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Vision Analysis

OrganizationPopular
MiniMax-AI
vision-analysis

Analyze, describe, and extract information from images using the MiniMax vision MCP tool. Use when: user shares an image file path or URL (any message containing .jpg, .jpeg, .png, .gif, .webp, .bmp, or .svg file extension) or uses any of these words/phrases near an image: "analyze", "analyse", "describe", "explain", "understand", "look at", "review", "extract text", "OCR", "what is in", "what's in", "read this image", "see this image", "tell me about", "explain this", "interpret this", in connection with an image, screenshot, diagram, chart, mockup, wireframe, or photo. Also triggers for: UI mockup review, wireframe analysis, design critique, data extraction from charts, object detection, person/animal/activity identification. Triggers: any message with an image file extension (jpg, jpeg, png, gif, webp, bmp, svg), or any request to analyze/describ/understand/review/extract text from an image, screenshot, diagram, chart, photo, mockup, or wireframe.

Overview

PublisherMiniMax-AI
Repositoryskills
Skill namevision-analysis
Stars
13.6K
Forks
1.2K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by MiniMax-AI on GitHub. Read the source before you install it.

Installation

Install the Vision Analysis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/MiniMax-AI/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/vision-analysis .claude/skills/vision-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vision Analysis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Vision Analysis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Vision Analysis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Vision Analysis

Analyze images using the MiniMax MiniMax_understand_image MCP tool available in the MiniMax Token Plan.

Prerequisites

  • MiniMax Token Plan subscription with valid MINIMAX_API_KEY
  • MiniMax MCP configured (MiniMax_understand_image tool available)

If MCP tool is not configured

Step 1: The agent should fetch setup instructions from: https://platform.minimaxi.com/docs/token-plan/mcp-guide

Step 2: Detect the user's environment (OpenCode, Cursor, Claude Code, etc.) and output the exact commands needed. Common examples:

OpenCode — add to ~/.config/opencode/opencode.json or package.json:

json
{
  "mcp": {
    "MiniMax": {
      "type": "local",
      "command": ["uvx", "minimax-coding-plan-mcp", "-y"],
      "environment": {
        "MINIMAX_API_KEY": "YOUR_TOKEN_PLAN_KEY",
        "MINIMAX_API_HOST": "https://api.minimaxi.com"
      },
      "enabled": true
    }
  }
}

Claude Code:

bash
claude mcp add -s user MiniMax --env MINIMAX_API_KEY=your-key --env MINIMAX_API_HOST=https://api.minimaxi.com -- uvx minimax-coding-plan-mcp -y

Cursor — add to MCP settings:

json
{
  "mcpServers": {
    "MiniMax": {
      "command": "uvx",
      "args": ["minimax-coding-plan-mcp"],
      "env": {
        "MINIMAX_API_KEY": "your-key",
        "MINIMAX_API_HOST": "https://api.minimaxi.com"
      }
    }
  }
}

Step 3: After configuration, tell the user to restart their app and verify with /mcp.

Important: If the user does not have a MiniMax Token Plan subscription, inform them that the understand_image tool requires one — it cannot be used with free or other tier API keys.

Analysis Modes

ModeWhen to usePrompt strategy
describeGeneral image understandingAsk for detailed description
ocrText extraction from screenshots, documentsAsk to extract all text verbatim
ui-reviewUI mockups, wireframes, design filesAsk for design critique with suggestions
chart-dataCharts, graphs, data visualizationsAsk to extract data points and trends
object-detectIdentify objects, people, activitiesAsk to list and locate all elements

Workflow

Step 1: Auto-detect image

The skill triggers automatically when a message contains an image file path or URL with extensions: .jpg, .jpeg, .png, .gif, .webp, .bmp, .svg

Extract the image path from the message.

Step 2: Select analysis mode and call MCP tool

Use the MiniMax_understand_image tool with a mode-specific prompt:

describe:

Provide a detailed description of this image. Include: main subject, setting/background,
colors/style, any text visible, notable objects, and overall composition.

ocr:

Extract all text visible in this image verbatim. Preserve structure and formatting
(headers, lists, columns). If no text is found, say so.

ui-review:

You are a UI/UX design reviewer. Analyze this interface mockup or design. Provide:
(1) Strengths — what works well, (2) Issues — usability or design problems,
(3) Specific, actionable suggestions for improvement. Be constructive and detailed.

chart-data:

Extract all data from this chart or graph. List: chart title, axis labels, all
data points/series with values if readable, and a brief summary of the trend.

object-detect:

List all distinct objects, people, and activities you can identify. For each,
describe what it is and its approximate location in the image.

Step 3: Present results

Return the analysis clearly. For describe, use readable prose. For ocr, preserve structure. For ui-review, use a structured critique format.

Output Format Example

For describe mode:

## Image Description

[Detailed description of the image contents...]

For ocr mode:

## Extracted Text

[Preserved text structure from the image]

For ui-review mode:

## UI Design Review

### Strengths
- ...

### Issues
- ...

### Suggestions
- ...

Notes

  • Images up to 20MB supported (JPEG, PNG, GIF, WebP)
  • Local file paths work if MiniMax MCP is configured with file access
  • The MiniMax_understand_image tool is provided by the minimax-coding-plan-mcp package

Frequently asked questions

What does the Vision Analysis AI skill do?

Analyze, describe, and extract information from images using the MiniMax vision MCP tool. Use when: user shares an image file path or URL (any message containing .jpg, .jpeg, .png, .gif, .webp, .bmp, or .svg file extension) or uses any of these words/phrases near an image: "analyze", "analyse", "describe", "explain", "understand", "look at", "review", "extract text", "OCR", "what is in", "what's in", "read this image", "see this image", "tell me about", "explain this", "interpret this", in connection with an image, screenshot, diagram, chart, mockup, wireframe, or photo. Also triggers for:...

Why use Vision Analysis on TypingMind?

Because you install it once and use it with any model. Vision Analysis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Vision Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MiniMax-AI/skills/tree/main/skills/vision-analysis. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Vision Analysis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Vision Analysis?

As many as you like. As long as a model supports skills, you can use Vision Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Vision Analysis AI skill free?

Yes. It is published on GitHub by MiniMax-AI under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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