pdf-toolkit

name	pdf-toolkit
description	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.
homepage	https://pypdf.readthedocs.io/
provenance	{"origin":"clawhub-mit0","license":"MIT-0","upstream_url":"https://clawhub.ai/pdf","maintained_by":"OpenSquilla"}
metadata	{"platform":{"emoji":"📕","requires":{"anyBins":["python","python3"]},"install":[{"id":"pypdf","kind":"uv","package":"pypdf","label":"Install pypdf (uv pip)"},{"id":"reportlab","kind":"uv","package":"reportlab","label":"Install reportlab (uv pip)"}]}}

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

python {baseDir}/scripts/extract.py /path/to/doc.pdf --json

Output:

{
  "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 to switch detection mode.

For OCR (scanned PDFs), this skill does not include Tesseract — use the sibling skill that wraps an OCR engine (out of scope here).

---

Path B: Merge / Split

Merge full files:

python {baseDir}/scripts/merge.py a.pdf b.pdf c.pdf --out combined.pdf

Or merge specific page ranges with the manifest form:

python {baseDir}/scripts/merge.py manifest.json --out combined.pdf

manifest.json:

[
  {"file": "a.pdf", "pages": "1-3"},
  {"file": "b.pdf", "pages": "5,7,9-11"},
  {"file": "c.pdf"}
]

Page ranges are 1-based, comma-separated, hyphen for ranges. Omit pages to include the whole file. Splits use the same syntax in reverse:

python {baseDir}/scripts/split.py input.pdf --pages "1-3,7,10-12" --out output_dir/

Each range writes one output file: output_dir/input_001.pdf, output_dir/input_002.pdf, …

---

Path C: Form fill

python {baseDir}/scripts/form_fill.py form.pdf data.json --out filled.pdf

data.json maps field name → string value:

{
  "applicant_name": "Wei E.",
  "submission_date": "2026-05-06",
  "agreed": "Yes"
}

The script discovers fields via pypdf.PdfReader.get_fields() and updates them with update_page_form_field_values(). Fields not present in the JSON are left untouched. Run with --list-fields to enumerate the form's fields without filling.

Caveats:

• /Btn checkbox fields take the export value (often Yes, On, or 1) rather than true — inspect with --list-fields to discover.
• AcroForm fills only. XFA forms (used by some legal templates) require Adobe-specific tooling and are out of scope.
• Some signed PDFs invalidate the signature when fields change. Strip signatures explicitly with --clear-signatures if that is intended.

---

Path D: Generate from scratch

Use reportlab directly when you need a new PDF:

from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import LETTER
from pathlib import Path

c = canvas.Canvas(str(Path("out.pdf")), pagesize=LETTER)
c.setFont("Helvetica-Bold", 18)
c.drawString(72, 720, "Q3 Review")
c.setFont("Helvetica", 11)
c.drawString(72, 696, "Revenue grew 18% year over year.")
c.showPage()
c.save()

For tables, headers/footers, and multi-column layouts, switch to reportlab.platypus (SimpleDocTemplate, Paragraph, Table, PageBreak). See references/reportlab.md.

---

Boundary with nano-pdf

nano-pdf (sibling bundled skill) wraps an LLM that takes a page index and a natural-language instruction. Use it when the change is "fix the typo on page 1" or "make the title shorter". Use this skill when the change is "merge these three PDFs", "extract the tables", or "fill the form". The two do not overlap: if you find yourself reaching for nano-pdf to do a merge, switch to pdf-toolkit; if you reach here to "rewrite page 5 to be friendlier", switch back.

---

Common pitfalls

Symptom	Cause	Fix
Extracted text is empty	Scanned PDF, no text layer	OCR is out of scope; use a separate OCR skill
Garbled characters in extract	PDF uses a custom font encoding	Try pdfplumber.open(path, laparams={...}) with char_margin adjustments
Merged PDF is huge	Underlying PDFs include large embedded fonts	Subset fonts via pypdf compress_content_streams()
Form fill silently no-ops	Field name in JSON does not match PDF field name	Run with --list-fields first to see exact names
Pages out of order after split	Range overlap collapsed unexpectedly	Use disjoint ranges, e.g. 1-3,4-6 not 1-5,3-6

---

Boundaries

• This skill works with text-based and form-based PDFs. Scanned image PDFs need OCR before any text path produces results.
• Encrypted PDFs are read-only here. Decryption requires the user-supplied password and is out of scope for this skill.
• For PDF-to-image rendering, use a separate skill that wraps Poppler or PyMuPDF.
• Digital signature operations (signing, verifying, revoking) are out of scope.