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 Pixel-Process-UG/superkit-agents --skill pdf-processinggit clone --depth 1 https://github.com/Pixel-Process-UG/superkit-agentsWrote 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/pixel-process-ug/superkit-agents/pdf-processing)<a href="https://agentmods.dev/skills/pixel-process-ug/superkit-agents/pdf-processing"><img src="https://agentmods.dev/badge/skills/pixel-process-ug/superkit-agents/pdf-processing/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/pixel-process-ug/superkit-agents/pdf-processing"><img src="https://agentmods.dev/badge/skills/pixel-process-ug/superkit-agents/pdf-processing.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 | $0.00077 | $0.03108 |
| Opus 5.5 | $0.00031 | $0.01243 |
| Sonnet 5.5 | $0.00015 | $0.00622 |
| Haiku 4.5 | $0.00008 | $0.00311 |
Grade A, and why
pdf-processing 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 — 363 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Processing
Overview
Generate, manipulate, and extract data from PDF documents. This skill covers the Python PDF ecosystem: pypdf for merging/splitting/metadata, pdfplumber for text and table extraction, reportlab for generation, pytesseract for OCR, and strategies for form filling, watermarking, and complex document assembly.
Apply this skill whenever PDFs need to be created, parsed, transformed, or combined through code.
Multi-Phase Process
Phase 1: Requirements
- Determine operation type (generate, extract, manipulate)
- Identify input PDF characteristics (scanned, digital, forms)
- Define output requirements (format, quality, size)
- Plan data pipeline (source data to PDF or PDF to data)
- Assess volume and performance requirements
STOP — Do NOT select a library until the operation type and input characteristics are clear.
Phase 2: Implementation
- Select appropriate library for the task (see decision table)
- Implement core processing logic
- Handle edge cases (corrupted files, encrypted PDFs, mixed content)
- Add error handling and validation
- Optimize for file size and processing speed
STOP — Do NOT skip edge case handling for encrypted, rotated, or scanned PDFs.
Phase 3: Validation
- Verify output renders correctly in multiple PDF viewers
- Check text is selectable (not rasterized) when applicable
- Validate extracted data accuracy
- Test with edge case PDFs (large, encrypted, scanned)
- Verify accessibility (tagged PDF where needed)
Library Selection Decision Table
| Task | Library | Why | Alternative |
|---|---|---|---|
| Text extraction | pdfplumber | Best accuracy, handles layouts | pypdf (simpler, less accurate) |
| Table extraction | pdfplumber | Structured table parsing | camelot (dedicated table tool) |
| PDF generation | reportlab | Full control, professional quality | weasyprint (HTML-to-PDF) |
| Merge / split | pypdf | Simple, reliable, fast | — |
| Form filling | pypdf | Reads and fills AcroForms | pdfrw (alternative API) |
| Metadata read/write | pypdf | Read/write PDF properties | — |
| OCR (scanned docs) | pytesseract + pdf2image | Scanned document text extraction | EasyOCR (deep learning) |
| Watermarking | pypdf + reportlab | Overlay pages | — |
| HTML to PDF | weasyprint | CSS-based layout, server-friendly | playwright (browser rendering) |
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 · 363 lines · 77 tokens per session scan A b42c6cb852e4
pdf-processing is a skill published in the GitHub repository Pixel-Process-UG/superkit-agents (3 stars, last pushed 7mo ago), licensed MIT. It adds 77 tokens to every session and 3,108 once invoked, about $0.0003 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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