VLM

Analyze images and generate natural-language responses using image URLs or base64-encoded images.

2.7k|627|Updated Sep 11, 2025
One-click install
npx skills add https://github.com/jjyaoao/HelloAgents --skill vlm-jjyaoao
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: VLM
Source: https://github.com/jjyaoao/HelloAgents/tree/main/skills/VLM
Command: npx skills add https://github.com/jjyaoao/HelloAgents --skill vlm-jjyaoao

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires z-ai-web-dev-sdk, and includes scripts (resource) components.

What problem does it solve?

Vision-based chat capabilities are needed to analyze images, describe visual content, and build multimodal AI assistants. This skill provides a ready-to-use integration with z-ai-web-dev-sdk to combine image understanding with conversation.

Core Features & Use Cases

  • Multimodal analysis: describe images, answer questions, and derive insights from image content using image_url or base64-encoded images.
  • Easy integration: backend-oriented SDK usage with clear prompts and messages for multi-turn conversations.
  • Use cases: e-commerce product descriptions, accessibility descriptions, document-like image understanding.

Quick Start

Describe an image by providing its URL and a question to obtain a natural-language answer.

Frequently Asked Questions about VLM

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a multimodal AI assistant that analyzes images and answers questions?

To build a multimodal AI assistant for image analysis, integrate a backend SDK like z-ai-web-dev-sdk to process image URLs or base64 data, generate natural-language descriptions, and handle multi-turn vision-chat conversations.

Can I use base64-encoded images for vision chat and image analysis?

Yes, vision chat and image analysis support both image URLs and base64-encoded images as input formats, allowing you to process visual content directly without needing publicly hosted image links.

Does z-ai-web-dev-sdk support multi-image analysis and multi-turn conversations?

Yes, z-ai-web-dev-sdk supports multi-image analysis and multi-turn conversations, enabling complex visual question answering workflows and continuous context tracking across multiple follow-up inputs.

What is the best way to generate e-commerce product descriptions from images?

Generating e-commerce product descriptions from images is best handled by multimodal vision models that analyze image content and output natural-language text, automating accessibility descriptions and visual QA workflows.

Do I need a backend environment to run OCR and image classification workflows?

Yes, a backend environment is required to run OCR and image classification workflows because the z-ai-web-dev-sdk dependency operates server-side to process base64 images, manage streaming output, and execute multimodal analysis.

When should I not use a multimodal vision model for image understanding?

You should not use a multimodal vision model for image understanding when your task requires pure text extraction without contextual analysis, or when operating in environments lacking backend SDK support for processing base64 image data.