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 graniet/kheish --skill nano-pdfgit clone --depth 1 https://github.com/graniet/kheishWrote 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/graniet/kheish/nano-pdf)<a href="https://agentmods.dev/skills/graniet/kheish/nano-pdf"><img src="https://agentmods.dev/badge/skills/graniet/kheish/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/graniet/kheish/nano-pdf"><img src="https://agentmods.dev/badge/skills/graniet/kheish/nano-pdf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00034 | $0.00517 |
| Opus 5 | $0.00017 | $0.00259 |
| Sonnet 5 | $0.00007 | $0.00103 |
| Haiku 4.5 | $0.00003 | $0.00052 |
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 6d 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.
What it actually says
Kheish Compatibility
This skill is repo-local and stays inactive until explicitly activated.
When the original instructions refer to legacy tool names, use these Kheish mappings:
terminal=>bashweb_extract=>web_fetch, plusweb_searchwhen discovery is neededsearch_files=>grep_searchandglob_searchbrowser_*tools require a browser-capable surfaced tool or MCP; if none is available, use the closest available surface and say so explicitly
When the instructions mention local helper files, resolve them from ${KHEISH_SKILL_DIR}.
nano-pdf
Edit PDFs using natural-language instructions. Point it at a page and describe what to change.
Prerequisites
# Install with uv (recommended — already available in Kheish)
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.
- 6d ago First seen · 71 lines · 34 tokens per session scan A f4c5368db786
nano-pdf is a skill published in the GitHub repository graniet/kheish (227 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 34 tokens to every session and 517 once invoked, about $0.0002 per session on Opus 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 2026-09-03.
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Use when extracting text, tables, or content from PDF documents.
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