pdf

name	pdf
description	Read and extract text content from PDF files using pdfplumber (Python)
license	MIT
compatibility	opencode
metadata	{"audience":"developers","workflow":"file-reading"}

What I do

• Locate PDF files in the repository using glob patterns (e.g., **/*.pdf).
• Extract text content from PDFs using pdfplumber (Python library).
• Handle multi-page PDFs, paginate through large documents, and extract tables.
• Summarize extracted content for use in design, documentation, or code tasks.

When to use me

Use this when the user asks to read, inspect, or extract information from a PDF file, or when a task references content in a PDF document.

Prerequisites

Ensure pdfplumber is installed:

pip install pdfplumber

Usage

Step 1: Locate PDF Files

If the PDF path is unknown, search for it:

Glob: **/*.pdf

Step 2: Extract All Text from the PDF

Use Python with pdfplumber. Set PYTHONIOENCODING=utf-8 to handle Unicode characters in the output:

$env:PYTHONIOENCODING='utf-8'; python -c "
import pdfplumber, sys
path = sys.argv[1]
with pdfplumber.open(path) as pdf:
    print(f'Pages: {len(pdf.pages)}')
    for i, page in enumerate(pdf.pages):
        text = page.extract_text()
        if text:
            print(f'\\n<<< PAGE {i+1} / {len(pdf.pages)} >>>\\n')
            print(text)
" '<absolute-path-to-pdf>'

Step 3: Extract a Specific Page Range

For large PDFs, specify start and end page numbers (1-indexed):

$env:PYTHONIOENCODING='utf-8'; python -c "
import pdfplumber, sys
path, start, end = sys.argv[1], int(sys.argv[2]), int(sys.argv[3])
with pdfplumber.open(path) as pdf:
    for i in range(start - 1, min(end, len(pdf.pages))):
        text = pdf.pages[i].extract_text()
        if text:
            print(f'\\n<<< PAGE {i+1} / {len(pdf.pages)} >>>\\n')
            print(text)
" '<path>' <start> <end>

Step 4: Find a PDF by Glob and Extract (Combined)

$env:PYTHONIOENCODING='utf-8'; $file = Get-ChildItem -Path '<search-dir>' -Filter '*.pdf' -Recurse | Select-Object -First 1; python -c "
import pdfplumber, sys
with pdfplumber.open(sys.argv[1]) as pdf:
    print(f'Pages: {len(pdf.pages)}')
    for i, page in enumerate(pdf.pages):
        text = page.extract_text()
        if text:
            print(f'\\n<<< PAGE {i+1} >>>\\n' + text)
" $file.FullName

Step 5: Extract Tables from a PDF

If the PDF contains tabular data:

$env:PYTHONIOENCODING='utf-8'; python -c "
import pdfplumber, sys, itertools
with pdfplumber.open(sys.argv[1]) as pdf:
    for pi, page in enumerate(pdf.pages):
        tables = page.extract_tables()
        for ti, table in enumerate(tables):
            print(f'\\n--- Table in Page {pi+1} ---')
            for row in table:
                print(' | '.join([c or '' for c in row]))
" '<path>'

Step 6: Summarize

After extracting, synthesize the key information relevant to the task. Strip boilerplate (legal notices, page headers/footers) and focus on the substantive content.