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Prompts Exa Scientific Web Search Toolkit

agent research skill risk: low

Exa Scientific Web Search Toolkit

Defines routing, capabilities, and setup for an Exa-powered web toolkit that performs semantic web searches (with optional research-paper filtering and academic domain restrictions…

  • External action: medium

SKILL 6 files · 3 folders

SKILL.md
---
name: scientific-agent-skills-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 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:

```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`

REQUIRED CONTEXT

  • user request or URL

OPTIONAL CONTEXT

  • category
  • include-domains

TOOLS REQUIRED

  • web_search
  • web_extract

ROLES & RULES

  1. Read the user's request and match it to one of the capabilities below.
  2. Read the corresponding reference file for detailed instructions before running commands.
  3. Default to Web Search for topic lookups, research questions, or "what is X?" queries.
  4. Use Web Extract when the user provides a URL or asks you to read/fetch a specific page.
  5. Prefer academic and scientific sources for technical or scientific queries.
  6. When citing academic sources, include author names and publication year where available.
  7. Do not remove or rename this header when adapting the scripts.

EXPECTED OUTPUT

Format
markdown
Constraints
  • follow routing table and decision guide
  • prefer academic sources for scientific queries
  • use specified scripts and env vars for execution

SUCCESS CRITERIA

  • Match user request to correct capability (Web Search or Web Extract).
  • Apply academic source priority for scientific queries.
  • Use --category and --include-domains for scholarly results when appropriate.
  • Include author names, year, and DOI links when citing academic sources.

FAILURE MODES

  • May skip reading reference files before executing commands.
  • May fail to apply academic filtering for scientific topics.
  • May omit required citation details for academic sources.

CAVEATS

Dependencies
  • references/web-search.md
  • references/web-extract.md
  • EXA_API_KEY environment variable
  • exa-py Python SDK
Missing context
  • Content of referenced files (references/web-search.md, references/web-extract.md)
  • Definition of $SKILL_PATH environment variable
Ambiguities
  • Description field is truncated mid-sentence ('URL extra')

QUALITY

OVERALL
0.72
CLARITY
0.80
SPECIFICITY
0.85
REUSABILITY
0.70
COMPLETENESS
0.60

IMPROVEMENT SUGGESTIONS

  • Complete the truncated description in the YAML frontmatter.
  • Either inline the referenced .md files or provide explicit placeholders for them.

USAGE

Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.

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