What problem does it solve?
PowerPoint files often mix text boxes, tables, charts, and pure image slides, making it hard to programmatically extract complete content for analysis. This Skill provides a full-pipeline approach that captures every slide's content, including rendering and captioning image-only slides that text extraction would otherwise miss.
Core Features & Use Cases
- Full Slide Text Extraction: Pulls text frames, tables, and chart titles from every slide using python-pptx, with automatic .ppt to .pptx conversion via LibreOffice.
- Structured Table & Chart Extraction: Converts embedded tables into pandas DataFrames and reads chart data series when available.
- Image-Only Slide Captioning: Renders slides without extractable text to PNG via LibreOffice and PyMuPDF, then captions them with a vision model so no content is lost.
- Use Case: Given a 50-slide business report, extract all text, compute ratios from embedded tables (e.g., hiring percentages), search for keywords across slides, and build a timeline of dated events.
Quick Start
Analyze the attached presentation 'report.pptx' by extracting all slide text and tables, captioning any image-only slides, and summarizing the key findings.