Nano Pdf

Nano Pdf is a community skill for lightweight PDF processing, covering text extraction, page manipulation, PDF creation, metadata editing, and format conversion for quick document handling without heavy dependencies.

What Is This?

Overview

Nano Pdf provides a streamlined interface for common PDF operations that AI agents and automation scripts need to perform. It covers text extraction that pulls readable content from PDF documents including tables and structured data while preserving layout information, page manipulation that splits, merges, rotates, and reorders PDF pages for document reorganization tasks, PDF creation that generates new documents from text, images, and HTML content with configurable formatting, metadata editing that reads and modifies document properties such as title, author, creation date, and custom fields, and format conversion that transforms PDFs to and from other formats including text and images. The skill provides a lightweight alternative to full PDF processing libraries for the most common document operations.

Who Should Use This

This skill serves AI agents that need to read and generate PDF documents, automation developers processing document pipelines, and teams handling PDF manipulation tasks from the command line. It is particularly well suited for workflows where installing large PDF frameworks is impractical or where fast, scriptable document handling is the priority.

Why Use It?

Problems It Solves

Full PDF processing libraries are large dependencies that add complexity to simple extraction tasks. AI agents cannot read PDF content directly and need a tool to convert documents to text for analysis and comprehension. Splitting or merging PDF files manually through GUI applications is slow for batch processing workflows. Extracting structured data from PDFs often requires multiple tools and format conversion steps to produce usable output.

Core Highlights

Text extractor pulls content from PDFs while preserving layout and table structure. Page manager splits, merges, rotates, and reorders document pages efficiently. Document creator generates PDFs from text, images, and HTML source content. Metadata editor reads and modifies document properties and custom fields.

How to Use It?

Basic Usage

nanopdf extract report.pdf

nanopdf split document.pdf \
  --pages 1-5 \
  --output section1.pdf

nanopdf merge \
  part1.pdf part2.pdf \
  --output combined.pdf

nanopdf info report.pdf

Real-World Examples

nanopdf extract \
  financial_report.pdf \
  --format csv \
  --tables-only \
  > tables.csv

nanopdf create \
  --from invoice.html \
  --output invoice.pdf

nanopdf rotate \
  scanned.pdf \
  --pages 3,7 \
  --angle 90

for f in docs/*.pdf; do
  nanopdf extract "$f" \
    > "${f%.pdf}.txt"
done

Advanced Tips

Use table extraction mode for financial reports and spreadsheet-style PDFs to get structured CSV output instead of plain text. Chain PDF operations in shell pipelines for complex document workflows like extracting specific pages then merging them with other documents. Set output format to JSON for structured metadata extraction that integrates with downstream processing scripts. When generating PDFs from HTML, validate the source markup first to ensure consistent rendering and avoid unexpected layout shifts in the output file.

When to Use It?

Use Cases

Extract text from uploaded PDF documents for AI analysis and summarization workflows. Split large PDF reports into individual chapter files for targeted distribution. Generate PDF invoices and receipts from structured data in automated business processes. Batch convert entire directories of PDF files to plain text for indexing or search pipeline ingestion.

Related Topics

PDF processing, document extraction, text parsing, document conversion, page manipulation, and file format transformation.

Important Notes

Requirements

The nanopdf CLI tool installed and accessible in the system PATH for executing commands. Input PDF files accessible from the local filesystem or provided via standard input. Sufficient disk space for output files when processing large documents or performing batch operations.

Usage Recommendations

Do: use the tables-only extraction mode for documents with structured tabular data to get clean CSV output. Test extraction on a sample page before processing entire documents to verify output quality and formatting. Use batch processing loops for multiple files rather than running individual commands sequentially.

Don't: expect perfect text extraction from scanned PDFs without OCR since the tool processes embedded text, not images. Overwrite original files with output results without keeping backups of the source documents. Assume all PDF formatting will be preserved when converting to other formats since complex layouts may simplify during conversion.

Limitations

Scanned PDF documents without embedded text require separate OCR processing before text extraction can work effectively. Complex PDF layouts with overlapping elements and custom fonts may produce imperfect text extraction results. Very large PDF files may consume significant memory during processing operations, so consider splitting oversized documents into smaller segments before running extraction or conversion commands.