# PDF Understanding

> PDF Understanding is an Agent Skill for documents published in the B-M-Capital-Research/honeclaw repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Read and analyze user-uploaded PDFs, preferably using the system-extracted text fragments, and output summaries, key points, and risk notes

- Skill name: `PDF Understanding`
- Category: [Documents](https://www.openparable.com/skill/documents/1)
- Source: https://github.com/B-M-Capital-Research/honeclaw/blob/HEAD/skills/pdf_understanding/SKILL.md
- Repository: B-M-Capital-Research/honeclaw (742 GitHub stars when collected)

## SKILL.md

## PDF Understanding Skill

When the message contains a `【PDF extraction text】` block, the system has already attempted to extract text from the PDF. Follow the flow below.

### Standard Flow

1. Identify the user's goal first: summary, Q&A, risk scan, financial metric extraction, investment judgment, and so on
2. Prefer the content in `【PDF extraction text】` and answer with a structured conclusion:
   - Core conclusion (1-3 points)
   - Key evidence (important text points from the PDF)
   - Uncertain or missing items
3. If extraction failed or the text is insufficient, which is common for scanned PDFs:
   - State clearly that the current PDF text is insufficient
   - Ask the user for OCR text, a key-page screenshot, or a specific page number
4. If the user's question requires external fact checking, add tools:
   - `web_search(query="...")` for news, announcements, or industry context
   - `data_fetch(...)` for real-time market or company data

### Output Requirements

- Do not guess conclusions that are not present in the PDF
- When citing evidence, stay close to the original wording and avoid inventing numbers
- Keep the output concise and actionable for a chat setting

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