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 jnPiyush/AgentX --skill pdfgit clone --depth 1 https://github.com/jnPiyush/AgentXWrote 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/jnpiyush/agentx/pdf)<a href="https://agentmods.dev/skills/jnpiyush/agentx/pdf"><img src="https://agentmods.dev/badge/skills/jnpiyush/agentx/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/jnpiyush/agentx/pdf"><img src="https://agentmods.dev/badge/skills/jnpiyush/agentx/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 | $0.00058 | $0.01987 |
| Opus 5.5 | $0.00023 | $0.00795 |
| Sonnet 5.5 | $0.00012 | $0.00397 |
| Haiku 4.5 | $0.00006 | $0.00199 |
Grade A, and why
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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Practical patterns for reading, writing, and transforming PDF files in Python and from the shell.
Prerequisites
- Python 3.9+
- Pick libraries by task (install only what you need):
pypdf-- merge, split, rotate, encrypt, light text extraction, form fieldspdfplumber-- structured text and table extraction with positional inforeportlab-- generate new PDFs from codepdfminer.six-- low-level text extraction whenpdfplumberis not enoughpdf2image+pytesseract-- OCR scanned PDFs (needs Poppler + Tesseract installed)
- Shell tools (optional):
qpdf,pdftotext,pdfimagesfrom Poppler
When to Use
- The input or output of the task is a
.pdffile - You need to pull text or tables out of a PDF for downstream processing
- You need to assemble, split, or modify existing PDFs
- You need to generate a PDF report from data
- You need to fill an existing PDF form or apply a watermark
Library Selection
| Goal | Prefer | Notes |
|---|---|---|
| Merge / split / rotate | pypdf |
Fast, pure Python, no native deps |
| Reliable text + tables | pdfplumber |
Best for layout-aware extraction |
| Last-resort raw text | pdfminer.six |
Lower level than pdfplumber |
| Create a new PDF | reportlab |
Flowables for reports, canvas for fixed layout |
| Scanned PDFs (image-only) | pdf2image + pytesseract |
Requires Poppler + Tesseract on PATH |
| Forms (AcroForm) | pypdf |
Use update_page_form_field_values |
| Heavy CLI batch ops | qpdf |
Robust, deterministic |
Read Text
import pdfplumber
def extract_text(path: str) -> str:
parts: list[str] = []
with pdfplumber.open(path) as pdf:
for page in pdf.pages:
text = page.extract_text() or ""
parts.append(text)
return "\n\n".join(parts)
Tips:
extract_text()returnsNonefor image-only pages -- fall back to OCR.- Use
page.crop(bbox).extract_text()to scope to a region.
Extract Tables
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.
- 1mo ago Changed 2eb6102fbcc7
- 1mo ago First seen · 231 lines · 58 tokens per session scan A b05caa668e97
pdf is a skill published in the GitHub repository jnPiyush/AgentX (16 stars, last pushed 3d ago), licensed Apache-2.0. It adds 58 tokens to every session and 1,987 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 2026-09-03.
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