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/exa-search

Exa search API key.

From plugin
k-dense-ai-scientific-agent-skills-2
45k165 skills
Install
$ npx -y skills add K-Dense-AI/scientific-agent-skills --skill exa-search --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/exa-search

Context preview

The summary Claude sees to decide when to auto-load this skill.

Exa search API key.

SKILL.md

exa-search.SKILL.md
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](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:

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](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:

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 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`
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Repo: K-Dense-AI/scientific-agent-skills