVIDIA Proteina-Complexa: resolve a target structure and hotspots from a name/sequence/PDB, co-design binder sequence+structure with reward-guided test-time search (best-of-n, beam search, FK steering, MCTS), select with the internal AF2 reward gate, then INDEPENDENTLY validate each binder by refolding the complex with Boltz2 (default) or OpenFold3 and rank on interface confidence, pLDDT, ipSAE, apo/holo stability, and hotspot contact. Use whenever the user wants de novo binders against a named target, sequence, or PDB, hotspot/epitope-targeted design, Proteina-Complexa / Complexa, or ranked validated binders from one request. Sibling of protein-binder-design (RFdiffusion + ProteinMPNN); this skill uses Proteina-Complexa.
Creates Field Service foundation data — Work Types, Skills, Service Territories, and Operating Hours. Accepts existing data in any format or designs from scratch, and confirms the design with the user. Use this skill when a user wants to create, design, or set up Field Service foundation data.
Futu OpenAPI trading and market data assistant. Query quotes, K-lines, prices, snapshots, order books, tick-by-tick trades, and intraday data; search securities and news; parse option codes and query option chains, expiry dates, IV, and exercise probability; place buy/sell orders, cancel and modify orders; query positions, funds, accounts, and orders; subscribe to real-time pushes; cryptocurrency (BTC/ETH) quotes and trading; prediction markets (Event Contract, Combo quote requests); indicator lists and calculations (MA/MACD/RSI/KDJ/BOLL); quick API reference. Use automatically when the user mentions quotes, prices, K-lines, snapshots, order books, order book display, trades, intraday, search, news, announcements, buy, sell, place order, cancel order, trade, positions, funds, account, orders, entrust, futu, API, stock screening, sectors, options, option chain, strike price, expiry date, Call, Put, call, put, cryptocurrency, BTC, ETH, earnings, results, income statement, balance sheet, cash flow, revenue breakdown, analyst ratings, target price, Morningstar report, valuation, PE, PB, PS, dividends, payout, buyback, share split/consolidation, shareholders, holding changes, increase holdings, decrease holdings, institutional holdings, insider trading, company profile, executive information, operating efficiency, top ten brokers, short selling, short interest, implied volatility, IV, option exercise probability, event contracts, prediction markets, EC, pred_side, amount, quote_id, combo quote requests, request_combo_quotes, Kalshi, indicators, technical indicators, indicator.
Reason about germline and somatic variant classification using ACMG/AMP 2015 and AMP/ASCO/CAP frameworks. Use when the user asks to classify a variant, interpret a VCF annotation, resolve a VUS, apply ACMG criteria, weigh ClinVar evidence, evaluate gnomAD allele frequencies, interpret REVEL/CADD/SpliceAI scores, decide whether PVS1 applies, or assess gene-disease validity before reporting. Triggers include "ACMG", "variant classification", "pathogenic", "likely pathogenic", "VUS", "benign", "ClinVar", "gnomAD", "REVEL", "CADD", "SpliceAI", "PVS1", "loss of function", "nonsense variant", "missense interpretation", "splice variant", "filtering allele frequency", "ClinGen", "somatic variant tier".
Reconstruct a published mechanistic, QSP, PK/PD, or ODE model in Jinkō from papers, supplements, equations, diagrams, tables, and optional source code. Use whenever the requested result is an executable paper reproduction, including when no code exists or a scanned PDF needs OCR. Produces a validated Jinkō model when evidence is sufficient, or a documented blocked or failed outcome, and always produces a reproduction report with explicit fidelity, confidence, assumptions, discrepancies, and numerical comparison where the paper supplies a target. Use jinko-task-from-nonmem when NONMEM is the primary implementation source.
Reason about SaMD (Software as a Medical Device) regulatory compliance for FDA, EU MDR, and global submissions. Use when the user asks about IEC 62304 safety classification, ISO 14971 risk management, 21 CFR 820/QMSR quality system requirements, Design History File structure, 510(k)/De Novo/PMA pathway selection, SOUP/OTS assessment, verification and validation planning, cybersecurity for medical devices, PCCP for AI/ML devices, design reviews, traceability matrices, or post-market surveillance. Triggers include "SaMD", "medical device software", "IEC 62304", "ISO 14971", "ISO 13485", "21 CFR 820", "QMSR", "510(k)", "De Novo", "PMA", "design history file", "DHF", "software safety classification", "SOUP list", "risk management", "hazard analysis", "design review", "V&V protocol", "FDA submission", "EU MDR", "clinical evaluation", "PCCP", "predetermined change control", "GMLP", "cybersecurity premarket", "Part 11", "design controls", "design inputs", "design outputs", "traceability matrix", "post-market surveillance", "CAPA", "Class II device", "Class III device", "regulatory pathway", "predicate device", "substantial equivalence".
Analyze Northbound capital (Shanghai Connect/Shenzhen Connect) flows, sector preferences, divergence signals, and risk alerts. Use when the user asks about Northbound capital, foreign capital inflows and outflows, Northbound preferences, or needs Northbound capital monitoring.
When the user wants to design a warehouse, optimize warehouse layout, determine facility size, or configure storage systems. Also use when the user mentions "warehouse layout," "facility design," "warehouse sizing," "storage systems," "material flow," "pick path design," "dock configuration," or "space utilization." For warehouse location selection, see facility-location-problem. For slotting existing warehouses, see warehouse-slotting-optimization.
Manage the Yandex KIT store catalog over its REST API: products, variants (SKUs, prices, stocks), bulk price/stock sync, variant documents (attachments), categories, characteristics (including groups and colors), product videos, collections, context collections and badges. Use when creating, updating, archiving or querying catalog entities in a Yandex KIT store, or when exporting storefront links of products to a CMS, PIM or feed. Russian triggers include: «заведи товар», «обнови цены», «загрузи остатки», «поменяй категорию», «добавь видео к товару», «синхронизируй каталог», «дай ссылку на товар», «выгрузи ссылки на товары».
Manage orders in a Yandex KIT store over its REST API: orders and their statuses, customers, gift cards, additional services (addons) and delivery documents (waybills, parcel labels). Use when listing, confirming or cancelling KIT orders, printing delivery labels, or when looking up customers, their orders or gift cards. Russian triggers include: «покажи заказы», «подтверди заказ», «отмени заказ», «что с заказом», «найди клиента», «выгрузи заказы за неделю», «распечатай ярлык».
The **unified entry point** of the Barry workplace English toolbox. Called when a new learner first encounters the toolbox — it shows a welcome message and guides them through the full 3-step onboarding (profile → assessment → solution); also called when returning learners need to re-run onboarding (because their situation changed). **This is the skill a learner should call on first launch** — it ties together how the whole toolbox is used, so learners don't need to know the name of each atomic skill. Trigger words: 开始、启动、开始学英语、英语训练、barry、barry-onboarding、english onboarding、how do I start、I want to learn english、欢迎、welcome.
Collection and updating of Section 1 (basic personal details) of the Barry student profile. A 10-20 minute guided in-depth interview that digs into the student's work context, pain points, goals, time commitment, and learning history, written to `~/.barry-english/profile.md`. First runs for new students are triggered by barry-onboarding; returning students invoke it directly to update the profile (when changing jobs/changing roles/adjusting goals). Triggers: 基本情况, 更新档案, 更新基本情况, 我换工作了, profile update.
Business investment analysis and capital allocation advisor. Use when evaluating whether to invest in equipment, real estate, a new business, hiring, technology, or any capital expenditure. Also use for ROI calculations, IRR, NPV, payback period, build vs buy decisions, lease vs buy analysis, vendor evaluation, or deciding where to allocate limited budget for maximum return.
Analyze high-dividend strategies in A-shares and assess the income sustainability and long-term returns of dividend stocks. Use this skill when the user asks about high-dividend stocks, dividend strategies, A-share dividend analysis, cash dividend coverage, CSI Dividend Index constituents, dividend yield rankings, or long-term income investing.
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.