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 nobodyohm-web/Thot --skill nano-pdfgit clone --depth 1 https://github.com/nobodyohm-web/ThotWrote 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/nobodyohm-web/thot/nano-pdf)<a href="https://agentmods.dev/skills/nobodyohm-web/thot/nano-pdf"><img src="https://agentmods.dev/badge/skills/nobodyohm-web/thot/nano-pdf/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/nobodyohm-web/thot/nano-pdf"><img src="https://agentmods.dev/badge/skills/nobodyohm-web/thot/nano-pdf.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 | $0.00014 | $0.00419 |
| Opus 5 | $0.00007 | $0.00210 |
| Sonnet 5 | $0.00003 | $0.00084 |
| Haiku 4.5 | $0.00001 | $0.00042 |
Grade A, and why
nano-pdf 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 7d 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.
This is a copy
100% identical to nano-pdf — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
nano-pdf
Edit PDFs using natural-language instructions. Point it at a page and describe what to change. For structural PDF work (merge, split, forms, watermarks, creation), see the pdf skill; for text extraction from scans, see ocr-and-documents.
Prerequisites
# Install with uv (recommended — already available in Hermes)
uv pip install nano-pdf
# Or with pip
pip install nano-pdf
Usage
nano-pdf edit <file.pdf> <page_number> "<instruction>"
Examples
# Change a title on page 1
nano-pdf edit deck.pdf 1 "Change the title to 'Q3 Results' and fix the typo in the subtitle"
# Update a date on a specific page
nano-pdf edit report.pdf 3 "Update the date from January to February 2026"
# Fix content
nano-pdf edit contract.pdf 2 "Change the client name from 'Acme Corp' to 'Acme Industries'"
Notes
- Page numbers may be 0-based or 1-based depending on version — if the edit hits the wrong page, retry with ±1
- Always verify the output PDF after editing (use
read_fileto check file size, or open it) - The tool uses an LLM under the hood — requires an API key (check
nano-pdf --helpfor config) - Works well for text changes; complex layout modifications may need a different approach
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.
- 7d ago First seen · 54 lines · 14 tokens per session scan A e0bdce5fe2d2
nano-pdf is a skill published in the GitHub repository nobodyohm-web/Thot (0 stars, last pushed 16d ago), licensed MIT. It adds 14 tokens to every session and 419 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to nano-pdf, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
PDF files: create, read, merge, fill, OCR, edit text.
pdf-toolkit
Structured .pdf operations: extract text/tables, merge pages from multiple PDFs, split a PDF by page ranges, fill PDF form fields, and generate fresh PDFs from JSON. Trigger when the user wants programmatic PDF work without natural-language rewriting — examples: pull tables from a report, combine three PDFs, extract…
nano-pdf
Edit PDFs with natural-language instructions using the nano-pdf CLI.
parse-document
Convert a PDF, scan, image of a page, or office file to clean markdown through the connected Superlinked MCP edge, so the source document is not read into model context directly. Use when the user asks to read, parse, OCR, extract from, summarize, or answer questions about a document.
pdf-explore
Use this skill when the user has attached a PDF, paper, report, or other document and the answer needs content from more than one place in it: summarize the methods or any other section, compare sections, find where a topic is discussed, read a value or label off a figure or chart, or find/list/extract every instance…
smart-data-collection
A workflow for extracting structured information from images and documents such as PDFs, Word files, and spreadsheets, then storing it in a database.