Skills
101,174 packaged capabilities and playbooks for agents. Install any of them with one command.
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Guide for using the Marketplace Ad Pros MCP server to manage and analyze Amazon Advertising accounts. Use when working with Amazon Ads campaigns, performance reports, bid/budget recommendations, keyword research, or product data through the MCP tools.
Perform full-dimensional penetrating analysis of Amazon competitor listings, including copy logic, review analysis, keyword analysis, and market dynamics. After analysis, automatically save a Markdown report to the reports/ directory. Invoke when user uses /amazon-analyse command with a product ASIN.
Manage Apple Notes on macOS — list, search, read, create, append, move, delete, and export notes, and manage folders. Use when the user mentions Apple Notes / 备忘录, "add a note", "my notes", searching their notes, organizing folders, or exporting a note to Markdown/HTML. macOS-only; runs locally against Notes.app — no cloud API, no token.
Records research provenance at the end of a coding or research session by scanning the conversation and writing decisions, experiments, dead ends, pivots, claims, and heuristics into the ara/ directory (exploration_tree.yaml, claims.md, heuristics.md, observations.yaml, session records), each tagged user, ai-suggested, ai-executed, or user-revised. Use when a task is finished and you want a session epilogue. Use when you need an auditable trace of how a project evolved. Use when decisions and dead ends need logging with provenance. Use when initializing an ara/ directory. Do not use during task execution, since it must run only after the request is complete.
Strategic guidance for designing modern data platforms, covering storage paradigms (data lake, warehouse, lakehouse), modeling approaches (dimensional, normalized, data vault, wide tables), data mesh principles, and medallion architecture patterns. Use when architecting data platforms, choosing between centralized vs decentralized patterns, selecting table formats (Iceberg, Delta Lake), or designing data governance frameworks.
Prepare and post preprints to arXiv without processing failures or leaks, covering TeX source packaging (.bbl, figures, case-sensitive paths), stripping private comments, choosing categories and license, endorsement, metadata (title, abstract, comments field), versioning and replacements, and linking the journal DOI later. Use when posting a paper to arXiv, when arXiv's TeX compilation fails, before uploading source, or when updating a preprint after acceptance. Includes a zero-dependency preflight checker.
End-to-end AscendC custom operator development for Ascend NPU in an ascend-kernel (csrc/ops + build.sh + torch_npu PyTorch custom op) project. Use to design, generate, build, test, document, and tune a new AscendC operator from a name and a math/functional spec. Covers project init, two-level tiling design, op_host/op_kernel code generation, framework registration, compile/install/debug, PyTorch-style API docs, precision evaluation and root-cause debugging, torch_npu.profiler performance benchmarking, performance optimization, and security code review.
Deep accessibility scorecard for a single Figma component or component set — state coverage (default/hover/focus/disabled/error/active/loading), focus-indicator quality and contrast, non-color state differentiation, target size, annotation completeness, and color-blind simulation (protanopia/deuteranopia/tritanopia), all rolled into per-category 0–100 scores and prioritized recommendations. Use when the user wants to vet ONE component before shipping it: triggers 'audit this component', 'accessibility score for this button', 'is this component set accessible', 'check the states on this component', 'does my button have a focus state', 'color blind check', 'rate this component for a11y', 'component accessibility scorecard'. Works on ANY Figma plan. For a broad sweep over a whole page/frame use lint-design-figma; for CODE-side (HTML) checks use scan-code-accessibility-figma.
Implement web service integrations in B2C Commerce using LocalServiceRegistry. Use this skill whenever the user needs to call external REST or SOAP APIs from a cartridge, configure service credentials and profiles in services.xml, handle HTTP requests with createRequest/parseResponse callbacks, set up FTP or SFTP file transfers, or troubleshoot circuit breaker errors. Also use when connecting to payment gateways, shipping providers, or third-party services -- even if they just say 'call an external API from my controller' or 'my service keeps timing out'.
Knowledge comic creator supporting multiple styles (Logicomix/Ligne Claire, Ohmsha manga guide). Creates original educational comics with detailed panel layouts and sequential image generation. Use when user asks to create "知识漫画", "教育漫画", "biography comic", "tutorial comic", or "Logicomix-style comic".
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.
Drive your own Claude Code session from Basecamp: run the local connector, acknowledge trusted requests, and delegate work to background subagents that reply in Basecamp. Use when asked to connect an agent to this computer, drive agents from Basecamp, watch for mentions, assignments, pings, comments, or boosts, start or stop the connector, check its status or health, or change who may give the agent work and which projects it serves. Covers credentials (basecamp auth agent connect), permissions and projects (basecamp connect setup), status, and doctor. Running the connector requires Claude Code.
Use when adding `RapierPhysicsPlugin`, spawning `RigidBody`/`Collider`, reading `CollisionEvent` or `PhysicsQuarantineEvent`, querying with `ReadRapierContext`, configuring `KinematicCharacterController`, or ordering gameplay around `PhysicsSet` in Bevy 0.20.
When the user wants to optimize their Bing Maps listing, set up Bing Places for Business, or improve visibility in Microsoft's search ecosystem. Also use when the user mentions "Bing Places," "Bing Maps," "Bing local," "Microsoft local listings," or "Copilot local." For Google Business Profile, see gbp-optimization. For Apple Maps, see apple-business-connect.
Blutui project guidelines from the Blutui Engineering team. Use this skill whenever working on ANY Blutui project — writing or editing templates, layouts, components, or partials; creating or querying Collections; building or handling forms; configuring routing or Courier; working with Canopy or Cassettes; using the Blutui MCP; or setting up a new Blutui project from scratch. If the user mentions Blutui, Canopy, Cassettes, Courier, or any Blutui-specific concept, always load and follow this skill before writing any code or configuration.
Write a high-quality prompt for any LLM or AI assistant — Claude, Claude Code, ChatGPT, Gemini, Cursor, Windsurf, Copilot, or any coding / chat agent. Use this skill whenever the user asks to write, improve, refine, shorten, or rewrite a prompt; asks "how should I phrase this for [model]" or "what's a good prompt for [task]"; describes a task they want an AI to do but hasn't yet formulated it as a prompt; or pastes an existing prompt and asks for revision. Based on Boris's (Anthropic, Claude Code creator) prompt methodology — short and accurate prompts, plan-before-code, feedback loops, persistent context in files. The universal principles (short, plan-first, feedback-loop, no-padding) apply to any LLM; the Claude-Code-specific anchors (CLAUDE.md, @file, slash commands) only apply when the target is Claude Code. If the user's intent is unclear (target model, deliverable, scope, or whether the AI has a way to self-verify is missing), ask 1–3 targeted clarifying questions via AskUserQuestion before writing the prompt.
Use when users explicitly ask to brainstorm, shape requirements, compare approaches, or produce a planning/design document before implementation. Turn rough ideas into validated brainstorming/design docs through focused dialogue, role-based analysis, and explicit user approval. Do not trigger this skill for straightforward implementation requests that do not need dedicated design exploration.
Advise users on Contentstack Brand Kit concepts, setup, governance, and on-brand AI generation. Route API-specific tasks to the right Brand Kit capability or reference skill, and enforce brand and safety rules before presenting anything as ready. Use when users ask about Contentstack Brand Kit, Voice Profiles, Knowledge Vault, brand voice, tone, style rules, on-brand AI generation, setup, governance, or API usage.
Finds free backlink and brand mention opportunities across Hacker News, Quora, GitHub, directories, and niche communities. Outputs a prioritized action plan with draft responses ready to post. Use after brand research and content creation to amplify reach and AI engine citations.
Applies Apple's Project Purple design philosophy for radical innovation. This skill should be used when the user wants to challenge industry conventions, approach open-ended problems requiring disruptive thinking, or when standard brainstorming needs a breakthrough approach.
Apply bulletproof-react conventions when writing, organizing, or reviewing React or TypeScript apps. Covers feature-based folder structure, API layers, state management categories, testing strategy, error handling, auth, and performance. Use whenever the user creates a new React feature, sets up project structure, asks "where does this go" or "how should I organize this", decides where state lives, writes data-fetching or auth code, or asks for a React architecture review. Triggers on "feature folder", "React project structure", "should I use Redux", "how to structure API calls".
BullMQ queue system reference for Redis-backed job queues, workers, flows, and schedulers. Use when: (1) creating queues and workers with BullMQ, (2) adding jobs (delayed, prioritized, repeatable, deduplicated), (3) setting up FlowProducer parent-child job hierarchies, (4) configuring retry strategies, rate limiting, or concurrency, (5) implementing job schedulers with cron/interval patterns, (6) preparing BullMQ for production (graceful shutdown, Redis config, monitoring), or (7) debugging stalled jobs or connection issues
Carbon Design System expert for React and Web Components. Use for Carbon components (Button, Modal, DataTable, etc.), IBM product UI, Carbon Charts (React/Angular/Vue/Svelte/vanilla JS), Carbon icons and pictograms, Carbon design tokens and IBM Plex font, Carbon usage and accessibility documentation, AI Chat / watsonx integration, or any Carbon code generation
Use Chonkie for fast, lightweight text chunking in RAG pipelines. Covers all 11 chunker types (Token, Fast, Sentence, Recursive, Semantic, Late, Code, Neural, Slumber, Table, TeraflopAI), the Pipeline API for chaining fetch→process→chunk→refine→export→store workflows, embeddings refineries, vector DB handshakes (Chroma, Qdrant, Pinecone, etc.), tokenizer selection, recipe system, REST API server, and async/batch processing. Use when: splitting documents for embeddings, building ingestion pipelines, chunking code or markdown, setting up vector DB ingestion, or any text segmentation task for retrieval-augmented generation.
Deterministic CI/CD interaction patterns with structured evidence output. Push-and-wait discipline (one pending run at a time), five-category failure triage (test-failure, lint-failure, build-failure, flaky-test, infra-failure) with classification-specific fix strategies, self-healing for lint/format/infra failures, flaky test detection, and CI_RESULT JSON evidence packets for every run. Use when pushing code to CI, triaging CI failures, waiting for pipeline results, classifying build errors, dealing with flaky tests, or producing CI evidence for quality gates. Triggers on: "CI failed", "push and wait for CI", "triage build failure", "flaky test", "CI pipeline", "build broke", "CI evidence". NOT for: individual test debugging (use debugging-protocol), code review (use code-review).
Diagnose and fix failing CircleCI builds quickly and safely. Use when users ask to investigate failed CircleCI jobs, triage flaky pipelines, identify root causes from logs, and implement minimal fixes in configuration, test setup, or build-related code paths.
Generate ASCII art logos/banners for CLIs (with box drawing borders, █ block characters, and ANSI 24-bit gradients) and provide runnable scripts plus integration code. Use for requests such as "make a terminal logo like the Spec Kit CLI", "colorful ASCII banner", "figlet-style title", or "CLI startup welcome screen".
Use when reviewing Spring Boot 4 / Java 17+ code with concrete files or diffs — pull requests, modules, or pasted Java/Spring sources — for migration risks, architecture boundary leaks, JSpecify null-safety gaps, security flaws, performance regressions, or Spring Data pitfalls. Not for Kotlin-only code, non-Spring frameworks, or generic review advice without code context.
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, modifying, or reviewing code — implementation tasks, code changes, refactoring, bug fixes, or feature development. Do NOT use for architecture design, documentation, or non-code tasks.
Use this skill to discover and score online communities across Reddit, Slack, Discord, Facebook, LinkedIn, and independent forums. Trigger it when finding where a target audience gathers, planning organic participation, partnerships, or community-led go-to-market.
Use this skill to synthesize research on two or more competitors into feature and pricing comparisons, positioning, SWOT, moat analysis, and strategic recommendations. Trigger it after individual competitor profiles exist or when preparing a market landscape.
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.