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 telagod/code-abyss --skill processing-pdfsgit clone --depth 1 https://github.com/telagod/code-abyssWrote 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/telagod/code-abyss/processing-pdfs)<a href="https://agentmods.dev/skills/telagod/code-abyss/processing-pdfs"><img src="https://agentmods.dev/badge/skills/telagod/code-abyss/processing-pdfs/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/telagod/code-abyss/processing-pdfs"><img src="https://agentmods.dev/badge/skills/telagod/code-abyss/processing-pdfs.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 | $0.00057 | $0.00537 |
| Opus 5.5 | $0.00023 | $0.00215 |
| Sonnet 5.5 | $0.00011 | $0.00107 |
| Haiku 4.5 | $0.00006 | $0.00054 |
Grade A, and why
processing-pdfs 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.
What it actually says
PDF Processing
Essential PDF operations using Python libraries and CLI tools.
Decision Matrix
| Task | Best Tool | Reference |
|---|---|---|
| Merge / split / metadata / rotate | pypdf | recipes.md |
| Extract text (layout preserved) | pdfplumber | recipes.md |
| Extract tables | pdfplumber | recipes.md |
| Create new PDF | reportlab | recipes.md |
| Batch CLI ops | qpdf / pdftk | recipes.md |
| OCR scanned PDFs | pytesseract + pdf2image | advanced.md |
| Add watermark / extract images / encrypt | pypdf / pdfimages | advanced.md |
| Fill PDF forms | pdf-lib / pypdf | FORMS.md |
| Advanced pypdfium2 / pdf-lib JS | — | REFERENCE.md |
Quick Start
from pypdf import PdfReader
reader = PdfReader("document.pdf")
print(f"Pages: {len(reader.pages)}")
text = "".join(page.extract_text() for page in reader.pages)
Workflow
- Identify task — text extraction? table? creation? form? Pick row from matrix above.
- Load reference — recipes.md covers 90% of tasks; advanced.md for OCR / encrypt; FORMS.md for forms.
- Implement — copy-adapt recipe; verify output.
- Validate — open in a viewer or grep extracted text.
Library Selection
| Library | Use for |
|---|---|
| pypdf | Merge, split, metadata, encryption, rotation |
| pdfplumber | Text extraction with layout, tables |
| reportlab | Generate PDFs programmatically |
| pdf2image + pytesseract | OCR scanned documents |
| qpdf / pdftk (CLI) | Batch ops, no Python needed |
What ships with it
12 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.
- FORMS.md 9.2 KB
- REFERENCE.md 16 KB
- references/advanced.md 1.1 KB
- references/recipes.md 3.3 KB
- scripts/check_bounding_boxes_test.py 8.6 KB runs code
- scripts/check_bounding_boxes.py 3.1 KB runs code
- scripts/check_fillable_fields.py 362 B runs code
- scripts/convert_pdf_to_images.py 1.1 KB runs code
- scripts/create_validation_image.py 1.6 KB runs code
- scripts/extract_form_field_info.py 6.0 KB runs code
- scripts/fill_fillable_fields.py 4.7 KB runs code
- scripts/fill_pdf_form_with_annotations.py 3.5 KB runs code
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 First seen · 52 lines · 57 tokens per session scan A 8da07515d278
processing-pdfs is a skill published in the GitHub repository telagod/code-abyss (243 stars, last pushed 3mo ago), licensed MIT. It adds 57 tokens to every session and 537 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 2026-08-30.
Other skills, from other repositories
xberg
Extract text, tables, metadata, and images from 97+ document formats (PDF, Office, images, HTML, email, archives, academic) using Xberg CLI.
nano-pdf
Extract text and metadata from PDF files using pdftotext and poppler-utils. Supports full extraction, page ranges, and structured output.
nano-pdf
Edit PDFs with natural-language instructions using the nano-pdf CLI.
summarize
Summarize URLs or files with the summarize CLI (web, PDFs, images, audio, YouTube).
Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as reportlab, pdfplumber, and pypdf for generation and extraction.
report-to-pdf
Narrow conversion skill. Invoke only when the user explicitly asks to convert an existing Data Analytics report, dashboard, or inline chart export into a PDF artifact.