# Notebooklm To Editable PPTX

> Convert a NotebookLM generated image-based PPTX into a fully editable PowerPoint presentation (PPTX) using native macOS Vision OCR.

- Skill: `yizhao6211999/notebooklm-to-editable-pptx` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add yizhao6211999/notebooklm-to-editable-pptx`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yizhao6211999/notebooklm-to-editable-pptx/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Docs & Writing
- Author: yizhao6211999 (https://skillmd.com/u/yizhao6211999)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/yizhao6211999/notebooklm-to-editable-pptx

---


# NotebookLM to Editable PPTX Conversion

## Overview

NotebookLM currently generates PowerPoint (.pptx) presentations where every slide is a flattened, uneditable image. When you need to convert a NotebookLM export into an **editable** .pptx file, leverage this skill.

This workflow uses a native macOS Swift script (`Vision` framework) for highly accurate OCR on the images, followed by programmatic reconstruction of the presentation using `python-pptx`.

## Prerequisites Ensure

1. `python3` and `pip` are installed.
2. The python module `python-pptx` is installed:
   ```bash
   pip3 install python-pptx
   ```
3. A macOS environment (the Swift OCR script relies on Apple's `Vision` framework).

## Workflow

Follow these steps precisely:

### 1. Extract Images from the NotebookLM PPTX

Use the `extract_images.py` script provided in this skill's `scripts/` folder to pull the PNG images out of the uneditable presentation.

```bash
# Locate the script first
export SKILL_DIR=$(dirname $(find ~ -name "extract_images.py" | grep "notebooklm-to-editable-pptx" | head -n 1))

# Extract images to a temporary directory
mkdir -p /tmp/pptx_images
python3 "$SKILL_DIR/extract_images.py" "path/to/NotebookLM_Export.pptx" /tmp/pptx_images
```

### 2. OCR the Extracted Images

Use the `ocr.swift` script to perform Optical Character Recognition (OCR) on all the extracted PNG files. Save the output to a text file for analysis.

```bash
# Clear the text file first
> /tmp/pptx_extracted_text.txt

# Run OCR on all extracted slides (Slide count must match the extraction output)
for i in /tmp/pptx_images/*.png; do
  echo "--- $i ---" >> /tmp/pptx_extracted_text.txt
  swift "$SKILL_DIR/ocr.swift" "$i" >> /tmp/pptx_extracted_text.txt
done
```

### 3. Analyze the Extracted Text

Read the `/tmp/pptx_extracted_text.txt` file and carefully parse the content for each slide:
- Distinguish between Title text, Body points, and Table Data.
- Identify the logical structure.

### 4. Generate the Editable PPTX

Write a custom Python script for the specific presentation using `python-pptx`. Map the extracted OCR text into real, editable `python-pptx` Layouts (such as Title Slides, Title and Content, Tables, etc.).

**Guidelines for the generation script**:
- Use `prs = Presentation()`
- `prs.slide_layouts[0]` is for Title Slides.
- `prs.slide_layouts[1]` is for Title and Content (bullet points).
- For tables, use `prs.slide_layouts[5]` (Title Only) and draw a table via `slide.shapes.add_table(rows, cols, left, top, width, height)`.
- Reconstruct the slide content logically based on your OCR analysis.

```bash
# Example generic execution
python3 custom_pptx_generator.py
```

## When to Use

This skill applies whenever a user uploads a PowerPoint (.pptx) generated by NotebookLM (or any presentation where the slides are purely flattened images) and explicitly requests to make the text "editable", "convert to a real PPTX", or "recreate the layout".