Skills
101,174 packaged capabilities and playbooks for agents. Install any of them with one command.
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This skill MUST be used to create, review, analyze, teach, or facilitate 生態系地圖 (ecosystem maps), 利害關係人地圖 (stakeholder maps), or 服務藍圖 (service blueprints), including uploaded blueprints and CJM-to-blueprint requests. It SHOULD also be used for 服務設計、服務流程優化、服務旅程、接觸點 or 前台後台分析 when the task needs participant relationships, value exchanges, or service delivery analysis, even without naming a tool. It MUST NOT require users to remember a skill name.
Genre pack: Swiss-editorial design identity. Warm paper background, ink-black type, one vermillion accent, oversized serif display with monospaced labels, hairline grids, indexed sections, strict asymmetric composition. Use when the brief asks for a calm, editorial, print-inspired, or quietly premium feel. Stack on top of the design-taste core skill.
Effective web research discipline for AI agents — route first, then research with rigor. Step 0 triages whether a question needs external web lookup vs is answerable from the internal codebase/docs; when external, default mode auto-applies 4 maxims; on explicit 'strict/deep research' requests it runs a 7-dimension source-credibility evaluation (CRAAP + E-E-A-T) with an auditable report. When the static layer (WebSearch/WebFetch/curl) can't reach content (login-required / JS-rendered / anti-scraping like 小红书·公众号), it escalates to the real browser via the web-access skill (CDP, carries login state). Triggers: "web research", "external research", "look up information", "effective research", "strict research", "deep research", "strict fact-checking", "logged-in access", "dynamic pages", "anti-scraping", "how to use this library/framework", "are there vulnerabilities", "what is best practice" / web research, look up, investigate, strict research, deep research, fact-check, login-state access, dynamic page, anti-scraping. Do NOT use for: searching the local codebase, reading repo files, grepping code.
Scaffold a native-looking, effective Electron app with best practices baked in. Creates a production-ready Electron application with security hardening, modern tooling, proper IPC patterns, auto-updates, native UI elements, and optimal build configuration. Use this skill when users want to start a new Electron project or modernize an existing one.
Compress natural language memory files (CLAUDE.md, todos, preferences) into simple, plain language to save input tokens. Simplifies jargon-heavy text while preserving all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /eli5-compress <filepath> or "compress memory file"
Use this skill when building an Elixir macro or a declarative DSL — a schema/spec/route/workflow language in the shape of Ecto.Schema, Absinthe, Plug.Router, or ExUnit — with quote/unquote, __using__, module attributes, and @before_compile. It corrects the wrong defaults a model makes once it commits to metaprogramming — putting logic inside the quote block, re-evaluating unquoted expressions, forgetting Macro.escape, fighting hygiene with var!, generating code ad hoc instead of accumulating declarations, and validating the DSL at runtime rather than at compile time. Applies to writing or reviewing macro/DSL code. NOT for deciding whether to use a macro at all — that gate belongs to staff-level-elixir and adversarial-elixir, which say prefer plain functions.
Audits email domain deliverability setup (SPF, DKIM, DMARC, MX records, blacklists, TLS) and generates health score (0-100) with prioritized fix list. Checks bulk sender compliance against Google/Yahoo/Microsoft 2024-2026 requirements. Provides DNS records to add/update. Use when user asks to audit, check, or analyze email deliverability, domain health, or inbox placement.
Use when the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-cro.
Git-based engineering retrospective analyzing commits, PRs, and velocity over configurable windows with monorepo path scoping. Triggers on: "retrospective", "sprint retro", "weekly review", "what did we ship", "engineering retro", "dev summary", "commit analysis".
Generates an executive summary from planning artifacts for non-technical stakeholders. Auto-discovers business requirements, technical requirements, and timeline from the docs/ folder structure. Outputs a comprehensive summary covering business problem, solution, features, timeline, success metrics, risks, and resources.
Complete fal.ai image-to-image system. PROACTIVELY activate for: (1) FLUX image-to-image transformation, (2) ControlNet (canny, depth, pose), (3) Inpainting with masks, (4) Upscaling (ESRGAN, Clarity), (5) Background removal (BiRefNet, RemBG), (6) Face restoration (GFPGAN, CodeFormer), (7) IP-Adapter style transfer, (8) Strength parameter tuning. Provides: Transformation endpoints, mask formats, ControlNet types, upscaling options. Ensures proper image editing and enhancement workflows.
Build MCP servers in Python with FastMCP framework to expose tools, resources, and prompts to LLMs. Supports storage backends (memory/disk/Redis), middleware, OAuth Proxy, OpenAPI integration, and FastMCP Cloud deployment. Use when: creating MCP servers, defining tools or resources, implementing OAuth authentication, configuring storage backends for tokens/cache, adding middleware for logging/rate limiting, deploying to FastMCP Cloud, or troubleshooting module-level server, storage, lifespan, middleware order, circular imports, or OAuth errors. Keywords: FastMCP, MCP server Python, Model Context Protocol Python, fastmcp framework, mcp tools, mcp resources, mcp prompts, fastmcp storage, fastmcp memory storage, fastmcp disk storage, fastmcp redis, fastmcp dynamodb, fastmcp lifespan, fastmcp middleware, fastmcp oauth proxy, server composition mcp, fastmcp import, fastmcp mount, fastmcp cloud, fastmcp deployment, mcp authentication, fastmcp icons, openapi mcp, claude mcp server, fastmcp testing, storage misconfiguration, lifespan issues, middleware order, circular imports, module-level server, async await mcp
Apply when deciding, designing, or implementing FastStore theme customizations in src/themes/ or working with design tokens and SCSS variables. Covers global tokens, local component tokens, Sass variables, CSS custom properties, and Brandless architecture. Use for any visual customization of FastStore storefronts that does not require component overrides.
Batch content grabber — bulk fetch bookmarks, user tweets, search results, author notes, wiki pages, subreddit posts, and more from X/Twitter, Xiaohongshu, Reddit, WeChat, YouTube, Feishu, Zhihu. Use when user wants to batch/bulk fetch, search keywords, or grab all posts from an account.
Use when given a GitHub issue URL or number to investigate and implement a fix. Triggers on "fix issue", "fix bug", "fix #123", GitHub issue URLs, or any request to resolve a reported problem from a GitHub issue. Also triggers when asked to investigate errors, diagnose failures, or debug unexpected behavior in DBHub.
Make Flutter UIs work with TalkBack, VoiceOver, JAWS/NVDA, large text, high contrast, and reduced motion. Covers Semantics, MergeSemantics, ExcludeSemantics, BlockSemantics, 48×48 tap targets, icon-only tooltips, TextScaler, MediaQuery a11y *Of getters, sort keys vs keyboard focus, contrast, and guideline tests. Use when the user mentions accessibility, a11y, semantics, TalkBack, VoiceOver, screen reader, tap target, tooltip, text scale, high contrast, reduce motion, or runs /flutter-improving-accessibility.
Odoo frontend JavaScript patterns for website themes. Covers publicWidget framework (complete pattern with editableMode handling), Owl v1/v2 component patterns, _t() translation best practices, Bootstrap 4-to-5 migration, version detection, and critical development rules. Supports Odoo 14-19. <example> Context: User wants to create a publicWidget user: "Create a publicWidget for my Odoo website" assistant: "I will create a publicWidget with editableMode handling and proper cleanup." <commentary>publicWidget creation.</commentary> </example> <example> Context: User asks about Owl components user: "How do I create an Owl component in Odoo 18?" assistant: "I will show the Owl v2 pattern with static template and props." <commentary>Owl component pattern.</commentary> </example> <example> Context: User needs help with translations user: "How do I translate JavaScript strings in Odoo?" assistant: "Use _t() at DEFINITION TIME for static labels, not runtime wrappers." <commentary>Translation best practices.</commentary> </example> <example> Context: User migrating Bootstrap classes user: "Convert Bootstrap 4 classes to Bootstrap 5 for Odoo 17" assistant: "Replace ml-* with ms-*, mr-* with me-*, text-left with text-start." <commentary>Bootstrap migration.</commentary> </example>
Invoke to set up CI/CD pipelines for game builds -- automated testing, build pipelines, and deployment to Steam, itch.io, or Epic. Triggers on: "CI", "CD", "pipeline", "automated build", "deploy", "Steam deploy", "itch.io butler", "GitHub Actions game", "build automation". Do NOT invoke for general code review (use game-code-review) or manual testing guidance (use game-qa-lead). Part of the AlterLab GameForge collection.
Run a structured post-mortem analyzing what went well, what went wrong, and extractable lessons. Pulls git history, milestone data, and retrospective notes automatically. Triggers on: "post-mortem", "project review", "what did we learn", "lessons learned", or when a major milestone or project is complete. Do NOT invoke for sprint-level retrospectives (use game-retrospective) or design reviews (use game-design-review). Part of the AlterLab GameForge collection.
A senior expert assistant for China's college entrance examination (gaokao) question setting, offering professional guidance and review services. Suitable for creating gaokao questions, reviewing question quality, analyzing exam paper structure, and understanding question-setting trends. Combines document tools to extract and unpack files, web search to learn the latest trends, and analysis tools to evaluate question quality and paper structure. Covers the "one core, four layers, four wings" evaluation system, 2025 question-setting trends, question type conventions, scoring standards, and the question-setting process, in line with gaokao question-setting best practices.
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".
Guided Git workflow assistant. Helps with branching strategies, writing conventional commits, opening pull requests, resolving merge conflicts, and keeping history clean. TRIGGER when the user writes /git-workflow or asks for help with Git, branches, commits, PRs, or merge conflicts.
Open the project's deployment platform link. Triggers when user says 「去部署」「部署平台」「准备部署」 (go deploy / deploy platform / prepare to deploy) — even without explicitly saying "open link", as long as the intent is to access a deployment console or release platform. The skill reads docs/deploy.md for deployment links; if absent, scans project docs to extract and generate config; if nothing found, prompts user to provide. Supports multiple deployment links per project.
Diagnose SaaS, AI, product-led, sales-led, marketing, retention, activation, positioning, launch, founder-selling, and growth problems with source-traceable guidance organized by GTM lifecycle stage. Use when a founder or operator asks what to prioritize, how to launch or sell a product, whether to launch privately or under a brand/pseudonym, how to handle fear of criticism or selling, whether PMF exists, which GTM motion fits, whom to hire, or which experiment to run. After the user enters a GTM consultation, also use for all follow-up messages in that consultation—including short replies such as “继续”, objections, new facts, revisions, and requests to test another option—until the user explicitly asks to exit or stop using the skill. Route by stage and problem, preserve source provenance and evidence limits, and produce a compressed actionable decision.
Develop Home Assistant add-ons with Docker, Supervisor API, and multi-arch builds. Use when creating add-ons, configuring Dockerfiles, setting up ingress, or publishing to repositories. Activates on keywords: add-on, addon, supervisor, hassio, ingress, bashio, docker.
Generate an accessibility decision handoff for engineering. Chains: decision-documentation, compliance-mapping, accessibility-testing-strategy. Use when a design is ready for implementation and the engineering team needs clear accessibility specifications.
Immediate trigger conditions: the user mentions "building a website with HAP", "HAP front-end project", "HAP as a database", "corporate website", "official website", "building via HAP", "making a website with HAP", "HAP website", "building an official website", "front-end/back-end separation", "content management system", "HAP front end", "HAP official website". Provides a complete guide to building a HAP + front-end project, including HAP back-office configuration, front-end project structure, API integration, and data rendering.
Ask another coding agent in a Herdr pane—on this machine or another—and get exactly one authorized reply, with a loop guard, depth limit of 1, a fan-out cap, and a record of every delegation; send one-way notices; keep a plan’s lead with epochs and succession; lead a multi-agent debate to decide, research the state of the art, stress-test, or verify (rounds, angles, red teams, counted ballots and claims, a panel seated from idle panes or agentkit accounts). Use only when the user mentions Herdr, peers, a debate, panel or research by several agents, another agent, pane or machine, or when a plan you are executing delegates a task through Herdr. Do not use merely because parallel work could help. Requires HERDR_ENV=1 and Herdr’s official herdr skill.
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.
A skill for Huawei Cloud solution operations. It helps agents inspect, plan, operate, troubleshoot, and verify Huawei Cloud resources through hcloud, Huawei Cloud SDKs, Terraform, and MaaS capabilities. Use this when users want to query or change Huawei Cloud resources, troubleshoot authentication and API issues, assess environments, plan infrastructure, manage costs, or verify operational outcomes.
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.