URL Extraction

Extract content from: $ARGUMENTS

Command

Choose a short, descriptive filename based on the URL or content (e.g., alphafold-paper, nature-editorial). Use lowercase with hyphens, no spaces.

bash

uv run --with exa-py python "$SKILL_PATH/scripts/exa_extract.py" "$ARGUMENTS" \
  --text \
  -o "$FILENAME.json"

You can pass multiple URLs as positional arguments — the script batches them in a single /contents call, which is faster and cheaper than looping.

Content modes:

--text (default if nothing else is passed) returns full-text content
--highlights returns extracted passages instead of full text

Academic content handling

When extracting from academic sources (arXiv, PubMed, journal sites, conference proceedings), use --text to get the full paper text:

bash

uv run --with exa-py python "$SKILL_PATH/scripts/exa_extract.py" "$URL" \
  --text \
  -o "$FILENAME.json"

For arXiv, either the /abs/ page URL or the raw PDF URL works. Prefer /abs/ when available — it has cleaner metadata (title, authors, published date) attached to the result.

Response format

Return content as:

Page Title

For academic papers, include structured metadata when available:

Authors: list of authors (from the author field)
Published: from published_date

Then the extracted content, with these rules:

Keep content verbatim — do not paraphrase or summarize
Parse lists exhaustively — extract EVERY numbered/bulleted item
Strip only obvious noise: nav menus, footers, ads
Preserve all facts, names, numbers, dates, quotes
For academic papers, preserve figure/table captions and references

Partial-result handling — when batching multiple URLs, one or more may fail (paywall, robots.txt, timeout). Report which URLs extracted successfully and which failed, rather than silently dropping failures.

After the response, mention the output file path ($FILENAME.json) so the user knows it's available for follow-up questions.