AI-powered web search via Exa with content extraction. Use when user says "exa search", "web search with content", "find similar pages", or needs broad web results beyond academic databases (arXiv, Semantic Scholar).

Exa AI Powered Web Search Search query: $ARGUMENTS Role & Positioning Exa is the broad web search source with built in content extraction: Skill Best for /arxiv Direct preprint search and PDF download /semantic scholar Published venue papers (IEEE, ACM, Springer), citation counts /deepxiv Layered reading: search, brief, section map, section reads /exa search Broad web search: blogs, docs, news, companies, research papers — with content extraction Use Exa when you need results beyond academic databases, or when you want content (highlights, full text, summaries) extracted alongside search results. Constants EXA FETCHER — canonical name exa search.py , resolved per [ shared references/integration contract.md ](../shared references/integration contract.md) §2 (Policy D1 — standalone /exa search has no documented fallback, so unresolved helper terminates with an explicit error). MAX RESULTS = 10 — Default number of results to return. Overrides (append to arguments): /exa search "RAG pipelines" — max: 5 — top 5 results /exa search "diffusion models" — category: research paper — research papers only /exa search "startup funding" — category: news, start date: 2025 01 01 — recent news /exa search "transformer" — content: text, max chars: 8000 — full text mode /exa search "transformer" — content: summary — LLM generated summaries /exa search "transformer" — domains: arxiv.org,huggingface.co — domain filter /exa search "https://arxiv.org/abs/2301.07041" — similar — find similar pages Setup Exa requires the exa py SDK and an API key: Set your API key: Get a key from [exa.ai](https://exa.ai). Workflow Step 1: Parse Arguments Parse $ARGUMENTS for: query : The search query (required) or a URL (for find similar mode) similar : If present, use find similar mode instead of search max : Override MAX RESULTS category : research paper , news , company , personal site , financial report , people content : highlights (default), text , summary , none max chars : Max characters for content extraction type : Search type — auto (default), neural , fast , instant domains : Comma separated include domains exclude domains : Comma separated exclude domains include text : Phrase that must appear in results exclude text : Phrase to exclude from results start date : ISO 8601 date — only results after this end date : ISO 8601 date — only results before this location : Two letter ISO country code Step 2: Locate Script Resolve $EXA FETCHER via the canonical strict safe chain (see [ shared references/integration contract.md ](../shared references/integration contract.md) §2). Policy D1 cascade: there is no native inline fallback for Exa (retrieval requires the exa py SDK + API key, which lives in the fetcher), so unresolved helper means the SKILL cannot produce its primary output — fail with explicit remediation. Step 3: Execute Search Standard search: With filters: Find similar pages: Get content for known URLs: Step 4: Present Results Format results as a structured table: For each result: Show title and URL Show published date if available Show highlights, text excerpt, or summary depending on content mode Flag particularly relevant results For category: "research paper" hits only — also record authors (from Exa's author / authors fields, or fallback: parse from the result snippet) and venue/publisher (from publisher , source , or the domain hosting the paper). These are needed by Step 6's wiki hook; if either is unavailable for a given hit, skip wiki ingest for that one hit and log a note. Step 5: Offer Follow up After presenting results, suggest: Deepen : "I can fetch full text for any of these results" Find similar : "I can find pages similar to any result" Narrow : "I can re search with domain/date/text filters" Step 6: Update Research Wiki (if active, research paper results only) Required when research wiki/ exists AND the search returned results of category: "research paper" ; skip silently otherwise. General web results (blog posts, docs, news) are not ingested — the wiki is for papers only. When the predicates hold, resolve $WIKI SCRIPT per the canonical chain at [ shared references/wiki helper resolution.md ](../shared references/wiki helper resolution.md) (Variant B — warn and skip). For each research paper hit, try to recover an arXiv ID from the URL ( arxiv.org/abs/<id ); if present, use arxiv id . Otherwise fall back to manual metadata: The helper handles slug / dedup / page / index / log — do not handwrite papers/<slug .md . See [ shared references/integration contract.md ](../shared references/integration contract.md). Key Rules Always check that EXA API KEY is set before searching Default to highlights content mode for a good balance of speed and context Use category: "research paper" when the user is clearly looking for academic content Use text content mode when the user needs full page content Combine with /arxiv or /semantic scholar for comprehensive literature coverage

exa-search