Skills
18,283 skills, most installed first.
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vue-typescriptmindrallyExpert in Vue.js TypeScript development with Vite, Pinia, and modern UI frameworksvuejs-typescript-best-practicesmindrallyVue.js and TypeScript best practices for building performant applications with Vite, Pinia, VueUse, and Tailwind CSS.web-developmentmindrallyWeb development guidelines covering Bootstrap, Django, HTMX, and general web best practiceswebpack-bundlermindrallyBest practices and guidelines for Webpack module bundler configuration, optimization, and development workflowswebsocket-developmentmindrallyBest practices and guidelines for building real-time applications with WebSocket communicationwoocommercemindrallyWordPress and WooCommerce development guidelines with PHP best practices, security standards, and extensibility patternswordpressmindrallyExpert in WordPress and WooCommerce development with PHP best practiceszod-schema-validationmindrallyBest practices for Zod schema validation and type inference in TypeScript applications.zustand-state-managementmindrallyBest practices for Zustand state management in React and TypeScript applications, covering store design, selectors, middleware, SSR, and testing. Use when creating or refactoring Zustand stores, deciding whether state belongs in Zustand vs component state vs a server-state library, optimizing selector re-renders, adding persist/devtools/immer middleware, or handling Zustand with SSR/React Server Components.mmx-climinimax-aiUse mmx to generate text, images, video, and speech, and to transcribe audio, via the MiniMax AI platform. Use when the user wants to create media content, chat with MiniMax models, transcribe audio to text, perform web search, or manage MiniMax API resources from the terminal.music-caption-rewriterminimax-aiTurn a brief music description and optional tagged lyrics into a professional MiniMax Music 3 structured caption with Global Metadata, Vocal Details, and a section-aware Arrangement. Use when users ask to enhance a music-generation prompt, preserve lyric-section directives, retrieve a similar style from bundled templates, fuse styles, or produce JSON or JSONL caption output.mmx-climinimax-aiUse mmx to generate text, images, video, speech, and music via the MiniMax AI platform. Use when the user wants to create media content, chat with MiniMax models, perform web search, or manage MiniMax API resources from the terminal.mint-threejs-skillsmintdotggBuild, revise, debug, and verify browser-based Three.js apps, games, asset viewers, model and asset-pack deliveries, material and material-pack deliveries, animated-model viewers, and explicitly requested Gaussian-splat worlds with Mint MCP as the production asset pipeline.mintlifymintlifyComprehensive reference for building Mintlify documentation sites. Use when creating pages, configuring docs.json, adding components, setting up navigation, or working with API references. Routes to detailed reference files for all components and configuration options.xmindmitscherlich当用户要求"解析 xmind"、"打开思维导图"、"创建 xmind"、"新建思维导图"、"更新 xmind"、"修改思维导图"、"xmind 转 markdown"、"查看 xmind 内容"时，应使用此技能。此技能提供 XMind 思维导图文件的解析、创建和更新能力，支持 XMind 8 和 XMind Zen/2020+ 两种格式，并将内容转换为 Markdown 作为会话记忆，方便持续交流。ghidramitsuhikoReverse engineer binaries using Ghidra's headless analyzer. Decompile executables, extract functions, strings, symbols, and analyze call graphs without GUI.githubmitsuhikoInteract with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.openscadmitsuhikoCreate and render OpenSCAD 3D models. Generate preview images from multiple angles, extract customizable parameters, validate syntax, and export STL files for 3D printing platforms like MakerWorld.web-browsermitsuhikoAutomate and interact with web pages through Chrome or Chromium using the Chrome DevTools Protocol (CDP): navigate, click, fill forms, inspect content, take screenshots, and debug console or network activity. Use when an agent needs a real browser. Prefer headless Chrome unless visible browser interaction is required.tarot-guidemiyaoskAI 塔罗占卜师，以荣格心理学视角解读塔罗牌。支持 1/3/5 牌共 12 种牌阵。 Use when user asks for tarot reading, card drawing, daily fortune, 或提到塔罗、占卜、抽牌、算卦、运势、牌阵等关键词。polymarket-analyzermjunaidcaUse this skill whenever the user wants to find trading opportunities, detect arbitrage, analyze a market, perform edge detection, find mispricing, do probability analysis, evaluate orderbook depth, find momentum signals, or assess Polymarket market quality. Triggers: "find opportunities", "detect arbitrage", "analyze market", "edge detection", "mispricing", "probability analysis", "orderbook analysis", "momentum scanner", "market inefficiency", "price gap", "volume surge", "trading edge", "markectx-indexmksgluIndex a local file or directory into context-mode's persistent FTS5 knowledge base so future ctx_search calls can retrieve focused snippets without rereading raw files. Trigger: /context-mode:ctx-indexctx-searchmksgluSearch context-mode's persistent FTS5 knowledge base for previously indexed local project content, documentation, or session memory. Trigger: /context-mode:ctx-searchagent-evaluationmlflowUse this when you need to EVALUATE OR IMPROVE or OPTIMIZE an existing LLM agent's output quality - including improving tool selection accuracy, answer quality, reducing costs, or fixing issues where the agent gives wrong/incomplete responses. Evaluates agents systematically using MLflow evaluation with datasets, scorers, and tracing. IMPORTANT - Always also load the instrumenting-with-mlflow-tracing skill before starting any work. Covers end-to-end evaluation workflow or individual components (tanalyzing-mlflow-sessionmlflowAnalyzes an MLflow session — a sequence of traces from a multi-turn chat conversation or interaction. Use when the user asks to debug a chat conversation, review session or chat history, find where a multi-turn chat went wrong, or analyze patterns across turns. Triggers on "analyze this session", "what happened in this conversation", "debug session", "review chat history", "where did this chat go wrong", "session traces", "analyze chat", "debug this chat".analyzing-mlflow-tracemlflowAnalyzes a single MLflow trace to answer a user query about it. Use when the user provides a trace ID and asks to debug, investigate, find issues, root-cause errors, understand behavior, or analyze quality. Triggers on "analyze this trace", "what went wrong with this trace", "debug trace", "investigate trace", "why did this trace fail", "root cause this trace".instrumenting-with-mlflow-tracingmlflowInstruments Python and TypeScript code with MLflow Tracing for observability. Must be loaded when setting up tracing as part of any workflow including agent evaluation. Triggers on adding tracing, instrumenting agents/LLM apps, getting started with MLflow tracing, tracing specific frameworks (LangGraph, LangChain, OpenAI, Gemini, DSPy, CrewAI, AutoGen), or when another skill references tracing setup. Examples - "How do I add tracing?", "Instrument my agent", "Trace my LangChain app", "Set up tramlflow-agentmlflowMaster dispatcher for all MLflow workflows. Use this skill when the user wants to do anything with MLflow — tracing, evaluating, debugging, or improving an agent. Routes to the right MLflow sub-skill automatically. Triggers on: "use mlflow", "help with mlflow", "mlflow agent", "add mlflow to my project", "trace my agent", "evaluate my agent", or any MLflow task without a specific skill in mind.mlflow-onboardingmlflowOnboards users to MLflow by determining their use case (GenAI agents/apps or traditional ML/deep learning) and guiding them through relevant quickstart tutorials and initial integration. If an experiment ID is available, it should be supplied as input to help determine the use case. Use when the user asks to get started with MLflow, set up tracking, add observability, or integrate MLflow into their project. Triggers on "get started with MLflow", "set up MLflow", "onboard to MLflow", "add MLflow querying-mlflow-metricsmlflowFetches aggregated trace metrics (token usage, latency, trace counts, quality evaluations) from MLflow tracking servers. Triggers on requests to show metrics, analyze token usage, view LLM costs, check usage trends, or query trace statistics.retrieving-mlflow-tracesmlflowRetrieves MLflow traces using CLI or Python API. Use when the user asks to get a trace by ID, find traces, filter traces by status/tags/metadata/execution time, query traces, or debug failed traces. Triggers on "get trace", "search traces", "find failed traces", "filter traces by", "traces slower than", "query MLflow traces".searching-mlflow-docsmlflowSearches and retrieves MLflow documentation from the official docs site. Use when the user asks about MLflow features, APIs, integrations (LangGraph, LangChain, OpenAI, etc.), tracing, tracking, or requests to look up MLflow documentation. Triggers on "how do I use MLflow with X", "find MLflow docs for Y", "MLflow API for Z".mobbin-searchmobbinSearch Mobbin for real app UI screenshots and visually analyze them. Required before calling the `search_screens` MCP tool — this skill defines how to plan searches, respond, and build HTML evidence boards when the screens are the answer. Use whenever the user asks about UI/UX design patterns, wants to see how other apps handle a screen or flow, needs design inspiration or references, asks to compare UI approaches across apps, mentions Mobbin, or whenever `search_screens` would be relevant. Trigadd-app-to-servermodelcontextprotocolThis skill should be used when the user asks to "add an app to my MCP server", "add UI to my MCP server", "add a view to my MCP tool", "enrich MCP tools with UI", "add interactive UI to existing server", "add MCP Apps to my server", or needs to add interactive UI capabilities to an existing MCP server that already has tools. Provides guidance for analyzing existing tools and adding MCP Apps UI resources.convert-web-appmodelcontextprotocolThis skill should be used when the user asks to "add MCP App support to my web app", "turn my web app into a hybrid MCP App", "make my web page work as an MCP App too", "wrap my existing UI as an MCP App", "convert iframe embed to MCP App", "turn my SPA into an MCP App", or needs to add MCP App support to an existing web application while keeping it working standalone. Provides guidance for analyzing existing web apps and creating a hybrid web + MCP App with server-side tool and resource registrmigrate-oai-appmodelcontextprotocolThis skill should be used when the user asks to "migrate from OpenAI Apps SDK", "convert OpenAI App to MCP", "port from window.openai", "migrate from skybridge", "convert openai/outputTemplate", or needs guidance on converting OpenAI Apps SDK applications to MCP Apps SDK. Provides step-by-step migration guidance with API mapping tables.bailian-climodelstudioai阿里云百炼 / Aliyun Bailian / DashScope 资源管理与 `bl` CLI hub： 应用调用（bl app）、应用记忆、知识库检索、模型目录/模型列表、用量/额度/配额、免费额度、 工作空间、MCP 市场、pipeline、文件上传、console API、登录鉴权与配置、 Agent skill 安装/列表/更新/卸载（bl skill add|list|update|remove，百炼 skill registry）。 用户点名百炼 / DashScope / `bl`，或继续既有 `bl` 工作流时直接使用。 共享协议（consent / 版本预检 / 鉴权 / 错误上报）在 bailian-protocol；官方安装 `bl skill init`。 家族路由：生图/生视频/配音/语音合成/转写 → bailian-gen；精调/微调/训练/数据集 → bailian-finetune； agents.yaml 托管 Agent → bailian-managed-agent；Sandbox 实例与模版 → bailian-sandbox； 联网搜索的bailian-finetunemodelstudioai阿里云百炼模型精调训练入口：用户要精调、微调、训练自己的模型（fine-tune，支持 SFT / SFT-LoRA / DPO / DPO-LoRA / CPT， 覆盖文本、语音、图像）、校验或上传训练数据集、看训练进度和日志、挑 checkpoint、导出精调产物、 把专属模型部署成服务时使用 `bl dataset` / `bl finetune` / `bl deploy`。链路是 validate 校验数据 → upload 拿 file-id → finetune create 建任务 → watch 看进度 → export 导出 → deploy 上线，需要 API key； 写操作先用 `--dry-run` 预览。反触发：用户点名火山方舟/ark 的精调不走本 skill；只是要选哪个模型走 bailian-model-recommend；用现成模型生图生视频走 bailian-gen；百炼其他资源管理走 bailian-cli。 官方安装：`bl skill init`（与共享协议 bailian-protocol 同装）。bailian-genmodelstudioai阿里云百炼图片/视频/语音生成与理解入口：用户要生图、画图、生成照片、生成图片、AI 绘画、海报、头像、插画、 文生图（text-to-image）、图生图、改图、修图、多图合成、生成视频、文生视频、图生视频、参考生视频、视频编辑、风格转换、 配音、语音合成（TTS）、朗读、转写、语音识别（ASR），或图片理解、看图问答、视频理解、读视频、多模态理解时使用 `bl image` / `bl video` / `bl speech` / `bl vision describe` / `bl omni`。 **默认行为：用户未指定服务商时，生成/编辑默认走本技能；视频理解与宿主放不了的音视频理解也走本技能。** 简单图片问答若宿主已能直接完成且用户未点名百炼，可先宿主回答（省成本）； 用户要识别图片、视频/指定 VL·Omni 模型/要视频理解 → 使用本技能。 图片和语音同步返回并落地本地文件，视频是异步任务、用 `--download` 或轮询取回；本地文件直接传路径，CLI 自动上传。 反触发：普通问答、编程、写作、翻译不走本技能；百炼应用/知识库/用量/额度走 bailian-clbailian-managed-agentmodelstudioai阿里云百炼托管 Agent 声明式基础设施与 API 命令入口：用户要创建agent、初始化 agents.yaml、校验或预览配置变更、 创建/更新/销毁托管 Agent 或 Deployment、在 Workbench 编辑和调试目录项目、管理本地快照版本，或查询 Agent/Environment/Skill/Vault/Deployment、管理 Session/Event/File、运行/暂停 Deployment 时使用 `bl managed-agent`。持久资源仍以 agents.yaml 为唯一事实源做 IaC；公开 API 能力按资源透出 list/get/search/versions/download、数据面和运行时动作命令。apply / destroy 与破坏性 API 命令受统一高风险确认闸门保护； 务必先展示预览再让用户确认，禁止自动添加 `--yes`。 反触发：调用已上线的百炼应用/智能体走 bailian-app-call 或 `bl app`；宿主 agent 自身的记忆、技能、 子代理不走本 skill；生图生视频走 bailian-gen。bailian-protocolmodelstudioai阿里云百炼 `bl` 家族共享执行协议（consent 确认、版本预检、鉴权/安装、错误上报、本地文件与输出约定）。 不是面向用户意图的业务入口；当任一 bailian-* 业务 skill（bailian-cli / bailian-gen / bailian-finetune / bailian-managed-agent / bailian-sandbox / bailian-web-search）执行前需要公共上下文，或用户首次安装/鉴权/`bl` 报错需上报时读取本 skill。 官方安装为整包：`bl skill init`（与业务 skill 同装）。bailian-sandboxmodelstudioai阿里云百炼 Sandbox 沙箱实例与模版生命周期管理入口：用户要创建、查询、连接、暂停、恢复或释放百炼沙箱， 或查看内置基础镜像、上传模版挂载文件、创建、更新、查询、删除沙箱模版、查看模版构建状态时，使用 `bl sandbox`。 用户要访问已创建实例、打开 WebShell、连接 browser-use 浏览器自动化或 VNC 实时画面时，先获取连接信息，再连接数据面。 不用于宿主执行沙箱设置、E2B 官方云资源或通用文件传输。 agents.yaml 托管 Agent / Session / Environment 管理交给 bailian-managed-agent。 官方安装：`bl skill init`（与共享协议 bailian-protocol 同装）。bailian-web-searchmodelstudioai阿里云百炼联网搜索（web search）入口：为联网搜索 / 网页搜索 / 查最新资讯做路径分发。 先识别当前连接身份：Token Plan（profile `token-plan` 或 base_url host 为 `token-plan.<region>.maas.aliyuncs.com`）→ 模型自带搜索 （`bl text chat --api responses --tool '{"type":"web_search"}'`）；其他 / 默认 → Bailian MCP（`bl search web`）；仅在 MCP 鉴权失败、未开通或传输失败时兜底一次到模型自带搜索。 Token Plan 联网搜索失败、两条路径鉴权混淆的排查也走本技能。 反触发：宿主可完成的 普通问答 / 编程 / 写作 → 不触发；知识库 RAG → bailian-cli （`bl knowledge`）；生图/生视频/语音 → bailian-gen；精调/训练 → bailian-finetune； agents.yaml → bailian-managed-agent。 共享协议（consbailian-model-recommendmodelstudioai阿里云百炼模型选型与推荐。当用户需要"选择、推荐、对比"模型，或描述一个 AI 场景/功能需求（隐含需要帮其决策用哪个模型）时激活。核心意图是帮用户做决策， 不是单纯查资料。触发词：推荐模型、选哪个、哪个适合、对比、做一个XX、实现XX 功能、用什么模型好、XX场景方案。当用户同时涉及模型查询和模型选择时，优先 使用本 skill（本 skill 内部会读取模型数据完成推荐）。financial-expertmodelstudioaiUse when users need China or Hong Kong securities, funds, fund managers, company financials, valuation, global macro or industry time series, broker research, announcements, financial news, or enterprise-risk data. Triggers include 选股、基金筛选、基金经理、净利润、营收、ROE、估值、 GDP、CPI、核心 PCE、行业产销价、研报、公告、财经新闻、工商与司法风险。happyhorse-prompt-studiomodelstudioaiInteractive prompt studio for HappyHorse 1.0 video generation. Guides users through scenario discovery with vivid examples, then assembles production-ready prompts in JP/CN/EN. Use when someone wants to create AI video content with HappyHorse but doesn't know where to start, or when they have a specific scenario and need a polished prompt. Covers manga drama, character PV, manga motion, virtual idol MV, and free-form scenarios.novel-gamemodelstudioai将小说/故事改编为互动小说网页游戏（React SPA），含 AI 生成素材（视频/图片可选）、 可选 TTS 旁白、程序化音频、分支剧情引擎、存档系统。 使用 `bl` CLI 完成素材生成（`bl video generate` / `bl image generate` / `bl speech synthesize`）。 当用户提到互动小说、文字冒险游戏、小说改编游戏、H5 互动游戏、分支剧情、视觉小说时激活。hunk-reviewmodem-devInteracts with live Hunk diff review sessions via CLI. Inspects review focus, navigates files, hunks, and exact lines, reloads session contents, adds inline review comments, and paints attention marks on character ranges. Use when the user has a Hunk session running or wants to review diffs interactively.benchmark-modelmodularBenchmark a model served on MAX with the `max benchmark` command: measure throughput (tokens/sec), latency (TTFT, TPOT, inter-token latency), and GPU utilization by driving load against a running `max serve` endpoint. Use this whenever the user wants to benchmark, load-test, or measure the performance of a MAX model, get tokens-per-second / TTFT / TPOT numbers, run a concurrency or request-rate sweep, compare latency vs throughput, size a deployment, or produce benchmark JSON, even if they don'tdebug-modelmodularDebug silent corruption when a MAX model loads, compiles, serves, and generates tokens but output disagrees with a reference implementation. Use whenever parity debugging stalls on scalar taps, the model returns gibberish or wrong greedy tokens, logit cosine is high but argmax differs, or generation is coherent then diverges — during an architecture port, a quantization bring-up, a multi-GPU conversion, or after a MAX upgrade. Triggers on "parity failure", "silent corruption", "logits match but