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Create, merge, split, fill, and secure PDF files.
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
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Create, merge, split, fill, and secure PDF files.
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Basado en la clasificación ocupacional SOC
Author a Hermes color theme that skins every surface.
Author live widget apps for the Hermes TUI dock.
Build auditable Excel workbooks headless with openpyxl — blue/black/green cell conventions, formulas over hardcodes, named ranges, balance checks, sensitivity tables. Use for financial models, audit outputs, reconciliations.
Create, read, edit Word .docx documents and templates.
Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).
Extract text from PDFs/scans (pymupdf, marker-pdf).
| name | |
| description | Create, merge, split, fill, and secure PDF files. |
| version | 1.0.0 |
| author | Anthropic (adapted by Nous Research) |
| license | Proprietary. LICENSE.txt has complete terms |
| platforms | ["linux","macos","windows"] |
| metadata | {"hermes":{"tags":["PDF","Documents","Forms","Office","Productivity"],"category":"productivity","related_skills":["ocr-and-documents","nano-pdf","docx","xlsx"]}} |
Create, combine, split, transform, and secure PDF files — merging, page manipulation, form filling, watermarks, encryption, and text/table extraction. For heavy text extraction from scanned documents prefer the ocr-and-documents skill; for natural-language edits to existing PDF text prefer nano-pdf.
Use this skill whenever the user wants to do anything with PDF files: reading or extracting text/tables, combining or merging multiple PDFs, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting, extracting images, or OCR on scanned PDFs. If the user mentions a .pdf file or asks to produce one, use this skill.
pip install pypdf pdfplumber reportlab
which pdftotext || sudo apt install -y poppler-utils # pdftotext, pdftoppm, pdfimages
which qpdf || sudo apt install -y qpdf # CLI merge/split/decrypt
macOS: brew install poppler qpdf. OCR extras: pip install pytesseract pdf2image + sudo apt install -y tesseract-ocr.
Script paths below are relative to this skill's directory. Form filling has its own workflow — read forms.md and follow it. Advanced library usage (pypdfium2, pdf-lib) and troubleshooting: reference.md.
| Task | Best Tool | Command/Code |
|---|---|---|
| Merge PDFs | pypdf | writer.add_page(page) per page |
| Split PDFs | pypdf | One page per file |
| Extract text | pdfplumber | page.extract_text() |
| Extract tables | pdfplumber | page.extract_tables() |
| Create PDFs | reportlab | Canvas or Platypus |
| Command-line merge/split | qpdf | qpdf --empty --pages ... |
| OCR scanned PDFs | pytesseract | Convert to images first (or use ocr-and-documents) |
| Fill PDF forms | see forms.md | scripts/fill_fillable_fields.py etc. |
| Edit existing text | nano-pdf skill | nano-pdf edit file.pdf <page> "<instruction>" |
from pypdf import PdfReader, PdfWriter
# Merge
writer = PdfWriter()
for pdf_file in ["doc1.pdf", "doc2.pdf"]:
for page in PdfReader(pdf_file).pages:
writer.add_page(page)
with open("merged.pdf", "wb") as f:
writer.write(f)
# Split: one file per page
reader = PdfReader("input.pdf")
for i, page in enumerate(reader.pages):
w = PdfWriter(); w.add_page(page)
with open(f"page_{i+1}.pdf", "wb") as f:
w.write(f)
# Rotate
page = reader.pages[0]
page.rotate(90) # clockwise
import pdfplumber, pandas as pd
with pdfplumber.open("document.pdf") as pdf:
text = "\n".join(page.extract_text() or "" for page in pdf.pages)
tables = [pd.DataFrame(t[1:], columns=t[0])
for page in pdf.pages
for t in page.extract_tables() if t]
from reportlab.lib.pagesizes import letter
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, PageBreak
from reportlab.lib.styles import getSampleStyleSheet
doc = SimpleDocTemplate("report.pdf", pagesize=letter)
styles = getSampleStyleSheet()
story = [Paragraph("Report Title", styles["Title"]), Spacer(1, 12),
Paragraph("Body text...", styles["Normal"]), PageBreak(),
Paragraph("Page 2", styles["Heading1"])]
doc.build(story)
Subscripts/superscripts: never use Unicode sub/superscript characters (₀₁₂, ⁰¹²) — the built-in fonts lack the glyphs and render solid black boxes. Use <sub>/<super> markup inside Paragraph objects: Paragraph("H<sub>2</sub>O", styles['Normal']). For canvas-drawn text, adjust font size and position manually.
pdftotext -layout input.pdf output.txt # text, layout preserved
pdftotext -f 1 -l 5 input.pdf output.txt # pages 1-5
qpdf --empty --pages file1.pdf file2.pdf -- merged.pdf # merge
qpdf input.pdf --pages . 1-5 -- pages1-5.pdf # split range
qpdf input.pdf output.pdf --rotate=+90:1 # rotate page 1
qpdf --password=pw --decrypt encrypted.pdf decrypted.pdf # remove password
pdfimages -j input.pdf img # extract images
from pypdf import PdfReader, PdfWriter
watermark = PdfReader("watermark.pdf").pages[0]
reader, writer = PdfReader("document.pdf"), PdfWriter()
for page in reader.pages:
page.merge_page(watermark)
writer.add_page(page)
with open("watermarked.pdf", "wb") as f:
writer.write(f)
writer.encrypt("userpassword", "ownerpassword")
import pytesseract
from pdf2image import convert_from_path
pages = convert_from_path("scanned.pdf")
text = "\n\n".join(pytesseract.image_to_string(img) for img in pages)
For batch/structured extraction from scans, the ocr-and-documents skill (pymupdf, marker-pdf) is the better path.
Read forms.md first — it distinguishes fillable (AcroForm) PDFs from flat scanned forms and walks through the helper scripts:
scripts/check_fillable_fields.py — does the PDF have AcroForm fields?scripts/extract_form_field_info.py / scripts/extract_form_structure.py — enumerate fieldsscripts/fill_fillable_fields.py — fill AcroForm fieldsscripts/fill_pdf_form_with_annotations.py — overlay text on flat formsscripts/check_bounding_boxes.py, scripts/create_validation_image.py — verify placement visuallypage.extract_text() returns None on image-only pages — guard with or "" and fall back to OCR.PdfReader(path, password=...) before pages are accessible.PdfReader and assert the expected page count.pdftotext or pdfplumber) and confirm the content you added is present.pdftoppm -jpeg -r 100 output.pdf page and inspect the images with vision_analyze.ocr-and-documents (scanned-document text extraction), nano-pdf (NL text edits in place), docx (Word), xlsx (spreadsheets), powerpoint (decks).