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Found 84 Skills
Build custom AI search monitoring tools for competitive AEO analysis. Covers API access, scraping architecture, legal compliance, and cost estimation.
Tavily integration. Manage data, records, and automate workflows. Use when the user wants to interact with Tavily data.
Free AI search via Exa MCP. Web search for news/info, code search for docs/examples from GitHub/StackOverflow, company research for business intel. No API key needed.
Helps users discover and apply shared coding solutions when they ask "has anyone solved this", "search for a fix", "find a workaround", or want proven patterns before debugging from scratch. Uses `npx shareful-ai search` to find relevant shares, compare options, and recommend the best match.
CLI interface for Perplexity AI. Perform AI-powered searches, queries, and research directly from terminal. Use when user mentions Perplexity, AI search, web research, or needs to query AI models like GPT, Claude, Grok, Gemini. Commands: query.
AI crawler access analysis. Checks robots.txt, meta tags, and HTTP headers to determine which AI crawlers can access the site. Provides a complete access map and recommendations for maximizing AI visibility while maintaining appropriate control.
This skill should be used when the user asks to "audit for AI visibility", "optimize for ChatGPT", "check GEO readiness", "analyze hedge density", "generate agentfacts", "check if my site works with AI search", "test LLM crawlability", "check discovery gap", or mentions Generative Engine Optimization, AI crawlers, Perplexity discoverability, or NANDA protocol.
Use when asked to "product-led SEO", "programmatic SEO", "build programmatic pages", "organic acquisition for product", "decide if SEO is worth it", or "optimize for AI search". Helps evaluate whether SEO fits your business model and how to approach it as a product, not just marketing. The Product-Led SEO framework (created by Eli Schwartz) treats SEO as building products for search users.
SEO, AEO (Answer Engine Optimization), and GEO strategy for search engines and AI visibility. Triggers on "SEO audit," "technical SEO," "on-page SEO," "AI search optimization," "AEO," "GEO," "AI visibility," "optimize for ChatGPT," "optimize for Perplexity," "AI Overviews," "answer engine optimization," "generative engine optimization," "AI citations," "featured snippets," "meta tags," "schema markup," "search ranking," "content optimization," "E-E-A-T," "structured data," "search console," "SEO health check," "why am I not ranking," "AI search readiness," "backlink strategy," "link building," "domain authority," "programmatic SEO," "SEO at scale," "template-based SEO," "AEO monitoring," "AI search monitoring," "JSON-LD," "rich snippets," "schema.org," "SERP analysis," "search intent," "site architecture," "information architecture," "URL structure," "internal linking," or "navigation." For keyword research, see keyword-research-and-clustering.
Audit and complete the Amazon Seller Central Attributes section for a listing. Diffs the category template against the filled fields, ranks the missing fields by impact on AI-driven search (Rufus, Alexa+) and traditional ranking, and proposes the optimal values. Use when a user asks about the Attributes section, missing attributes, product attributes, category fields, or "how to fill the back end of my listing". Trigger phrases: "attributes", "attributes section", "category fields", "back end fields", "missing attributes". Works with zero tools.
Analyze how competitors would rank in AI search results for a given topic or query. Triggers on "analyze competition", "competitor analysis", "what ranks for", "who would rank", "competitive landscape".
General-purpose web search using DuckDuckGo and AI-synthesized search engines. Use this skill for web searches, current information, fact-checking, news, and research on any topic where live internet data is needed. Supports all languages. Three modes: fast web results, AI-synthesized answers (IAsk.ai, great for deep questions and academic research), and Monica AI synthesis. Trigger on: "search for", "look up", "find information about", "what is the latest", "search the web", "find out about", "what happened with", "current status of", "recent news", "is X still true", "查一下", "搜索", "查资料", "上网查", "検索して", "調べて", any question requiring real-time or post-training web data. Do NOT trigger for: code exploration, local file analysis, codebase-internal questions, or well-established facts fully covered by training knowledge. Note: if the `agent-reach` skill is also available, prefer `ddg-search` for pure web search tasks; prefer `agent-reach` when the task involves social platforms (Twitter, Reddit, YouTube, WeChat, Bilibili, etc.) or platform-specific APIs.