Run2 document text extraction

Skill cxcscmu/SkillLearnBench/skills/b2-self-feedback-claude-opus-4-6/organize-messy-files/run2_document-text-extraction

[COLM'26] SkillLearnBench is the first benchmark for evaluating continual learning methods that automatically generate agent skills.

Install

npx -y skills add cxcscmu/SkillLearnBench --skill run2_document-text-extraction

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What its author says it does

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Extract text from PDF, PPTX, and DOCX files for content classification, with error handling and fallback strategies.

SKILL.md

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Document Text Extraction (Improved)

Libraries

PyPDF2 for PDF text extraction
python-pptx for PowerPoint text extraction
python-docx for Word document text extraction

Installation

pip3 install PyPDF2 python-pptx python-docx --break-system-packages

Key Lessons from Round 1

Read enough pages: 3 pages is usually sufficient for classification, but some papers have long introductions. Consider reading more pages for borderline cases.
Error handling: Always wrap extraction in try/except - some files may be corrupted.
Empty text handling: PyPDF2 may return empty strings for scanned PDFs. Have a fallback plan.

PDF Extraction

import PyPDF2

def extract_pdf_text(filepath, max_pages=3):
    """Extract text from first few pages of a PDF."""
    try:
        with open(filepath, 'rb') as f:
            reader = PyPDF2.PdfReader(f)
            text = ""
            for page in reader.pages[:max_pages]:
                text += page.extract_text() or ""
        return text
    except Exception:
        return ""

PPTX Extraction

from pptx import Presentation

def extract_pptx_text(filepath):
    """Extract all text from slides including shapes and tables."""
    try:
        prs = Presentation(filepath)
        text = ""
        for slide in prs.slides:
            for shape in slide.shapes:
                if hasattr(shape, "text"):
                    text += shape.text + "\n"
                # Also check tables
                if shape.has_table:
                    for row in shape.table.rows:
                        for cell in row.cells:
                            text += cell.text + " "
        return text
    except Exception:
        return ""

DOCX Extraction

from docx import Document

def extract_docx_text(filepath):
    """Extract text from all paragraphs in a Word document."""
    try:
        doc = Document(filepath)
        return "\n".join([p.text for p in doc.paragraphs])
    except Exception:
        return ""