Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
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Crypto market leaderboards — ranked aggregate feeds across the whole market: social-hype/sentiment rank, trending / top-search / Binance Alpha / tokenized-stocks rank, smart-money net-inflow rank (which tokens received the most inflow), top meme tokens by breakout score on Pulse launchpad, top trader PnL leaderboard (ALL / KOL). Use whenever the user wants a ranked list of tokens or addresses by some metric — phrases like "trending tokens", "top N by hype", "leaderboard", "rank by X", "biggest inflows", "top traders this week".
Use when the user needs multi-source research with citation tracking, evidence persistence, and structured report generation. Triggers on "deep research", "comprehensive analysis", "research report", "compare X vs Y", "analyze trends", or "state of the art". Not for simple lookups, debugging, or questions answerable with 1-2 searches.
Router for the Cargo CLI skill bundle — load first for anything Cargo-related, and whenever a task spans two Cargo domains. Explains what each skill owns, declarative GTM as Code projects (cargo-project) vs. the imperative CLI, the UUID and slug flow between skills, async polling of runs and batches, end-to-end use cases, and gotchas that fail silently (inputs in a top-level action's `config` stripped without an error, run vs. batch, model-uuid vs. segment-uuid). Triggers: “set up Cargo,” “what can Cargo do,” “which Cargo skill,” “bootstrap my workspace,” “I have a Cargo account,” “cargo-ai …,” or any `cargo-ai` command whose domain you are unsure of. Skip when the task obviously belongs to one skill — load that skill directly.
Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when implementing self-critique and reflection loops; building evaluator-optimizer pipelines for quality-critical generation; creating test-driven code refinement workflows; designing rubric-based or LLM-as-judge evaluation systems; adding iterative improvement to agent outputs (code, reports, analysis); or measuring and improving agent response quality.
Builds, configures, debugs, and optimizes AWS observability—operator-symptom questions and detecting Omni vs classic CloudWatch. CloudWatch on an already-reporting service: Log Insights, metric/composite/anomaly alarms, custom metrics/EMF, dashboards, X-Ray/ADOT tracing, canaries, CloudTrail, Dynamic Instrumentation (live breakpoints/snapshots), the Application Signals service map, and fleet health views. CloudWatch Omni on an existing Space: SQL over logs and traces, PromQL over metrics, Omni dashboards, Omni alerts, context graph for root cause, programmatic/IaC access (API/SDK/CLI/CloudFormation), driving Omni from a coding agent or skills, and evaluating AI agent quality from traces—on-demand and online scoring of live traffic, readback, custom evaluators. For first-time setup—creating an Omni Space, granting access, ingestion, or ADOT instrumentation for Application Signals (ServiceEvents, CI/CD metadata) or Omni—use setting-up-cloudwatch-observability. Not for app logging or threat detection.
Run automated post-deploy UI verification with a browser automation MCP (claude-in-chrome, Playwright, or Puppeteer): console-error and Core Web Vitals smoke checks, form and auth-flow interaction tests, screenshot visual regression across three breakpoints, and axe-core accessibility audits ending in a SHIP / DO-NOT-SHIP verdict. Use when testing a deployed feature on staging or preview, before shipping frontend changes, reviewing a frontend PR, or checking responsive layout and accessibility.
Build a fully automated AI-powered data collection agent for any public source—job boards, prices, news, GitHub, sports, anything. Runs on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions. Use when the user wants to monitor, collect, or track any public data automatically.
Comprehensive Perl security covering taint mode, input validation, safe process execution, DBI parameterized queries, web security (XSS/SQLi/CSRF), and perlcritic security policies. Use when reviewing Perl input handling, process execution, DBI queries, or web-facing code.
Condense any input—an idea, brief, PRD, transcript, or mixed notes—into a short spec: one kernel file plus supporting files that downstream skills build from. Also updates and validates existing specs. Use when the user says “create a spec,” “distill this into a spec,” “validate this spec,” or “update the spec.”
Git workflow patterns including branching strategies, commit conventions, keeping history clean and readable, tidying local commits before merging, merge vs rebase, conflict resolution, and collaborative development best practices for teams of all sizes. Use when choosing a branching strategy, writing commit conventions, cleaning up history before a pull request, deciding merge versus rebase, or resolving conflicts.
Translate visa document images (bank deposit, employment, income, and retirement certificates; HEIC, PNG, or JPG) into English via OCR and produce a bilingual PDF pairing the original image with a formatted certified-style translation. Use when a visa application needs a document translated to English, an official certificate OCR'd and translated, or a bilingual translation PDF for immigration paperwork.
Manage the files in a Cargo workspace — upload knowledge (PDF, CSV, text) and build native or connector-backed libraries that agents retrieve from (RAG), and use files as plain storage: write and read by path, list a folder, and share a signed or public link. Triggers: “upload this PDF,” “add these docs as knowledge,” “build a knowledge base,” “sync our help center into Cargo,” “what files are in the workspace,” “index this folder,” “attach our pricing sheet,” “store this file,” “save the report somewhere,” “give me a link to the file,” “make this file public.” Skip when wiring a file or library into an agent — use cargo-ai; when uploading a CSV that drives a batch run — that is a workspace-management file upload.
This skill should be used when the user asks about 'account balance', 'how much USDT do I have', 'my funding account', 'show my positions', 'open positions', 'position P&L', 'unrealized PnL', 'closed positions', 'position history', 'realized PnL', 'account bills', 'transaction history', 'trading fees', 'fee tier', 'account config', 'max order size', 'how much can I buy', 'withdrawable amount', 'transfer funds', 'move USDT to trading account', or 'switch position mode'. Also use for '总资产', 'full balance', 'all assets', 'total holdings', 'net worth', 'how much do I have in total', 'show all my balances', 'all account balances', 'asset overview', 'aggregated balance', 'asset snapshot', '资产快照'. Requires API credentials. Do NOT use for market prices (use okx-cex-market), placing/cancelling orders (use okx-cex-trade), or grid/DCA bots (use okx-cex-bot).
Debug complex issues using competing hypotheses, parallel investigation, evidence collection, and root cause arbitration. Use this skill to debug bugs with multiple potential causes, perform root cause analysis, or organize parallel investigation workflows.
Build MCP servers with Node/TypeScript SDK — tools, resources, prompts, Zod validation, stdio vs Streamable HTTP. Use Context7 or official MCP docs for latest API. Use when building or debugging an MCP server — tools, resources, prompts, validation, or transport choice.
Extract self-contained static HTML from a built web application or React components by inlining CSS and images. Use this skill whenever you need to capture a specific UI state, share a static version of a page, or prepare assets for Stitch upload, even if the user just asks to 'save the HTML' or 'mock the view'.
Codified customs and trade compliance expertise — HS/HTS tariff classification with GRI rules, commercial invoices and entry documentation, Incoterms 2020, FTA qualification and duty optimization (USMCA, RCEP, FTZs, drawback), denied-party screening, and penalty mitigation across US, EU, UK, and APAC jurisdictions. Use when classifying goods, preparing import/export documentation, screening restricted parties, responding to customs audits or CF-28/penalty notices, or optimizing duties.
Upload local assets (images, mockups, extracted HTML, design markdown) to a Stitch project. ALWAYS use this skill when you need to upload visual assets, HTML pages, or design docs to Stitch, particularly when direct MCP tool calls fail or truncate due to base64 token limits
Convert existing projects into Apify Actors - serverless cloud programs. Actorize JavaScript/TypeScript (SDK with Actor.init/exit), Python (async context manager), or any language (CLI wrapper). Use when migrating code to Apify, wrapping CLI tools as Actors, or adding Actor SDK to existing projects.
Put something on the internet from Cargo — hosted web apps (Vite by default, other static frameworks detected) and serverless edge workers that answer HTTP requests, plus the deployments that build and promote them, the env vars and secrets a worker reads, running a worker locally, and custom domains and search indexing for public sites. Triggers: "build me a dashboard for this", "host this app", "give me a URL to share", "deploy this", "I need a webhook endpoint", "make it live", "promote to production", "ship a UI for my team", "give my worker an API token", "set a secret on the worker", "Missing CARGO_API_TOKEN", "my app cannot call my worker", "run the worker locally", "put it on my own domain", "make the site indexable by Google". Skip when: the app or worker should be declared as committed workspace code — use cargo-project.
Find and fix issues from Sentry using MCP. Use when asked to fix Sentry errors, debug production issues, investigate exceptions, or resolve bugs reported in Sentry. Methodically analyzes stack traces, breadcrumbs, traces, and context to identify root causes.
Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.
Codified demand planning expertise for multi-location retailers: demand forecasting method selection, ABC/XYZ segmentation, safety stock and reorder-point optimization, promotional lift and post-promo dip estimation, and seasonal transition and markdown timing. Use when forecasting demand, setting safety stock, planning replenishment, managing promotions, or optimizing inventory levels.
Coordinate parallel feature development with file ownership strategies, conflict avoidance rules, and integration patterns for multi-agent implementation. Use this skill when decomposing a large feature into independent work streams, when two or more agents need to implement different layers of the same system simultaneously, when establishing file ownership to prevent merge conflicts in a shared codebase, when designing interface contracts so parallel implementers can build against each other's APIs before they are ready, or when deciding whether to use vertical slices versus horizontal layers for a full-stack feature.
Review frontend code under `web/` or `packages/dify-ui/` when the user explicitly requests a review or audit. Supports PRs, branches, pending changes, files, and pasted diffs. Do not use for implementation-only requests, diagnosis without review intent, or backend-only code
MSW DefaultPlayer (character) management. Use the msw-general ModelBuilder to inspect/patch DefaultPlayer.model and Player.model, add/remove components, configure movement speed / jump force / HP / camera, and per-map-mode movement components. Use for DefaultPlayer model, player components, movement speed, jump force, HP, camera, physics. Keywords: player, DefaultPlayer, speed, jump, HP, camera, gravity, revive, respawn, character.
Authoring MSW scripts (.mlua) plus integrated playtest and debugging. Covers mlua syntax, annotations (@Component/@Logic/@ExecSpace/@Sync), lifecycle, exec spaces, property sync, event system, file workflow, build-log inspection, error classification, and the test/debug loop. Keywords: script, mlua, lua, Component, Logic, annotation, ExecSpace, Sync, event, play, test, debug, lifecycle.
Design, implement, and refactor Ports & Adapters systems with clear domain boundaries, dependency inversion, and testable use-case orchestration across TypeScript, Java, Kotlin, and Go services. Use when introducing or refactoring toward Ports and Adapters, or when domain logic has become entangled with I/O.
Operational controls for long-lived or cloud-hosted agent systems — runtime lifecycle (start, pause, stop, restart), observability (logs, metrics, traces), least-privilege safety scopes and kill switches, and rollout/rollback change management with audit logs and success/cost metrics. Use when running production agent fleets on PM2, systemd, or containers that need monitoring, incident response, or deployment gates.
Audit and improve SwiftUI runtime performance through code review and architecture. Use to diagnose slow rendering, janky scrolling, high CPU or memory usage, excessive view updates, or layout thrash in SwiftUI apps, and to provide guidance for user-run Instruments profiling when code review alone is insufficient.
MSW search integration — (1) vector search for API docs and implementation guides via the msw-mcp MCP server (mlua_api_retriever / mlua_document_retriever), (2) REST API search for resources (sprite / animation / sound / resource pack / avatar). Use for 'find details, examples, or related APIs not in .d.mlua', 'need a SpriteRUID', 'monster sprite', 'background image', 'find a sound', 'avatar item lookup', etc. Keywords: document search, API details, examples, guide, retriever, resource, sprite, animation, sound, RUID, resource pack, avatar.
MUST USE when designing ClickHouse architectures, selecting between ingestion or modeling patterns, or translating best practices into workload-specific system designs. Complements clickhouse-best-practices with decision frameworks and explicit provenance labels.
MSW avatar management — costume (CostumeManagerComponent, 17 slots) + animation 3-layer pipeline (StateComponent → AvatarStateAnimationComponent → AvatarRendererComponent). Four-level distinction: State key (uppercase) / AvatarBodyActionStateName (lowercase) / MapleAvatarBodyActionState enum / sprite action ID (swingO1, shoot1). Two mapping systems via IsLegacy/ActionSheet/StateToAvatarBodyActionSheet. PlayerControllerComponent auto-transition conflicts with ActionStateChangedEvent resolved via RemoveActionSheet/SetActionSheet/BodyActionStateChangeEvent. Applies to any avatar-bearing entity (NPC, monster, etc.), not only DefaultPlayer. Use for costume get/set, 17 equip slots, animation state mapping, action override, weapon-specific attack motion, custom shoot/cast/dance action. Keywords: avatar, costume, animation, state, action, shoot, swing, weapon, equipment, custom action, block auto playback, remap.
MSW combat system integration guide. Covers the Attack→Hit pipeline, damage model, i-frame, knockback, Hit Stop, Camera Shake, Sprite Flash, SFX, death/revive, damage skin, hit effect, avatar combat motion, custom events, and AI FSM — all based on MSW native APIs for 2D multi-genre coverage. Keywords: attack, hit, damage, combat, monster, hit effect, critical, projectile, damage skin, knockback, hit stop, combo, HP bar, collision, contact hit, TriggerComponent.
Reference guide to 9 prioritization frameworks with formulas, when-to-use guidance, and templates — RICE, ICE, Kano, MoSCoW, Opportunity Score, and more. Use when selecting a prioritization method, comparing frameworks like RICE vs ICE, or learning how different prioritization approaches work.
Split an RFC into a multi-agent execution DAG—decompose it into work units with dependencies and acceptance tests, run research, planning, implementation, testing, and review for each unit, then merge through a queue with re-based branches and perform final system verification. Use when a feature is too large for a single agent pass, orchestrating RFC-driven multi-agent execution, or managing merge queues across agent-built units.
Transform an output-focused roadmap into an outcome-focused one that communicates strategic intent. Rewrites initiatives as outcome statements reflecting user and business impacts. Use when shifting to outcome roadmaps, making a roadmap more strategic, or rewriting feature lists as outcomes.
Use when planning or writing server-side code that uses `@supabase/server` — Edge Functions, Hono apps, webhook handlers, or any backend that creates Supabase clients or validates inbound auth. Trigger **before** writing or modifying any file that imports from `@supabase/server` (or sub-paths like `@supabase/server/core`); calls `withSupabase`, `createSupabaseContext`, `createAdminClient`, `createContextClient`, `verifyAuth`, `verifyCredentials`, or `extractCredentials`; configures an `auth:` mode (`'none'` | `'publishable'` | `'secret'` | `'user'`, or keyed variants like `'secret:*'`); or lives under `supabase/functions/` and authenticates an inbound request. Also trigger during planning — if a plan mentions any of the above, load the skill before drafting code; do not extrapolate `auth:` values or auth modes from neighboring functions. Also trigger when you see legacy patterns to migrate to this package — `Deno.serve`, `createClient(Deno.env.get('SUPABASE_URL'))`, imports from `esm.sh/@supabase` or `deno.land/std`, usage of `SUPABASE_ANON_KEY` / `SUPABASE_SERVICE_ROLE_KEY`, or the deprecated `allow:` config option / removed `'always'` / `'public'` mode values / removed `authType` field.
Multi-perspective academic paper review with dynamic reviewer personas. Runs a 5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate) with field-specific expertise; role separation is not a claim of independent error processes. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy, 審查論文, 論文審查, 模擬審查, 同儕審查, 幫我審這篇, 以審查人角度評估, 審查者校準, 논문 심사, 동료 심사, 모의 심사, 심사자 관점에서 평가, 심사자 보정, revisar artículo, revisión entre pares, revisión de manuscrito, informe de árbitro, revisa mi artículo, criticar artículo, simular revisión, revisión editorial, calibrar revisor
Manage Grid bots (spot/contract/coin-margined), DCA Martingale bots (Spot DCA 现货马丁 / Contract DCA 合约马丁), and Smart Portfolio bots (智能组合, auto-rebalancing multi-asset portfolio) on OKX. Covers create, stop, amend, monitor P&L, TP/SL, margin/investment adjustment, AI-recommended parameters, and recommended zone backtest. Requires API credentials. Not for regular orders (okx-cex-trade), market data (okx-cex-market), or account info (okx-cex-portfolio).
Skill for using the command-line tool pdftk (PDFtk Server) for working with PDF files. Use when asked to merge PDFs, split PDFs, rotate pages, encrypt or decrypt PDFs, fill PDF forms, apply watermarks, stamp overlays, extract metadata, burst documents into pages, repair corrupted PDFs, attach or extract files, or perform any PDF manipulation from the command line.
Quality control and non-conformance management for regulated manufacturing (FDA 21 CFR 820, IATF 16949, AS9100): NCR lifecycle and disposition, 5-Why/Ishikawa/fault-tree/8D root cause analysis, CAPA systems, SPC interpretation, AQL sampling, and supplier quality audits. Use when investigating non-conformances, performing root cause analysis, managing CAPAs, interpreting SPC data, or handling supplier quality issues.
This skill should be used when the user asks to "test this website", "run exploratory testing", "check for accessibility issues", "verify the login flow works", "find bugs on this page", or requests automated QA testing. Triggers on web application testing scenarios including smoke tests, accessibility audits, e-commerce flows, and user flow validation using ScoutQA CLI. Use this skill proactively after implementing web application features to verify they work correctly.
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.