Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Other
Point Cowork at a folder of resumes plus a job description -- screens every candidate against the actual requirements, produces a ranked shortlist with evidence, drafts advance/decline emails, and builds interview kits for the top picks. Pairs with hiring-scorecard for the interview stage.
Build a preliminary, evidence-based EU AI Act readiness assessment across AI-system inventory, territorial scope, operator roles, prohibited-practice screening, risk classification, transparency, high-risk controls, general-purpose AI obligations, governance, and implementation milestones. Use when an organization needs to triage an AI use case, vendor, model, product, or portfolio for Regulation (EU) 2024/1689; prepare an AI inventory, gap register, implementation roadmap, or counsel briefing; assess provider, deployer, importer, distributor, product-manufacturer, authorised-representative, or GPAI-provider responsibilities; or re-check readiness after regulatory or product changes.
New listing DD and event radar via gate-cli (info/news/cex): listings, fundamentals, risk, sentiment, tape, LaunchPool calendar; optional first spot/Alpha order after Action Draft + Y/N. Use this skill whenever the user asks about new listings, pre-listing research, launchpool, rug checks, or a first buy on a new asset. Trigger phrases include 'new listing', 'due diligence new coin', 'launchpool calendar', 'listing announcement', 'is it a rug', 'first buy spot'.
Use this skill when a systematic review of a company's internal compliance management system is needed to identify gaps in policies, process deficiencies and data privacy compliance risks. Typical triggers include but are not limited to: - A company engages a lawyer or compliance consultant to conduct an internal compliance risk assessment - The company conducts a compliance self-inspection before an IPO, M&A or regulatory examination - After a compliance incident, the systematic deficiencies in the management system need to be investigated - When establishing or updating a compliance management system, the fit between existing policies and laws and regulations needs to be assessed - The user requests a review of the compliance of internal rules and regulations, core business processes or privacy policy agreements. This skill covers three review dimensions: completeness of the policy system, effectiveness of business process controls, and personal information protection compliance.
Assists judges in making structured, reviewable and defensible judicial value judgments in scenarios of conflicting rights, legal uncertainty, proportionality review and reasoned discretion. This Skill helps judges identify conflicts of legal values in hard cases, determine the boundaries of discretion, carry out value balancing, and form an analytical framework usable for judicial reasoning. It does not replace the judge's final ruling; instead, it helps judges translate value judgments into a judicial reasoning process grounded in facts, norms and argumentative structure.
Trigger this skill when the following situations arise in legal reasoning: (1) the text of a legal provision is ambiguous and open to multiple interpretations; (2) disputes arise when applying a provision to specific case facts; (3) it is necessary to argue that a certain provision should or should not apply to a particular situation; (4) the two parties disagree on the interpretation of the same provision; (5) provisions appear to conflict and need to be reconciled through interpretation; (6) novel case facts cannot be directly mapped to the text of an existing provision; (7) it is necessary to analyze or challenge the application of law in a judicial document. The core of this skill is to use legal interpretation methods such as literal, systematic, and teleological interpretation to conduct rigorous interpretive argumentation on key provisions, arrive at reasonable and defensible legal meanings, and present the interpretation process and conclusions in a standardized manner.
Based on a case fact description, calls 8 atomic capabilities in combination to predict the charge, applicable legal provisions, sentence length and sentencing circumstances, and outputs a structured prediction report with a confidence assessment.
Hands-on playbook for macOS disk cleanup, dev-machine optimization, and proactive health alerting. Use when the Mac is full or slow, when a process persistently burns CPU, when a kernel panic / watchdog timeout / vm-compressor-space-shortage / Jetsam event happened, when the user asks to free disk space, audit storage, set up disk/memory/CPU alerts, or restore the same monitoring on a new Mac. Built around Mole (`mo` CLI) for safety guards plus a custom LaunchAgent-based alerter for active warnings. Covers Apple Silicon laptops with heavy AI/Docker workloads. Not for general macOS support, hardware diagnostics, networking issues, GUI / window-manager bugs, Time Machine recovery, or broken app installs.
Hands-on playbook for Windows 11 disk cleanup, dev-machine optimization, and proactive health alerting. Use when the PC is full or slow, when a BSOD / Kernel-Power 41 / crash dump / commit-memory pressure happened, when the user asks to free disk space, audit storage, set up disk/memory alerts, or restore the same monitoring on a new PC. Built around native Microsoft-supported tooling (Storage Sense, cleanmgr, DISM, pnputil, vssadmin, wevtutil, powercfg) as the safety floor, a drift-protected HTML cleanup UI, and a Task Scheduler + BurntToast alerter. Covers dev machines with heavy AI/Docker/WSL workloads. Not for general Windows support, hardware diagnostics, GPU/driver troubleshooting, antivirus/malware removal, Windows Update repair, networking, or app-specific performance problems unrelated to disk or memory pressure.
Complete Polygon agent toolkit for on-chain operations on Polygon. Use this skill whenever helping an agent set up a wallet, check balances, send or swap tokens, bridge assets, deposit or withdraw from yield (Aave aTokens, ERC-4626 vaults), register on-chain identity, submit or query reputation/feedback, or make x402 micropayments. Covers the full lifecycle: Sequence smart contract wallets, Trails DeFi actions, ERC-8004 identity + reputation, x402 payments. Single CLI entry point (`polygon-agent`), AES-256-GCM encrypted storage.
Comprehensive portfolio analysis using Alpaca MCP Server integration to fetch holdings and positions, then analyze asset allocation, risk metrics, individual stock positions, diversification, and generate rebalancing recommendations. Use when user requests portfolio review, position analysis, risk assessment, performance evaluation, or rebalancing suggestions for their brokerage account.
Create the standard Available and Busy presence statuses needed for Omni-Channel routing. TRIGGER when users ask to deploy Omni presence statuses, configure agent availability, deploy Omni status metadata, create an Available status for Case, Incident, Messaging, or Voice, or add the standard Busy status. DO NOT TRIGGER for custom status designs, unsupported objects, or PresenceUserConfig capacity.
Use to bind agent users into a Salesforce Queue via GroupMember Data API POSTs, with SOQL-based idempotency (safe re-run — only inserts missing bindings). Binds either the generated demo agents (agent{1..N}.<suffix>@example.com) or an explicit list of real agents passed as usernames/User Ids. Triggers: add agents to a Case/Voice queue, assign agent users to a queue, populate queue membership for Omni routing. Do not use to create the queue (service-omni-queue-deploy), to create the agent users (service-omni-agent-users-create), or to assign permission sets (service-omni-permission-set-assign).
Use to enable or verify the Omni-Channel sidebar on a Lightning console app. Triggers: enable the Omni sidebar, pin Omni-Channel in a console app, configure the Omni sidebar, turn on the Omni-Channel utility region, verify the pinned Omni widget. Do not use for Aura apps, standard apps, utility-bar-only Omni widgets, or to create a console app.
When an AI Agent needs to systematically analyze a legal question, case facts, a legal provision or a legal relationship, it must first break it down into a structured list of elements. This skill triggers in the following scenarios: - A case fact description is received and all legal elements must be extracted before analysis - A legal relationship must be judged as established or not (e.g. contract formation, tort constitution, crime constitution) - Two or more legal facts/provisions must be compared for similarities and differences - It serves as a pre-quality gate before downstream tasks such as legal reasoning, legal application and legal advice - The user explicitly requests to "list the elements", "analyze item by item", or "check for omissions". The core goal of this skill is to ensure element extraction is complete and without omissions, forming a traceable, verifiable structured list, and only then allowing entry into the next stage of reasoning. It is the "quality gate" in the legal analysis chain.
Symbolic math in Python: exact algebra, calculus (derivatives, integrals, limits), equation solving, symbolic matrices, ODEs, code gen (lambdify, C/Fortran). Use for exact symbolic results. For numerical use numpy/scipy; for stats use statsmodels.
Issue, cancel, and fetch Hungarian invoices via the szamlazz.hu Agent API. Handles VAT calculation, NAV taxpayer lookup, partner caching, and PDF generation. Use when the user mentions számla, számlázás, invoice, sztornó, díjbekérő, proforma, or wants to bill a customer.
Trigger this skill when an AI agent encounters the following situations in legal reasoning: (1) multiple legal provisions apply to the same facts (competing statutory provisions); (2) evidence contradicts or is inconsistent with other evidence (evidence conflicts); (3) a case has multiple points of dispute requiring a determination of hearing or analysis order (prioritizing disputed issues); (4) different legal sources (statutes, regulations, judicial interpretations, local regulations, etc.) make different provisions on the same question (conflicts of legal sources); (5) there is tension between a party's claims and the application of law that needs to be reconciled. This skill is a core hub capability of legal reasoning, and almost all complex legal analysis involves some form of conflict resolution.
This skill triggers when a user submits contract text, a transaction arrangement, a business agreement or a description of a legal relationship and needs to assess possible legal disputes or breach-of-contract risks. Typical trigger scenarios include but are not limited to: - The user asks for a contract review and identification of potential risks - The user asks whether a transaction arrangement has any obstacles to performance - The user describes difficulties in contract performance and needs to determine whether they constitute a breach - The user asks for a risk rating of contract clauses - The user provides an agreement between two or more parties and asks to identify possible points of dispute - The user describes a performance deviation that has already occurred and needs to assess the legal consequences - Forward-looking risk identification is needed in scenarios such as contract review, due diligence and transaction negotiation This skill focuses on the two core questions of "whether legal disputes will arise" and "whether breach-of-contract risks exist", and outputs a structured risk list with recommended responses.
Trigger this skill when specific legal consequences need to be derived from confirmed legal facts, identified legal relationships, and matched legal norms (including but not limited to the type and scope of civil liability, calculation of damages, determination of criminal sentences, type and extent of administrative penalties, validity status of contracts, etc.). Typical trigger scenarios include: - The user asks "how much compensation can I get" or "what liability does the other party bear" - The user asks "how many years will this behavior get" or "how much is the fine" - The need to derive specific legal effects from the satisfaction of legal constituent elements - The need to calculate quantified results such as specific compensation amounts, sentence ranges, or penalty amounts - The need to reach a final legal consequence after comprehensively considering adjustment factors such as aggravation, mitigation, or exemption. This skill is the terminal link in the legal reasoning chain, converting abstract legal norms into concrete, actionable legal conclusions.
Gate Smart Earn (L2) via gate-cli: Simple Earn, dual products, staking, yield compare, idle-fund ideas, subscribe/redeem with confirmation. Use this skill whenever the user asks about earn APY, flexible or fixed earn, dual investment, staking rewards, positions, or earn subscribe/redeem. Trigger phrases include earn, Simple Earn, dual investment, staking, flexible earn, fixed earn, subscribe earn, redeem earn, auto renew, APY compare.
HODLMM volatility risk monitor — reads Bitflow HODLMM pool state, computes current-state volatility proxy from bin distribution, scores regime (calm/elevated/crisis), and emits position-sizing or liquidity-pull signals for LP agents. Read-only; no wallet required.
Get option chain data from Interactive Brokers for equities, ETFs, and futures (FOP), including calls and puts with strikes, bids, asks, volume, implied volatility, and model Greeks. Use when user asks about options using IBKR data, futures options (NQ/ES/CL/GC...), or needs real-time option quotes from their broker. Requires TWS or IB Gateway running locally.
Ability to analyse, design, optimise, and improve systems that integrate people, processes, technology, and resources to meet defined performance, quality, cost, and safety requirements. Includes applying engineering, statistical, and systems methods to model workflows, identify inefficiencies, evaluate trade-offs, and implement improvements across operations and supply chains. Applies across manufacturing, services, logistics, healthcare, and infrastructure contexts and is independent of specific tools or industries, with human accountability retained for decisions, outcomes, and impacts.
Legal abductive reasoning skill, used to generate and evaluate the most plausible explanatory hypotheses when evidence is incomplete and facts are ambiguous. Combines Mill's five methods (agreement, difference, joint method of agreement and difference, residues, concomitant variations) for structured causal inference. Trigger when the user needs to "propose possible legal interpretations", "generate defense/prosecution hypotheses", "evaluate multiple readings of evidence", or "infer the best explanation from incomplete facts". Applies to case analysis, evidence evaluation, disputes over rule application, causal inference, and similar scenarios.
Comprehensive portfolio analysis using Alpaca MCP Server integration to fetch holdings and positions, then analyze asset allocation, risk metrics, individual stock positions, diversification, and generate rebalancing recommendations. Use when user requests portfolio review, position analysis, risk assessment, performance evaluation, or rebalancing suggestions for their brokerage account.
Create reusable agent users for Omni-Channel setup and routing validation. TRIGGER when users ask to create Omni agents, provision Omni test users, seed sandbox users for routing, create Omni-Channel routing agents, or repair missing demo agents. DO NOT TRIGGER for queue membership, permission-set assignment, or supervisor-user creation.
Use to populate the Omni-Channel Supervisor action + tab surface on an existing OmniSupervisorConfig by inserting the standard OmniSupervisorConfigAction and OmniSupervisorConfigTab companion rows via the Data API, idempotent (inserts only the missing types). Requires an OmniSupervisorConfig from service-omni-supervisor-config-deploy. Triggers: give the supervisor the standard action buttons and tabs, add Wallboard/Agents/Queues tabs to Omni Supervisor, configure supervisor actions like Change Queues/Skills. Do not use to create the supervisor configuration itself, create supervisor users, assign the supervisor permission set, or add custom-action / FlexiPage / AWS-dashboard / AI-agent surfaces (those need an external reference and must be set up in Setup).
Use to create N Omni-Channel supervisor users on a Salesforce org via Anonymous Apex, using the supervisor{i}.<suffix>@example.com pattern with SOQL-based idempotency (re-runs skip existing usernames). Passwords are set via System.setPassword and handled fail-closed: the wrapper proves no active debug TraceFlag before setting a password, and otherwise leaves the user ACTIVE and reset_required. Triggers: create supervisor users, provision supervisor accounts, scaffold supervisor personas. Do not use on production customer orgs (blocked by the safe_to_write guard), to bind supervisors to OmniSupervisorConfig (service-omni-supervisor-config-deploy), or to assign the ContactCenterSupervisor permission set (service-omni-supervisor-permset-assign).
Assists legal staff of mainland China administrative agencies in making value judgments and interest balancing based on the basic principles of administrative law from a given administrative case, and in forming a reasoned discretionary conclusion.
Gensyn Delphi information market tools, including the Delphi agent trading competition. List and filter markets (including verifiable-only filter), fetch market details with live on-chain prices and implied probabilities, quote buy/sell trades, execute buy and sell transactions (with automatic token approval and slippage protection), view portfolio positions, browse trade history, query on-chain event data via Goldsky subgraph (buys, sells, redemptions, liquidations, settlements), check subgraph indexing status, redeem winnings from settled markets, liquidate expired or failed markets, manage ERC-20 token allowances, and check wallet ETH and token balances. Uses the @gensyn-ai/gensyn-delphi-sdk npm package on Gensyn testnet, mainnet, or the agent trading competition (competition-testnet — LMSR markets with their own contracts, token and leaderboard at agent-competition.gensyn.ai). Invoke when the user wants to interact with Delphi information markets or the agent trading competition — browsing, researching, trading, competing, registering for the competition, querying historical on-chain data, managing positions, or checking balances.
gate-dex CLI market & token data skill: K-line, liquidity, trading stats, token info, security audit, rankings, new listings, chain config, and raw RPC. Read-only; no signing. Use this skill whenever the user asks for on-chain market data, token info, or security audits via the gate-dex CLI. Trigger phrases include K-line, token price, market cap, token risk, honeypot check, token rankings, new tokens, liquidity, tx stats, chain config, rpc.
gate-dex CLI swap skill: one-shot DEX swap (quote → GV checkin → sign → broadcast) via the swap command. GV checkin built in — no external binary. Supports EVM multi-chain and Solana, with ERC20 approve flow. Use this skill whenever the user wants to swap, exchange, buy, sell, convert, or bridge tokens via the gate-dex CLI. Trigger phrases include swap, exchange, buy, sell, convert, bridge, cross-chain, quote, swap history, swap detail, swap-tokens, bridge-tokens.
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.