pdf-toolkit
Structured `.pdf` operations: extract text/tables, merge pages from multiple PDFs, split a PDF by page ranges, fill PDF form fields, and generate fresh PDFs from JSON. Trigger when the user wants programmatic PDF work without natural-language rewriting — examples: pull tables from a report, combine three PDFs, extract pages 5-12, fill a tax form, or build a new PDF from data. Distinct from `nano-pdf`, which uses an LLM to rewrite a page from a sentence; this skill is deterministic byte-level work via pypdf, pdfplumber, and reportlab.
Profile →npx skills add opensquilla/opensquilla --skill pdf-toolkit --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# pdf-toolkit Deterministic, structural PDF operations. Use this skill for programmatic work where you know exactly what you want done. Use the sibling `nano-pdf` skill instead when the task is "rewrite this page to say X" — `nano-pdf` applies a natural-language edit; `pdf-toolkit` applies an explicit operation. ## Decide the operation | Goal | Script | |---|---| | Get text or tables out of a PDF | `extract.py` | | Combine pages from multiple PDFs | `merge.py` | | Split a PDF by page ranges | `split.py` | | Fill `/Tx` form fields in a PDF | `form_fill.py` | | Build a new PDF from data | inline `reportlab` snippet, see Path C below | --- ## Path A: Extract ```bash python {baseDir}/scripts/extract.py /path/to/doc.pdf --json ``` Output: ```json { "pages": 12, "metadata": {"title": "...", "author": "..."}, "text": [ {"page": 1, "content": "..."}, {"page": 2, "content": "..."} ], "tables": [ {"page": 3, "rows": [["..."], ["..."]]} ] } ``` Text uses `pdfplumber` (already in default dependencies) which preserves column layout better than naive PDF text extraction. Tables use `pdfplumber.extract_tables()` with default settings; for tricky layouts pass `--tables-strategy lines|text|explicit
- Decide the operation
- Path A: Extract
- Path B: Merge / Split
- Path C: Form fill
- Path D: Generate from scratch
- Boundary with nano-pdf
- Common pitfalls
- Boundaries
python {baseDir}/scripts/extract.py /path/to/doc.pdf --json
python {baseDir}/scripts/merge.py a.pdf b.pdf c.pdf --out combined.pdf
python {baseDir}/scripts/merge.py manifest.json --out combined.pdf
python {baseDir}/scripts/split.py input.pdf --pages "1-3,7,10-12" --out output_dir/
python {baseDir}/scripts/form_fill.py form.pdf data.json --out filled.pdfWhat does the pdf-toolkit skill do?
Structured `.pdf` operations: extract text/tables, merge pages from multiple PDFs, split a PDF by page ranges, fill PDF form fields, and generate fresh PDFs from JSON. Trigger when the user wants programmatic PDF work without natural-language rewriting — examples: pull tables from a report, combine three PDFs, extract pages 5-12, fill a tax form, or build a new PDF from data. Distinct from `nano-pdf`, which uses an LLM to rewrite a page from a sentence; this skill is deterministic byte-level work via pypdf, pdfplumber, and reportlab.
How do I install it?
Run `npx skills add opensquilla/opensquilla --skill pdf-toolkit --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From opensquilla/opensquilla, a repository with 6,515 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.