Run3 Extract PDF Content and Metadata

Skill cxcscmu/SkillLearnBench/skills/b3-teacher-feedback-claude-haiku-4-5/organize-messy-files/run3_Extract-PDF-Content-and-Metadata

[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 run3_Extract-PDF-Content-and-Metadata

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What its author says it does

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Use this skill to extract the full text, title, abstract, and keywords from PDF files to determine their actual subject matter. Essential for content-based sorting when PDF filenames may be arXiv IDs or other non-descriptive identifiers.

SKILL.md

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When to use this skill

When you need to read the actual content of a PDF paper to determine its subject
When PDF filenames are identifiers (like 2105.03431v1.pdf) rather than descriptive titles
Before sorting PDFs into subject folders to ensure accuracy

How to extract PDF content

Using PyPDF2 or pdfplumber

import pdfplumber

def extract_pdf_content(pdf_path):
    with pdfplumber.open(pdf_path) as pdf:
        # Extract first page (usually contains title and abstract)
        first_page = pdf.pages[0]
        text = first_page.extract_text()
        
        # Also extract from next 1-2 pages for full abstract
        if len(pdf.pages) > 1:
            text += "\n" + pdf.pages[1].extract_text()
        
        return text

Key information to extract

Title: Usually at the top of page 1
Abstract: Contains subject keywords and main topic
Keywords section: Often explicitly labeled
Introduction: First paragraph usually summarizes the field

What to look for in content

LLM: Keywords like "language model", "transformer", "neural network", "NLP", "large language model", "BERT", "GPT"
Trapped ion and quantum computing: Keywords like "trapped ion", "quantum computer", "qubit", "quantum gate", "quantum algorithm"
Black hole: Keywords like "black hole", "event horizon", "gravitational", "spacetime", "Hawking", "relativity"
DNA: Keywords like "DNA", "genetics", "gene", "molecular biology", "sequence", "protein"
Music history: Keywords like "music", "composer", "symphony", "historical", "musical"

Store extracted content for analysis

Save the extracted text to a temporary variable or file for subject classification matching.