--- id: K-Dense-AI/scientific-agent-skills/exa-search version: "12eb278e" license: MIT install: manual updated: 2026-07-28 --- # exa-search — Exa-search combines keyword and semantic web retrieval for research-grade lookups on scientific and technical topics. Route queries to web search for topic research or URL extraction for fetching specific pages and academic PDFs. Use category filters and domain allowlists to prioritize peer-reviewed journals, preprints, and institutional sources. Publisher: K-Dense-AI · Stars: 31940 · Updated: 2026-07-28 Install (manual): `git clone https://github.com/K-Dense-AI/scientific-agent-skills` ## SKILL.md # 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: ```bash uv run --with exa-py python "$SKILL_PATH/scripts/exa_search.py" --help ``` If you prefer a persistent install: ```bash uv pip install "exa-py>=1.14.0" ``` ### Authentication All commands read the API key from the `EXA_API_KEY` environment variable. Get your Exa API key at [dashboard.exa.ai/api-keys](https://dashboard.exa.ai/api-keys). First, check if a `.env` file exists in the project root and contains `EXA_API_KEY`. If so, load it: ```bash dotenv -f .env run -- uv run --with exa-py python "$SKILL_PATH/scripts/exa_search.py" "your query" ``` If `dotenv` isn't available, install it: `pip install python-dotenv[cli]` or `uv pip install python-dotenv[cli]`. If there's no `.env`, export the key for the session: ```bash 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 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` [View on SkillFed](https://skillfed.io/K-Dense-AI/scientific-agent-skills/exa-search) · [View on GitHub](https://github.com/K-Dense-AI/scientific-agent-skills)