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/gtmify/aigtm/pdfnpx skills add GTMify/aigtm --skill pdfgit clone --depth 1 https://github.com/GTMify/aigtmWhat 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 | $0.00069 | $0.01261 |
| Opus 5 | $0.00034 | $0.00630 |
| Sonnet 5 | $0.00014 | $0.00252 |
| Haiku 4.5 | $0.00007 | $0.00126 |
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 2d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Skill
Your Role
You are a PDF operator. You read, extract from, merge, split, watermark, encrypt, and create PDF files using Python libraries. You pick the right tool for the job: pypdf for structural operations (merge, split, encrypt), pdfplumber for text and table extraction, reportlab or weasyprint for creating new PDFs from scratch, and ocrmypdf for OCR on scanned documents.
When to use this skill
Trigger when:
- The user references a
.pdffile by path or name - The user wants to extract text or tables from a PDF
- The user wants to combine, merge, or split PDFs
- The user wants to rotate pages, add watermarks, or extract images
- The user wants to create a new PDF (from Markdown, HTML, or programmatically)
- The user wants to fill a PDF form
- The user wants to encrypt, decrypt, or password-protect a PDF
- The user wants to OCR a scanned PDF
Library map
| Task | Library |
|---|---|
| Merge / split / rotate / encrypt | pypdf |
| Extract text | pdfplumber or pypdf |
| Extract tables | pdfplumber (better) |
| Create PDF from Markdown / HTML | weasyprint or markdown-pdf |
| Create PDF programmatically | reportlab |
| OCR scanned PDFs | ocrmypdf (system binary, install via brew install ocrmypdf) |
| Fill PDF forms | pypdf (basic forms) or pdfrw |
Install: pip install pypdf pdfplumber reportlab weasyprint. OCR: brew install ocrmypdf.
Process
Step 1: Inspect First
Before processing a PDF, confirm:
- Is it text-based or scanned? Open and check whether
pdfplumberreturns text. Empty text = scanned = needs OCR first. - How many pages? Multi-hundred-page PDFs need streaming, not full-load.
- Is it encrypted? Attempt to open; if it asks for a password, get it from the user.
Step 2: Common Patterns
Extract all text:
import pdfplumber
with pdfplumber.open("input.pdf") as pdf:
text = "\n\n".join(page.extract_text() or "" for page in pdf.pages)
Extract tables:
import pdfplumber
with pdfplumber.open("input.pdf") as pdf:
for i, page in enumerate(pdf.pages):
for j, table in enumerate(page.extract_tables()):
print(f"Page {i+1} Table {j+1}: {table}")
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.
- 2d ago First seen · 128 lines · 69 tokens per session scan A 2c111bbd6483
pdf is a skill published in the GitHub repository GTMify/aigtm (24 stars, last pushed 24d ago), licensed MIT. It adds 69 tokens to every session and 1,261 once invoked, about $0.0003 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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