Source: This skill is adapted from Anthropic's document-processing skill
Works with
document processing skills (pdf, docx, pptx, xlsx) for Claude Code and AI agents.
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondocument-processingExecute the skills CLI command in your project's root directory to begin installation:
Fetches document-processing from dirnbauer/webconsulting-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate document-processing. Access via /document-processing in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Source: This skill is adapted from Anthropic's document-processing skill document processing skills (pdf, docx, pptx, xlsx) for Claude Code and AI agents.
Create, edit, and analyze office documents including PDFs, Word documents, PowerPoint presentations, and Excel spreadsheets.
| Task | Document Type | Best Tool |
|---|---|---|
| Extract text | pdfplumber, pdftotext |
|
| Merge/split | pypdf, qpdf |
|
| Fill forms | pdf-lib (JS), pypdf |
|
| Create new | reportlab |
|
| OCR scanned | pytesseract + pdf2image |
|
| Extract text | DOCX | pandoc, markitdown |
| Create new | DOCX | docx-js (JS) |
| Edit existing | DOCX | OOXML (unpack/edit/pack) |
| Extract text | PPTX | markitdown |
| Create new | PPTX | html2pptx, PptxGenJS |
| Edit existing | PPTX | OOXML (unpack/edit/pack) |
| Data analysis | XLSX | pandas |
| Formulas/formatting | XLSX | openpyxl |
import pdfplumber
# Extract text with layout preservation
with pdfplumber.open("document.pdf") as pdf:
for page in pdf.pages:
text = page.extract_text()
print(text)
import pdfplumber
import pandas as pd
with pdfplumber.open("document.pdf") as pdf:
all_tables = []
for page in pdf.pages:
tables = page.extract_tables()
for table in tables:
if table:
df = pd.DataFrame(table[1:], columns=table[0])
all_tables.append(df)
# Combine all tables
if all_tables:
combined_df = pd.concat(all_tables, ignore_index=True)
combined_df.to_excel("extracted_tables.xlsx", index=False)
from pypdf import PdfWriter, PdfReader
writer = PdfWriter()
for pdf_file in ["doc1.pdf", "doc2.pdf", "doc3.pdf"]:
reader = PdfReader(pdf_file)
for page in reader.pages:
writer.add_page(page)
with open("merged.pdf", "wb") as output:
writer.write(output)
from pypdf import PdfReader, PdfWriter
reader = PdfReader("input.pdf")
for i, page in enumerate(reader.pages):
writer = PdfWriter()
writer.add_page(page)
with open(f"page_{i+1}.pdf", "wb") as output:
writer.write(output)
from pypdf import PdfReader, PdfWriter
reader = PdfReader("input.pdf")
writer = PdfWriter()
page = reader.pages[0]
page.rotate(90) # Rotate 90 degrees clockwise
writer.add_page(page)
with open("rotated.pdf", "wb") as output:
writer.write(output)
# Requires: pip install pytesseract pdf2image
import pytesseract
from pdf2image import convert_from_path
# Convert PDF to images
images = convert_from_path('scanned.pdf')
# OCR each page
text = ""
for i, image in enumerate(images):
text += f"Page {i+1}:\n"
text += pytesseract.image_to_string(image)
text += "\n\n"
print(text)
from pypdf import PdfReader, PdfWriter
watermark = PdfReader("watermark.pdf").pages[0]
reader = PdfReader("document.pdf")
writer = PdfWriter()
for page in reader.pages:
page.merge_page(watermark)
writer.add_page(page)
with open("watermarked.pdf", "wb") as output:
writer.write(output)
from pypdf import PdfReader, PdfWriter
reader = PdfReader("input.pdf")
writer = PdfWriter()
for page in reader.pages:
writer.add_page(page)
writer.encrypt("userpassword", "ownerpassword")
with open("encrypted.pdf", "wb") as output:
writer.write(output)
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 = []
# Add content
title = Paragraph("Report Title", styles['Title'])
story.append(title)
story.append(Spacer(1, 12))
body = Paragraph("This is the body of the report. " * 20, styles['Normal'])
story.append(body)
story.append(PageBreak())
# Page 2
story.append(Paragraph("Page 2", styles['Heading1']))
story.append(Paragraph("Content for page 2", styles['Normal']))
docImplementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
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Documentssame categoryReviews
4.6★★★★★55 reviews- EEvelyn Jain★★★★★Dec 28, 2024
document-processing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- MMateo Diallo★★★★★Dec 16, 2024
Solid pick for teams standardizing on skills: document-processing is focused, and the summary matches what you get after install.
- PPratham Ware★★★★★Dec 4, 2024
Keeps context tight: document-processing is the kind of skill you can hand to a new teammate without a long onboarding doc.
- AAisha Farah★★★★★Dec 4, 2024
I recommend document-processing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- SSakshi Patil★★★★★Nov 23, 2024
Registry listing for document-processing matched our evaluation — installs cleanly and behaves as described in the markdown.
- AAisha Martin★★★★★Nov 23, 2024
Solid pick for teams standardizing on skills: document-processing is focused, and the summary matches what you get after install.
- EEvelyn Ghosh★★★★★Nov 19, 2024
document-processing reduced setup friction for our internal harness; good balance of opinion and flexibility.
- KKaira Ramirez★★★★★Nov 7, 2024
I recommend document-processing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- KKiara Sethi★★★★★Oct 26, 2024
Useful defaults in document-processing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- CChaitanya Patil★★★★★Oct 14, 2024
document-processing reduced setup friction for our internal harness; good balance of opinion and flexibility.
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