How does batch processing work?

Large tasks are split into manageable batches (e.g., 8 images at a time) to ensure model accuracy and prevent memory or timeout issues during processing.

Which file formats are supported?

This skill is designed to identify and process image tags in both Markdown (.md) and HTML files.

Does this skill modify my image file paths?

No, the skill is strictly programmed to never change source paths or rename image files; it only updates the alt and title metadata within your documents.

Is it safe to run on production documentation?

Yes, safety is a core feature. The skill requires a mandatory --dry-run preview and automatically creates time-stamped backups before any changes are applied.

What happens if an image link is broken or the file is missing?

The skill includes a fallback mechanism that analyzes the surrounding text context to infer a suitable description, marking it as 'FALLBACK_CONTEXT' in the ledger.

Image Alt & Title Auto-Filler

Name: Image Alt & Title Auto-Filler
Author: z-soulx

byz-soulx

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Content Management

Automates the generation of semantic image alt and title tags for Markdown and HTML documents using AI vision.

This skill provides a structured, safety-first workflow to populate missing image metadata in documentation. By utilizing a scripted approach where the AI focuses solely on visual analysis, it ensures high-quality semantic descriptions without risking data loss or path corruption. It features a robust 3-file planning pattern, batch processing for large documentation sets, a mandatory dry-run preview requirement, and automatic backup creation to protect your original files while improving accessibility and SEO.

Key Features

01Contextual fallback mechanism to generate descriptions when images are inaccessible

02Batch processing support for handling large-scale documentation efficiently

03AI-powered visual analysis for accurate semantic alt/title generation

04Mandatory dry-run preview and automatic file backups for maximum safety

056 GitHub stars

06Detailed change ledger (image_ledger.md) for full traceability of modifications

Use Cases

01Enhancing technical documentation accessibility by filling missing alt tags

02Optimizing Markdown-based blog posts and guides for search engine rankings

03Auditing and bulk-updating image metadata across large software repositories

Key Features

01Contextual fallback mechanism to generate descriptions when images are inaccessible

02Batch processing support for handling large-scale documentation efficiently

03AI-powered visual analysis for accurate semantic alt/title generation

04Mandatory dry-run preview and automatic file backups for maximum safety

056 GitHub stars

06Detailed change ledger (image_ledger.md) for full traceability of modifications

Use Cases

01Enhancing technical documentation accessibility by filling missing alt tags

02Optimizing Markdown-based blog posts and guides for search engine rankings

03Auditing and bulk-updating image metadata across large software repositories