iyeque-pdf-reader_skill

Overview

This skill extracts text, searches inside PDFs, produces summaries, and retrieves basic document metadata. It is designed for quick inspection of PDF content and to surface key information without manual reading. The focus is on practical, scriptable tools that integrate with existing Python workflows.

How this skill works

The skill reads PDF files and extracts plain text using a PDF parsing library. It supports full or partial extraction (limit by pages), simple case-insensitive search that returns matching lines, chunk-based summarization that divides long text into manageable pieces and sends each chunk to an LLM, and a metadata reader that returns title, author, and page count. The functions are lightweight and intended to be used programmatically in pipelines or small utilities.

When to use it

• Quickly pull raw text from a PDF for downstream processing or indexing.
• Find occurrences of a keyword or phrase across large documents.
• Generate concise, multi-chunk summaries of long reports or papers.
• Extract basic metadata for cataloging or archival systems.
• Preprocess PDFs before feeding content to search indexes or LLMs.

Best practices

• Test extraction on representative PDFs because layout and embedded fonts affect results.
• Limit extraction to relevant pages when performance or token limits matter.
• Use case-insensitive queries and normalize text for more robust search results.
• Adjust chunk size to match the LLM input limits and expected summary granularity.
• Validate summaries against source text for accuracy, especially with technical content.

Example use cases

• Archive ingestion: extract text and metadata to populate a searchable archive index.
• Research review: summarize long academic papers or whitepapers into digestible points.
• Compliance checks: search contracts and reports for specific clauses or terms.
• Automation pipelines: preprocess PDFs before NLP tasks like entity extraction.
• Content audit: quickly surface titles, authors, and page counts for large PDF batches.