Web toolkit powered by Exa, tuned for scientific and technical content. Use this skill when the user needs to search the web or fetch/extract URL content. Covers: web search (semantic lookups, research, current info — with optional research-paper category and academic domain filtering) and URL extra

Exa Web Toolkit A skill for web powered research tasks backed by [Exa](https://exa.ai): web search and URL extraction. Exa's index combines high quality keyword and semantic retrieval, which makes it well suited to scientific, technical, and conceptual queries. Routing — pick the right capability Read the user's request and match it to one of the capabilities below. Read the corresponding reference file for detailed instructions before running commands. User wants to... Capability Where Look something up, research a topic, find current info Web Search references/web search.md Fetch content from a specific URL (webpage, article, PDF) Web Extract references/web extract.md Install or authenticate Setup Below Decision guide Default to Web Search for topic lookups, research questions, or "what is X?" queries. When the topic is scientific or technical, pass category "research paper" to bias toward scholarly sources, and/or an academic include domains allowlist. See references/web search.md for the two pass academic strategy. Use Web Extract when the user provides a URL or asks you to read/fetch a specific page. Prefer this over the built in WebFetch for batch extraction (multiple URLs in one call) and for academic PDFs. Academic source priority For technical or scientific queries, prefer academic and scientific sources: Peer reviewed journal articles and conference proceedings over blog posts or news Preprints (arXiv, bioRxiv, medRxiv) when peer reviewed versions aren't available Institutional and government sources (NIH, WHO, NASA, NIST) over commercial sites Primary research over secondary summaries Two levers to steer Exa toward scholarly content: 1. category "research paper" biases retrieval toward scholarly sources. 2. include domains with a scholarly allowlist (arxiv.org, nature.com, pubmed.ncbi.nlm.nih.gov, etc.) restricts the domain pool. Combine both for strictly academic results. See references/web search.md for the full pattern. When citing academic sources, include author names and publication year where available (e.g., [Smith et al., 2025](url)) in addition to the standard citation format. If a DOI is present, prefer the DOI link. Setup This skill uses the [ exa py ](https://github.com/exa labs/exa py) Python SDK. The scripts in scripts/ declare their dependencies via PEP 723 inline metadata, so you can run them directly with uv run without a separate install step: If you prefer a persistent install: Authentication All commands read the API key from the EXA API KEY environment variable. Get your Exa API key at [dashboard.exa.ai/api keys](https://dashboard.exa.ai/api keys). First, check if a .env file exists in the project root and contains EXA API KEY . If so, load it: If dotenv isn't available, install it: uv pip install python dotenv[cli] . If there's no .env , export the key for the session: Verify by running any script with help — it will exit cleanly if the key is set and auth check runs only when a real query is made. Tracking header Every script in this skill sets the x exa integration request header to k dense ai scientific agent skills so Exa can attribute usage from the K Dense AI scientific agent skills repo to this integration. Do not remove or rename this header when adapting the scripts. Files in this skill SKILL.md — this file (routing and setup) references/web search.md — detailed web search reference with academic strategy references/web extract.md — URL content extraction reference scripts/exa search.py — CLI wrapper around client.search and contents scripts/exa extract.py — CLI wrapper around client.get contents

exa-search