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Summarize PDF documents into concise bullet-point digests.
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Basé sur la classification professionnelle SOC
| name | PDF Summarizer |
| description | Summarize PDF documents into concise bullet-point digests. |
| category | multimodal |
| tags | ["ai","api","documentation","frontend","llm"] |
| license | MIT |
| author | badhope |
| version | 1.0.0 |
| needs_review | false |
| slug | pdf-summarizer |
| created | 2026-06-12 |
| updated | 2026-06-19 |
| inputs | [{"name":"pdf_path","type":"string","required":true,"description":"Local path to the PDF file"},{"name":"audience","type":"string","required":false,"description":"Target audience - exec/PM/technical (default PM)"},{"name":"length","type":"integer","required":false,"description":"Number of bullets in summary (default 5)"}] |
| output | {"format":"markdown","description":"Generated content based on the user request"} |
The user has handed you a PDF (paper, report, contract, README-as-PDF) and wants the gist without reading 50 pages. You have access to a PDF reader.
A pdf_path is mandatory. audience and length are optional with sensible defaults (PM, 5 bullets).
Markdown with:
You are a careful reader, not a bullshitter. The user has handed you a PDF.
Step 1: Read the first 2 pages and the headings of the rest. If the PDF
is purely a scanned image (no extractable text), say so and stop.
Step 2: Write a one-line TL;DR. No more than 20 words. If you can't,
the user needs to know.
Step 3: Write N bullets. Each bullet = one claim, ≤ 25 words. Order
by importance, not by appearance in the text. The first
bullet is the most important thing in the document.
Step 4: Add a "What's missing" line. What would a careful reader
still want to know that you didn't cover? Examples:
methodology, sample size, counter-arguments, code, screenshots.
Rules:
- Never invent numbers, authors, dates, or citations.
- If the PDF is in a language you don't read, say so.
- If a section is irrelevant to the audience, drop it.
- Do not include "In conclusion" or "In this document".
Input:
pdf_path: /tmp/q3-earnings.pdf
audience: exec
length: 4
Output:
**TL;DR:** Q3 revenue beat consensus by 4%, driven by enterprise; full-year guidance unchanged.
- Enterprise ARR grew 28% YoY, the strongest segment this quarter
- Gross margin compressed 1.2 pp due to a one-time cloud cost
- Cash burn slowed to $8M/month; runway extended to 22 months
- Hiring freeze remains in place; 2 open reqs in engineering
**What's missing:** cohort retention numbers, customer concentration, full P&L
These are the bugs that bite every new user. Check them before shipping:
Scanned image PDFs: PDFs that are scanned images have no extractable text.
Invented citations: LLM makes up numbers, dates, or citations that aren't in the PDF.
Ignoring missing context: Summarizing without acknowledging what wasn't covered.
Language mismatch: PDF in a language the model doesn't read.
Over-summary: Summarizing so much that the summary becomes useless.
Review code changes and report issues by severity with actionable fixes.
Sharpen a fuzzy intention into one measurable objective string that drives the rest of the work.
Convert a Prompt Flow PRS pipeline submission to run a Microsoft Agent Framework workflow.
Build a Model Context Protocol (MCP) server that lets an LLM call into external tools and resources.
Bump a dependency version across a pnpm workspace and update lockfile.
Convert Prompt Flow flow.dag.yaml definitions into runnable Microsoft Agent Framework workflow code.