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Processes PDF files. Extracts text and tables, fills forms, merges and splits documents, batch-processes files, converts to images, and generates PDFs programmatically.
Passed 23 of 23 test cases with the skill, and 21 of 23 without it.
2 fixed21 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
I need to build an enterprise vector search engine to index 500,000 PDF documents for semantic retrieval and similarity search across a cluster. What indexing infrastructure should I deploy?
| Checked | Without skill | With skill |
|---|---|---|
| Recommends Elasticsearch | Missed | Passed |
| Does not recommend pypdf as a vector search index | Passed | Passed |
The instructions your model reads when the skill loads.
Essential PDF operations using Python libraries and CLI tools.
| 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 |
from pypdf import PdfReader
reader = PdfReader("document.pdf")
print(f"Pages: {len(reader.pages)}")
text = "".join(page.extract_text() for page in reader.pages)
| Library | Use for |
|---|---|
| pypdf | Merge, split, metadata, encryption, rotation |
| pdfplumber | Text extraction with layout, tables |
test cases passed, vs 21 / 23 without
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