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 shahidshabbir-se/my-pi-setup --skill pdf-readinggit clone --depth 1 https://github.com/shahidshabbir-se/my-pi-setupWrote 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/shahidshabbir-se/my-pi-setup/pdf-reading)<a href="https://agentmods.dev/skills/shahidshabbir-se/my-pi-setup/pdf-reading"><img src="https://agentmods.dev/badge/skills/shahidshabbir-se/my-pi-setup/pdf-reading/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/shahidshabbir-se/my-pi-setup/pdf-reading"><img src="https://agentmods.dev/badge/skills/shahidshabbir-se/my-pi-setup/pdf-reading.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 | $0.00115 | $0.02738 |
| Opus 5.5 | $0.00046 | $0.01095 |
| Sonnet 5.5 | $0.00023 | $0.00548 |
| Haiku 4.5 | $0.00012 | $0.00274 |
Grade A, and why
pdf-reading 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 10d 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-reading — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 309 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Processing Guide
Overview
This guide covers essential PDF reading operations using Python libraries and command-line tools. For advanced features (pypdfium2 rendering, pdfplumber table settings, OCR fallback, encrypted/corrupted PDF handling), see REFERENCE.md.
Reading & Inspecting PDFs
Before doing anything with a PDF, understand what you're working with.
Content inventory
Run a quick diagnostic first. For simple tasks ("summarize this
document"), pdfinfo + pdffonts + a text sample may suffice. For
anything involving figures, attachments, or extraction issues, run the
full set:
# Always: page count, file size, PDF version, metadata
pdfinfo document.pdf
# Always: does a text layer exist? No fonts → scanned/raster → see "Scanned documents"
pdffonts document.pdf
# If fonts are present: sample the text layer
pdftotext -f 1 -l 1 document.pdf - | head -20
# If figures/charts may matter:
pdfimages -list document.pdf
# If the PDF might contain embedded files (reports, portfolios):
pdfdetach -list document.pdf
This tells you:
- Page count and size — how big is the job?
- Font status — are any fonts present? An empty
pdffontstable means the PDF is scanned or raster-only:pdftotextwill return nothing, so skip straight to "Scanned documents" below. Fonts shown as not embedded ("emb: no") with custom encodings may produce wrong characters on extraction. - Text extractability — when fonts exist, does
pdftotextreturn clean text, or is it garbled (broken encoding)? - Embedded raster images — are there photos or raster figures? (Note: vector-drawn charts from matplotlib/Excel won't appear — see "Extracting embedded images" below)
- Attachments — are there embedded spreadsheets, data files, etc.?
Text extraction
pypdf for basic text:
from pypdf import PdfReader
reader = PdfReader("document.pdf")
print(f"Pages: {len(reader.pages)}")
# Extract text
text = ""
for page in reader.pages:
text += page.extract_text()
What ships with it
2 files 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.
- 10d ago First seen · 309 lines · 115 tokens per session scan A e2081f071b4f
pdf-reading is a skill published in the GitHub repository shahidshabbir-se/my-pi-setup (2 stars, last pushed 2d ago), licensed MIT. It adds 115 tokens to every session and 2,738 once invoked, about $0.0005 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 2026-10-06.
Other skills, from other repositories
document-skills
Professional document creation, editing, and analysis for Office formats (docx, pdf, pptx, xlsx). Use when working with Word documents, PDFs, PowerPoint presentations, or Excel spreadsheets.
paper2html
Use when turning an academic paper PDF/arXiv/OpenReview page/local LaTeX source into a single-file Chinese HTML deep-reading page, especially when the user wants a Cheat-Sheet style explanation, KaTeX formulas, figure/table evidence, validation, or a publishable research page.
paperreview
Use when the user explicitly wants to upload a final or near-final PDF to paperreview.ai for an external second opinion. Skip this for local paper critique, which should go through paper-review-pipeline first.
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and…
Process PDF files - extract text, create PDFs, merge documents. Use when user asks to read PDF, create PDF, or work with PDF files.
analyzing-malicious-pdf-with-peepdf
Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects.