exa-search
k-dense-ai/scientific-agent-skills
Web search and content extraction powered by Exa, optimized for scientific and technical research.
What is exa-search?
Exa-search provides semantic web search and batch URL content extraction tuned for high-quality scientific and technical sources. Use it when you need to research topics, find current information, or fetch specific web pages and academic PDFs, with optional filtering by research-paper category and academic domains.
- Semantic web search with keyword and semantic retrieval for scientific and technical queries
- Research-paper category filtering to bias results toward peer-reviewed journals and scholarly sources
- Academic domain allowlisting to restrict searches to institutional, preprint, and journal sources
- Batch URL extraction for fetching multiple webpages, articles, and academic PDFs in one call
- Current information retrieval and topic research across the indexed web
How to install exa-search
npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill exa-search- EXA_API_KEY environment variable set with a valid Exa API key from dashboard.exa.ai/api-keys
- exa-py Python SDK (version ≥1.14.0)
- Internet access
- uv (Python script runner) or pip for dependency management
How to use exa-search
- 1.Set the EXA_API_KEY environment variable with your Exa API key
- 2.For web search: run `uv run --with exa-py python exa_search.py "your query"` with optional flags like `--category "research paper"` for academic filtering or `--include-domains` for domain allowlisting
- 3.For URL extraction: run `uv run --with exa-py python exa_extract.py <url1> <url2> ...` to fetch content from multiple URLs at once
- 4.For academic queries, combine `--category "research paper"` with `--include-domains arxiv.org,nature.com,pubmed.ncbi.nlm.nih.gov` to prioritize peer-reviewed and institutional sources
- 5.Review the references in `references/web-search.md` and `references/web-extract.md` for detailed command options and academic search strategies
Use cases
- Search for peer-reviewed research on a scientific topic with academic source priority
- Fetch and extract content from multiple URLs (articles, PDFs, webpages) in batch
- Look up current information or news on a technical topic with semantic search
- Find preprints and institutional sources (arXiv, bioRxiv, NIH, NASA) for a research question
- Extract text from a specific academic PDF or journal article by URL
- Researchers and scientists conducting literature reviews
- Technical writers and engineers researching implementation details
- Students and academics seeking peer-reviewed sources
- Data scientists and analysts gathering current information
- Anyone needing high-quality web search with scholarly filtering
exa-search FAQ
Use exa-search for semantic topic research, academic source filtering, and batch URL extraction. It's optimized for scientific queries and can fetch multiple URLs in one call; use built-in WebFetch only for simple single-URL retrieval.
Pass `--category "research paper"` to bias toward scholarly sources, and optionally use `--include-domains arxiv.org,nature.com,pubmed.ncbi.nlm.nih.gov` to restrict results to academic domains. Combine both flags for strictly scholarly results.
It can extract text from webpages, news articles, blog posts, and academic PDFs. Provide one or more URLs and it will batch-fetch and return the content from all of them.
No. The scripts use PEP 723 inline metadata, so you can run them directly with `uv run --with exa-py` without a separate install. Alternatively, install persistently with `uv pip install exa-py>=1.14.0`.
Export EXA_API_KEY for your session: `export EXA_API_KEY="your-key"`. Get your key from dashboard.exa.ai/api-keys. If a .env file exists, use `dotenv -f .env run --` before your command.
Full instructions (SKILL.md)
Source of truth, from k-dense-ai/scientific-agent-skills.
name: exa-search description: "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 extraction (fetching pages, articles, academic PDFs in batch). Use this skill for web-related tasks when the user wants high-quality search or scholarly filtering via category=research paper. Triggers on requests to search, look up, fetch a page, or extract an article." compatibility: Requires exa-py Python SDK, an EXA_API_KEY, and internet access. license: MIT metadata: version: "1.2" skill-author: Exa website: https://exa.ai docs: https://exa.ai/docs openclaw: primaryEnv: EXA_API_KEY envVars: - name: EXA_API_KEY required: true description: Exa search API key.
Exa Web Toolkit
A skill for web-powered research tasks backed by Exa: 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-domainsallowlist. Seereferences/web-search.mdfor 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:
--category "research paper"biases retrieval toward scholarly sources.--include-domainswith 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) in addition to the standard citation format. If a DOI is present, prefer the DOI link.
Setup
This skill uses the 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:
uv run --with exa-py python "$SKILL_PATH/scripts/exa_search.py" --help
If you prefer a persistent install:
uv pip install "exa-py>=1.14.0"
Authentication
All commands read the API key from the EXA_API_KEY environment variable. Get your Exa API key at dashboard.exa.ai/api-keys.
First, check if a .env file exists in the project root and contains EXA_API_KEY. If so, load it:
dotenv -f .env run -- uv run --with exa-py python "$SKILL_PATH/scripts/exa_search.py" "your query"
If dotenv isn't available, install it: uv pip install python-dotenv[cli].
If there's no .env, export the key for the session:
export EXA_API_KEY="your-key"
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 strategyreferences/web-extract.md— URL content extraction referencescripts/exa_search.py— CLI wrapper aroundclient.search_and_contentsscripts/exa_extract.py— CLI wrapper aroundclient.get_contents
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