pdf-summarize

name	pdf-summarize
description	Extract the text from a PDF (local file or URL) and summarize it — abstract, key points, and notable figures or numbers. Use when a task references a PDF report, paper, contract, or manual.
metadata	{"homepage":"https://github.com/bradflaugher/LFG"}

pdf-summarize

Pull readable text out of a PDF, then summarize it. Text extraction runs through pypdf, which is preinstalled in the sandbox.

Workflow

1. Get the PDF into the workspace (skip if it's already there):

   python3 -c 'import requests, sys; open("/workspace/doc.pdf","wb").write(requests.get(sys.argv[1], timeout=60).content)' \
       "https://example.com/report.pdf"
   

2. Extract text with the helper, which prints page-tagged plain text:

   python3 /skills/*/pdf-summarize/scripts/extract.py /workspace/doc.pdf > /workspace/doc.txt
   

   Use --pages 1-10 to limit very long documents, or --max-chars N to cap.

3. Read and summarize. Skim /workspace/doc.txt, then write /workspace/summary.md:

   • One-paragraph overview of what the document is and its purpose.
   • 3–6 bullet key points (decisions, findings, obligations…).
   • A short list of any important figures, dates, or names, with the page they appear on.

Rules

• If extraction returns little or no text, the PDF is probably scanned images — say so; OCR is out of scope here.
• Attribute claims to page numbers when you can (p.4).
• Never invent content that isn't in the extracted text. If something is ambiguous in the source, flag it rather than guessing.