Seongjin_Image-Describer

Image-Describer: Wiki to Markdown Image Link Converter

Convert Wiki-style image links (![[image.png]]) to Markdown format () with intelligent AI-powered image analysis.

Quick Reference (30 seconds)

Purpose: Convert Wiki-style image links to Markdown format with AI-generated alt text descriptions.

Execution Command:

cd "{working_directory}/.claude/skills/Seongjin_Image-Describer/Scripts" && \
source .venv/bin/activate && \
python Convert_Image-Link_Wiki-to-Markdown.py "{markdown_path}" -m gpt

Script Location: .claude/skills/Seongjin_Image-Describer/Scripts/Convert_Image-Link_Wiki-to-Markdown.py

Prerequisites:

• Python venv with: openai, google-generativeai, pillow, python-dotenv
• API Key: .claude/skills/Seongjin_Image-Describer/Scripts/.env with OPENAI_API_KEY or GOOGLE_API_KEY

Output: In-place modification of the markdown file.

Implementation Guide (5 minutes)

Basic Usage

Step 1: Ensure virtual environment is set up

cd "{working_directory}/.claude/skills/Seongjin_Image-Describer/Scripts"
python -m venv .venv
source .venv/bin/activate
pip install python-dotenv openai google-generativeai Pillow

Step 2: Create .env file in Scripts directory

# Create at: .claude/skills/Seongjin_Image-Describer/Scripts/.env
OPENAI_API_KEY=YOUR_API_KEY
OPENAI_MODEL=gpt-5-mini

# Or for Gemini
GOOGLE_API_KEY=AIza-your-google-key-here
GOOGLE_MODEL=gemini-3-flash-preview

Step 3: Execute the script

# Using GPT (default)
python Convert_Image-Link_Wiki-to-Markdown.py "/path/to/document.md" -m gpt

# Using Gemini
python Convert_Image-Link_Wiki-to-Markdown.py "/path/to/document.md" -m gemini

# Path conversion only (no AI analysis)
python Convert_Image-Link_Wiki-to-Markdown.py "/path/to/document.md" --no-describe

# Dry-run mode (preview changes without modifying file)
python Convert_Image-Link_Wiki-to-Markdown.py "/path/to/document.md" -n

Input/Output Format

Input (Wiki-style):

![[image.png]]
![[folder/diagram.jpg]]
![[screenshot.webp]]

Output (Markdown-style):

![Detailed AI-generated description of the image content](absolute/path/to/image.png)
![System architecture diagram showing...](absolute/path/to/folder/diagram.jpg)
![Screenshot of the application interface...](absolute/path/to/screenshot.webp)

CLI Options

Script Configuration

Configurable constants in the script:

CONTEXT_CHARS = 500   # Characters before/after image for context
MAX_RETRIES = 3       # API call retry attempts
CONCURRENT = 20       # Maximum parallel image analyses

Image Search Behavior

The script searches for images in the following order:

1. Current directory of the markdown file
2. Parent directory
3. Grandparent directory
4. Common asset folders (Attachments, images, assets)
5. Full vault search as fallback

Output Example

Building image index...
Found 10751 image files

============================================================
  Images requiring description: 5
  Model: GPT
  Concurrent processing: 20
============================================================

[1/5] Analyzing: chart.png
        Completed: This chart shows sales growth from 2020 to 2024...
[2/5] Analyzing: diagram.jpg
        Completed: System architecture diagram illustrating...

============================================================
  Processing Results Summary
   Success: 5
   Failed: 0
   Skipped: 0
   Total: 5
============================================================

Completed: document.md

Advanced Implementation (10+ minutes)

Two-Phase Processing

The script operates in two distinct phases:

Phase 1 - Link Conversion:

• Converts Wiki links (![[file]]) to Markdown format ()
• Resolves image paths using vault-wide search
• Saves changes immediately after conversion

Phase 2 - AI Description Generation:

• Identifies Markdown images with empty alt text
• Extracts contextual text (500 chars before/after)
• Generates AI descriptions using GPT or Gemini
• Saves each description immediately after generation

Error Handling

Image Not Found:

• Detection: File not found in vault index
• Behavior: Keeps original Wiki link unchanged
• Output: Warning message displayed

API Failure:

• Detection: Network or API errors
• Recovery: Up to 3 retry attempts with 1-second delay
• Behavior: Continues with remaining images

Invalid Markdown:

• Detection: Malformed image links
• Behavior: Graceful handling, partial conversion

Concurrent Processing

The script uses asyncio for efficient parallel processing:

• Semaphore limits concurrent API calls to 20
• Lock ensures safe file writes from multiple tasks
• Results are saved immediately as each image completes

Supported Image Formats

png, jpg, jpeg, gif, webp, svg, bmp, tiff, ico

PPT Workflow Integration

This skill serves as a critical pre-processing step in the PPT generation workflow.

Integration Flow

Step 1: Image-Describer processes markdown file

• Converts Wiki links to Markdown format
• Generates AI descriptions for all images

Step 2: PPT-Planner reads pre-processed markdown

• Understands image content through text descriptions
• Creates slide outlines based on visual content

Step 3: Nano-Banana generates slide images

• Uses PPT-Planner output to create final slides

Benefits

Context Overflow Prevention:

• Visual content converted to text descriptions
• Significantly reduces token usage in PPT-Planner

Enhanced Understanding:

• PPT-Planner can make intelligent decisions about image placement
• AI descriptions provide semantic understanding of visual content

Related Resources

Related Agent:

• Seongjin_Agent_PPT-Planner: Consumes pre-processed markdown for slide planning

Related Skills:

• Seongjin_Nano-Banana: Generates final PPT slide images
• Seongjin_Book-Prep: Can pre-process book chunks before conversion

Related Command:

• /ppt: Orchestrates complete workflow including image pre-processing

Works Well With

• /ppt command - Pre-processes markdown before slide generation workflow
• Seongjin_Agent_PPT-Planner - Consumes pre-processed markdown with image descriptions
• Seongjin_Book-Prep - Can pre-process book chunks before PPT generation
• Seongjin_Nano-Banana - Final step in PPT generation pipeline

Troubleshooting

API Key Not Found:

• Ensure .env file exists at .claude/skills/Seongjin_Image-Describer/Scripts/.env
• Verify OPENAI_API_KEY or GOOGLE_API_KEY is set correctly

Image Not Found:

• Check if image file exists in the vault
• Verify file extension matches supported formats
• Use dry-run mode to preview path resolution

Empty Descriptions:

• Check API connectivity
• Verify API key has sufficient quota
• Review API error messages in console output

Partial Processing:

• Script saves progress after each image
• Re-run script to process remaining images
• Already-processed images (with alt text) are skipped

Virtual Environment Issues:

# Recreate virtual environment
cd "{working_directory}/.claude/skills/Seongjin_Image-Describer/Scripts"
rm -rf .venv
python -m venv .venv
source .venv/bin/activate
pip install python-dotenv openai google-generativeai Pillow