Web toolkit powered by Exa for scientific and technical content search and URL extraction.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionexa-searchExecute the skills CLI command in your project's root directory to begin installation:
Fetches exa-search from exa-labs/exa-py and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate exa-search. Access via /exa-search in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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| 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 | skill-author: Exa website: https://exa.ai docs: https://exa.ai/docs |
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.
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 |
--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.For technical or scientific queries, prefer academic and scientific sources:
Two levers to steer Exa toward scholarly content:
--category "research paper" biases retrieval toward scholarly sources.--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) in addition to the standard citation format. If a DOI is present, prefer the DOI link.
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 "$SKILL_PATH/scripts/exa_search.py" --help
If you prefer a persistent install:
uv pip install "exa-py>=1.14.0"
All commands read the API key from the EXA_API_KEY environment variable. Get your Exa API key at dashboard.exa.ai/api-keys.
First, check if a .env file exists in the project root and contains EXA_API_KEY. If so, load it:
dotenv -f .env run -- uv run --with exa-py python "$SKILL_PATH/scripts/exa_search.py" "your query"
If dotenv isn't available, install it: pip install python-dotenv[cli] or 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.
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.
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 around client.search_and_contentsscripts/exa_extract.py — CLI wrapper around client.get_contentsPrerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Solid pick for teams standardizing on skills: exa-search is focused, and the summary matches what you get after install.
exa-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in exa-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
exa-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend exa-search for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
exa-search is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
exa-search reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added exa-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
exa-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
exa-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
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