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 agentmods add skills/optimeta/paideia/pdfnpx skills add OPTIMETA/PAIDEIA --skill pdfgit clone --depth 1 https://github.com/OPTIMETA/PAIDEIAWhat 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 | $0.00096 | $0.01707 |
| Opus 5 | $0.00048 | $0.00853 |
| Sonnet 5 | $0.00019 | $0.00341 |
| Haiku 4.5 | $0.00010 | $0.00171 |
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 3d 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 — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Processing Guide
When to use this skill
Load this skill whenever the workflow involves PDF input or output. In the paideia context specifically:
- Converting
materials/**/*.pdfto markdown inconverted/**/*.md(via/ingest) - Converting hand-written answer PDFs in
answers/*.pdfto markdown inanswers/converted/*.md(via/grade) - OCR for scanned lecture notes, textbook chapters, or hand-written work
Quick decision tree
What kind of PDF?
├─ Course material (materials/**/*.pdf) → VISION pipeline (see VISION.md)
│ pdfplumber is unreliable on course
│ content — even "prose-heavy"
│ textbook pages mix in equations,
│ figures, and multi-column layouts
│ that break digital extraction
│ silently. We route everything
│ through vision instead of
│ maintaining a per-category heuristic.
├─ Hand-written answer PDF → vision-ocr skill (see vision-ocr/)
└─ Arbitrary outside-the-plugin PDF → pdfplumber / pypdf / pytesseract
per the sections below, case-by-case
Within this plugin, /paideia:ingest routes all materials/**/*.pdf through the vision pipeline. The pdfplumber / pypdf / pytesseract blocks below remain for reference and for ad-hoc PDF work outside the ingest flow (e.g., quick text dumps, PDF merge/split, producing the cheatsheet PDF).
Core operations
Text extraction (digital PDF)
import pdfplumber
with pdfplumber.open("input.pdf") as pdf:
text_by_page = []
for page in pdf.pages:
text_by_page.append(page.extract_text() or "")
full_text = "\n\n---\n\n".join(text_by_page)
Simpler alternative using pypdf:
from pypdf import PdfReader
reader = PdfReader("input.pdf")
full_text = "\n\n".join(p.extract_text() or "" for p in reader.pages)
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.
- 3d ago First seen · 165 lines · 96 tokens per session scan A 33dedc946ab8
pdf is a skill published in the GitHub repository OPTIMETA/PAIDEIA (91 stars, last pushed 1mo ago), licensed MIT. It adds 96 tokens to every session and 1,707 once invoked, about $0.0005 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 2026-08-30.
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