Total 58,116 skills, AI & Machine Learning has 9659 skills
Showing 12 of 9659 skills
Build RAG pipelines with Exa.ai for real-time web retrieval. Use when building retrieval-augmented generation, integrating Exa with LangChain, LlamaIndex, Vercel AI SDK, or implementing AI agents with web search capabilities. Triggers on: RAG pipeline, retrieval augmented generation, Exa LangChain, Exa LlamaIndex, ExaSearchRetriever, ExaSearchResults, Exa MCP, Exa tool calling, Claude tool use, AI agent web search, grounded generation, citation generation, fact checking, hallucination detection, OpenAI compatibility, chat completions.
Router skill for LLMQuant event workflows. Use when the user needs earnings event briefs, M&A tracking, regulatory risk, catalysts, event calendars, or cross-asset event impact.
Build an AI agent backend with persistent memory: one Rivet Actor per conversation, queued message handling, and streaming LLM responses as realtime events.
基于 Google 搜索的 AI 概览（AI Overview / AI Mode）抓取，针对一个关键词返回主搜索的 AI 概览要点，适合用最新网页信息做深度调研、技术问答、长尾选品分析、海外消费者偏好分析。仅支持单轮对话，如需追问须由 agent 总结上下文后发起新请求。当用户提到 Google AI、AI Overview、AI Mode、谷歌AI概览、谷歌AI搜索、海外深度调研、长尾选品调研、消费者偏好分析、网页要点总结、Google AI search, AI Overview, AI Mode, deep research, consumer preference analysis 等场景时触发此技能。即使用户未明确提到"Google AI"，只要其需求是"用谷歌搜索 + AI 总结网页要点"，也应触发此技能。
Fluxo de trabalho com IA em 3 fases — Explorar (brainstorm guiado), Planejar (plano com tarefas atômicas) e Executar (passo a passo). Ative esta skill sempre que o usuário digitar `/explorar`, `/planejar` ou `/executar`, ou quando tiver qualquer objetivo que envolva planejamento, criação ou dúvida aberta. Serve tanto para tarefas de código quanto para tarefas do mundo real (escrever, pesquisar, contatar, montar). Idioma pt-BR.
Image generation skill using Gemini Web. Generates images from text prompts via Google Gemini. Also supports text generation. Use as the image generation backend for other skills like cover-image, xhs-images, article-illustrator.
Guide for creating effective opencode skills. Use for creating or updating skills that extend agent capabilities with specialized knowledge, workflows, or tool integrations. Examples: - user: "Create a skill for git workflows" → define SKILL.md with instructions and examples - user: "Add examples to my skill" → follow the user: "query" → action pattern - user: "Update skill description" → use literal block scalar and trigger contexts - user: "Structure a complex skill" → organize with scripts/ and references/ directories - user: "Validate my skill" → check structure, frontmatter, and discovery triggers
Iteratively reviews and fixes Claude Code skill quality issues until they meet standards. Runs automated fix-review cycles using the skill-reviewer agent. Use to fix skill quality issues, improve skill descriptions, run automated skill review loops, or iteratively refine a skill. Triggers on 'fix my skill', 'improve skill quality', 'skill improvement loop'. NOT for one-time reviews—use /skill-reviewer directly.
Generate beautiful wedding invitations, save the dates, RSVP cards, and wedding programs using each::sense AI. Create classic, modern, floral, rustic, destination, and cultural wedding stationery designs.
General RPI (Research, Plan, Implement, Iterate) execution skill. It is used for engineering tasks where users require "research first, then plan, then implement, and finally iterate", or when tasks are highly complex, high-risk, or have unclear impact. This skill does not rely on specific command-line tools or platforms, and is applicable to any AI Agent that supports skill mechanisms.
Detect and auto-install missing ToolUniverse research skills by checking common client skill directories and cloning from GitHub if absent. Use when ToolUniverse specialized skills are not installed, when setting up a new project, or when the tooluniverse router skill needs to bootstrap its sub-skills before routing.
Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API. Covers building ETL workflows for AI data processing, including embedding documents into vector databases, building knowledge graphs, creating search indexes, or processing data streams with incremental updates.