VLM

This one handles vision-based AI chat through the z-ai-web-dev-sdk, letting you analyze images, videos, and documents with conversational follow-ups. You can use it via CLI for quick one-off analysis or integrate it into backend code for multi-turn conversations. The CLI approach is handy for testing: just pass an image URL or local file with a prompt and get results piped to JSON. The SDK route gives you more control for building apps that need to maintain context across multiple images or ask follow-up questions about the same visual content. Works with base64 encoding or direct URLs, though base64 is recommended for reliability.

skills.sh installs: 343
GitHub stars: 26
last updated: Aug 21, 2026

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Install

$ npx -y skills add answerzhao/agent-skills --skill VLM --agent claude-code

Installs into .claude/skills of the current project.

Files

VLM(Vision Chat) Skill

This skill guides the implementation of vision chat functionality using the z-ai-web-dev-sdk package, enabling AI models to understand and respond to images combined with text prompts.

Skills Path

Skill Location: {project_path}/skills/VLM

this skill is located at above path in your project.

Reference Scripts: Example test scripts are available in the {Skill Location}/scripts/ directory for quick testing and reference. See {Skill Location}/scripts/vlm.ts for a working example.

Overview

Vision Chat allows you to build applications that can analyze images, extract information from visual content, and answer questions about images through natural language conversation.

IMPORTANT: z-ai-web-dev-sdk MUST be used in backend code only. Never use it in client-side code.

Prerequisites

The z-ai-web-dev-sdk package is already installed. Import it as shown in the examples below.

CLI Usage (For Simple Tasks)

For simple image analysis tasks, you can use the z-ai CLI instead of writing code. This is ideal for quick image descriptions, testing vision capabilities, or simple automation.