vision-bridge

Name: vision-bridge
Availability: InStock
Author: Guava

Route image analysis requests from text-only models to vision backends for structured reports.

6|1|Updated May 11, 2026

Search Tags:#multimodal #prompting #image-analysis #domain-context #vision-bridge #text-model

Ready to run

npx skills add https://github.com/Guavafsl/vision-bridge-skills --skill vision-bridge

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: vision-bridge
Source: https://github.com/Guavafsl/vision-bridge-skills/tree/main
Command: npx skills add https://github.com/Guavafsl/vision-bridge-skills --skill vision-bridge

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Vision Bridge delegates image analysis to an external vision model when the primary text model cannot view images, returning a structured report for the text model to review and act on.

Core Features & Use Cases

Two-stage workflow: vision analysis yields a structured text report, then the text model reviews and executes.
Domain and prompt context: supports optional domain context prepended to prompts and neutral system context for the vision model.
Flexible interaction: supports deep analysis, brief descriptions, custom questions, and verbose thinking traces.

Quick Start

Run python scripts/vision_bridge.py <image_path> to analyze an image and receive a structured visual report.

Frequently Asked Questions about vision-bridge

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

FAQPage Schema

How do I analyze images using a text-only model?▼

Image analysis for text-only models is handled by routing image requests to an external vision model, which returns a structured visual report for the text model to review and act on.

What environment variables do I need to configure for vision model routing?▼

Vision model routing requires configuring the VISION_API_KEY environment variable, alongside optional VISION_BASE_URL and VISION_MODEL settings to specify the backend and region.

Can I customize the image analysis prompt with specific domain context?▼

Domain context customization is fully supported, allowing you to prepend specific domain information and neutral system context to tailor the vision model's analysis prompts.

What is the two-stage workflow for multimodal image analysis?▼

The two-stage workflow first generates a structured text report from the vision analysis, then the primary text model reviews this report to execute subsequent actions or deep analysis.

How do I run an image analysis script from the command line?▼

Run python scripts/vision_bridge.py followed by the image path to execute the image analysis and receive a structured visual report directly in your terminal.

Does the vision bridge support flexible interaction styles for image analysis?▼

Flexible interaction supports deep analysis, brief descriptions, custom questions, and verbose thinking traces to provide varied levels of visual insight from the vision backend.