- Home
- Skills
- Cyangzhou
- 2 Project Yunshu
- Vlm Expert
vlm_expert_skill
- JavaScript
1
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill cyangzhou/-2--project-yunshu- --skill vlm_expert- SKILL.md457 B
Overview
This skill enables conversation driven by visual inputs, combining image understanding with natural-language prompts. It analyzes photos and figures out objects, scenes, relationships, and can compare multiple images for differences or similarities. The focus is practical multimodal interaction for tasks like description, analysis, and visual troubleshooting.
How this skill works
The skill inspects one or more images and extracts visual elements such as objects, scenes, spatial relationships, and salient attributes (color, pose, condition). It accepts a text prompt that frames the desired output (e.g., describe, compare, identify issues) and returns structured natural-language responses or comparison summaries. It also supports CLI-style commands to feed images and prompts together for automated workflows.
When to use it
- Generate descriptive captions or alt text for images
- Compare multiple images to highlight differences or confirm consistency
- Diagnose visual issues in photos or product images
- Enhance chatbots with image-aware responses for customer support
- Audit visual content for accessibility or basic content concerns
Best practices
- Provide a clear, task-focused prompt (e.g., “Describe damage to this item” vs. “What’s here?”)
- Use high-quality, well-lit images and include multiple angles for complex objects
- When comparing images, name or label each image in the prompt to avoid ambiguity
- Specify the desired output format (short caption, bullet list, or troubleshooting steps) to get actionable results
- Avoid sending private or sensitive images; redact personal data when possible
Example use cases
- Automated alt-text generation for accessibility workflows
- Customer support bot that inspects uploaded product photos and suggests return or repair steps
- Design review: compare two interface mockups and list visual differences
- E-commerce: verify product photos match listing descriptions and flag mismatches
- Field diagnostics: technician uploads images and receives likely causes and next steps
FAQ
Common formats like JPEG and PNG are supported; provide standard-resolution images for best results.
How do I get reliable comparisons between images?
Label each image in your prompt, supply consistent lighting and angles, and ask for a focused comparison (e.g., color, damage, layout).
Is sensitive content safe to process?
Avoid submitting personal or sensitive images. Treat visual inputs as you would any external service and remove or anonymize private details.