Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add krishagel/geoffrey --skill pdf-to-markdowngit clone --depth 1 https://github.com/krishagel/geoffreyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/krishagel/geoffrey/pdf-to-markdown)<a href="https://agentmods.dev/skills/krishagel/geoffrey/pdf-to-markdown"><img src="https://agentmods.dev/badge/skills/krishagel/geoffrey/pdf-to-markdown/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/krishagel/geoffrey/pdf-to-markdown"><img src="https://agentmods.dev/badge/skills/krishagel/geoffrey/pdf-to-markdown.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.00559 |
| Opus 5.5 | $0.00016 | $0.00224 |
| Sonnet 5.5 | $0.00008 | $0.00112 |
| Haiku 4.5 | $0.00004 | $0.00056 |
Grade A, and why
pdf-to-markdown scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- pdf-to-markdown — 94% identical, 2 lines differ
What it actually says
PDF to Markdown Converter
Convert PDF files to clean, well-structured Markdown. Tables become markdown tables. Images and graphics are described as text (no image files generated).
Quick Start
uv run skills/pdf-to-markdown/scripts/convert_to_markdown.py input.pdf
Output: ~/Desktop/{filename}.md
Options
| Flag | Description |
|---|---|
--no-llm |
Skip LLM processing (faster, images become [Image] placeholders) |
--force-ocr |
Force OCR on all pages (for scanned PDFs) |
--page-range "0,5-10" |
Process specific pages only |
Common Use Cases
Convert a PDF with default settings
uv run skills/pdf-to-markdown/scripts/convert_to_markdown.py ~/Documents/report.pdf
Specify output location
uv run skills/pdf-to-markdown/scripts/convert_to_markdown.py report.pdf ~/Documents/report.md
Fast conversion (no image descriptions)
uv run skills/pdf-to-markdown/scripts/convert_to_markdown.py --no-llm report.pdf
Scanned PDF (force OCR)
uv run skills/pdf-to-markdown/scripts/convert_to_markdown.py --force-ocr scanned_doc.pdf
Extract specific pages
uv run skills/pdf-to-markdown/scripts/convert_to_markdown.py --page-range "0-5" large_report.pdf
Output
- Pure Markdown text (no embedded images)
- Tables converted to Markdown table format
- Images/charts described as text using LLM
- Clean formatting suitable for AI processing
Requirements
- GEMINI_API_KEY: Required for LLM image descriptions (loaded from 1Password)
- Use
--no-llmflag if you don't have Gemini API access
First Run Note
The first run downloads ML models (~1-2GB) which are cached at ~/.cache/marker/. Subsequent runs are faster.
Technical Details
Uses Marker library:
- 31k+ GitHub stars
- Best-in-class PDF conversion accuracy
- Surya OCR for 90+ languages
- Gemini LLM integration for image understanding
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 78 lines · 41 tokens per session scan A 49edec9d806b
pdf-to-markdown is a skill published in the GitHub repository krishagel/geoffrey (7 stars, last pushed 7mo ago), licensed MIT. It adds 41 tokens to every session and 559 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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