Skills your agents can run

Audit, planning, and implementation of SEO improvements across technical SEO, on‑page optimization, structured data, Core Web Vitals, and content strategy. Use when users want to improve search visibility, apply SEO fixes, implement schema markup, work on sitemaps/robots, or perform keyword-to-URL mapping.

Neural search for web, code, and corporate investigations via Exa MCP. Use when a user needs web searches, code examples, company information, people lookup, or AI-driven deep investigations using Exa's neural search engine.

Search and summarize papers from ArXiv. Use when the user asks for the latest research, specific topics on ArXiv, or a daily summary of AI papers.

Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.

Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).

Search published venue papers (IEEE, ACM, Springer, etc.) via Semantic Scholar API. Complements /arxiv (preprints) with citation counts, venue metadata, and TLDR. Use when user says "search semantic scholar", "find IEEE papers", "find journal papers", "venue papers", "citation search", or wants published literature beyond arXiv preprints.

Web search and content extraction via SearXNG. No API keys, no rate limits. Available in containerized agents via the eddo-chat Docker network.

When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' or 'optimize for Claude/Gemini.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema-markup.

Google web search via Gemini Search Grounding (primary) and Custom Search JSON API (fallback). Use for: (1) Synthesized answers with citations (grounded search), (2) Raw link results with snippets, (3) Image search. Excellent Hebrew support. Preferred over built-in web_search (Perplexity).

Parse Windows Prefetch files to determine program execution history, including run counts, timestamps, and referenced files, for forensic investigations.

Search the web or X/Twitter using xAI Grok server-side tools (web_search, x_search) via the xAI Responses API. Use when you need tweets/threads/users from X, want Grok as an alternative to Brave, or you need structured JSON + citations.

Academic writing, research methodology, and scholarly communication workflows. Use when writing papers, literature reviews, grant proposals, conducting research, managing citations, or preparing for peer review. Essential for researchers, graduate students, and academics across disciplines.

Search the arXiv preprint repository for papers in physics, mathematics, computer science, quantitative biology, and related fields. Instructions for searching arXiv papers using a Python script and shell tool. Read SKILL.md to learn the workflow.

This skill should be used when user asks to "search for papers", "find research papers", "search arXiv", "search PubMed", "find academic papers", "search IEEE", "search Scopus", or "look up scientific literature".

Conduct comprehensive multi-source research for complex questions. Use when the user asks a complicated question requiring multiple sources, in-depth analysis, cross-referencing, or expert-level research reports. Triggers on "research", "investigate", "deep dive", "analyze thoroughly", "comprehensive report", or questions involving conflicting sources.

USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity. Supports Goggles, local/POI. For AI answers use answers. Recommended for anyone building AI/agentic applications.

SEO & GEO (Generative Engine Optimization) for websites. Analyze keywords, generate schema markup, optimize for AI search engines (ChatGPT, Perplexity, Gemini, Copilot, Claude) and traditional search (Google, Bing). Use when user wants to improve search visibility.

RAG and semantic search via OpenViking Context Database MCP server. Query documents, search knowledge base, add files/URLs to vector memory. Use for document Q&A, knowledge management, AI agent memory, file search, semantic retrieval. Triggers on "openviking", "search documents", "semantic search", "knowledge base", "vector database", "RAG", "query pdf", "document query", "add resource".

百度 AI 搜索。支持网页搜索、百度百科、秒懂百科、AI 智能生成四种模式。自动包含当前日期上下文。当用户要求搜索信息、查询百科、获取最新资讯、搜索新闻、查找资料时使用。

Monitor topics of interest and proactively alert when important developments occur. Use when the user wants automated monitoring of specific subjects (e.g., product releases, price changes, news topics, technology updates). Supports scheduled web searches, AI-powered importance scoring, smart alerts versus weekly digests, and memory-aware contextual summaries.