minimax-image-understanding

imsus/pi-extension-minimax-coding-plan-mcp · updated Apr 8, 2026

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$npx skills add https://github.com/imsus/pi-extension-minimax-coding-plan-mcp --skill minimax-image-understanding
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summary

Use this skill when you need to analyze, describe, or extract information from images.

skill.md

MiniMax Image Understanding Skill

Use this skill when you need to analyze, describe, or extract information from images.

How to Use

Call the understand_image tool directly with a prompt and image URL:

understand_image({
  prompt: "Your question about the image",
  image_url: "https://example.com/image.png"
})

When to Use

Use understand_image when:

  • Screenshots: Error messages, UI issues, code in screenshots
  • Visual content: Photos, diagrams, charts, graphs
  • Documents: Extracting text from images (OCR), understanding layouts
  • UI/UX analysis: Evaluating designs, identifying components
  • Visual debugging: Understanding visual bugs or layout issues

When NOT to Use

Do NOT use understand_image when:

  • Image is already described in the conversation
  • The image is a simple icon or emoji you recognize
  • No image is provided or the image URL is inaccessible
  • Redundant with existing context (e.g., file contents already visible)

Usage

understand_image({
  prompt: "What do you see in this image?",
  image_url: "https://example.com/screenshot.png"
})

API Details

Endpoint: POST {api_host}/v1/coding_plan/vlm

Request Body:

{
  "prompt": "Your question about the image",
  "image_url": "data:image/jpeg;base64,/9j/4AAQ..."
}

Response Format:

{
  "content": "AI analysis of the image...",
  "base_resp": {
    "status_code": 0,
    "status_msg": "success"
  }
}

Image Processing

The tool automatically handles three types of image inputs:

  1. HTTP/HTTPS URLs: Downloads the image and converts to base64

    • Example: https://example.com/image.jpg
  2. Local file paths: Reads local files and converts to base64

    • Absolute: /Users/username/Documents/image.png
    • Relative: images/photo.png
    • Removes @ prefix if present
  3. Base64 data URLs: Passes through existing base64 data

    • Example: data:image/png;base64,iVBORw0KGgo...

Image Formats

Supported:

  • JPEG (.jpg, .jpeg)
  • PNG (.png)
  • WebP (.webp)

Not supported:

  • PDF, GIF, PSD, SVG, and other formats

Crafting Effective Prompts

For Descriptions

  • "Describe what's in this image in detail"
  • "What is the main subject of this image?"
  • "Describe the visual style and composition"

For Code/Technical

  • "What code is shown in this screenshot?"
  • "Extract all text from this image"
  • "Identify the UI framework/components used"

For Analysis

  • "Analyze this UI design. What is working well and what could be improved?"
  • "What emotions or mood does this image convey?"
  • "Compare this design to Material Design principles"

For OCR/Text Extraction

  • "Extract all text from this image"
  • "Read the error message in this screenshot"
  • "What does the label say in this image?"

Examples

Error Analysis

understand_image({
  prompt: "What is the error message and where is it located in this screenshot?",
  image_url: "./error-screenshot.png"
})

Code Screenshot

understand_image({
  prompt: "What code is shown in this screenshot? Please transcribe it exactly.",
  image_url: "https://example.com/code.png"
})

Design Review

understand_image({
  prompt: "Analyze this UI design. What is working well and what could be improved?",
  image_url: "https://example.com/mockup.png"
})

OCR

understand_image({
  prompt: "Extract all text from this image",
  image_url: "/Users/username/Documents/scan.png"
})

Tips

  1. Be specific in your prompt about what you want to know
  2. Mention format if you need structured output (e.g., "list all elements")
  3. Include context if the image is part of a larger task
  4. For screenshots, specify if you need full-page or just a specific area
  5. Complex analysis may trigger a confirmation prompt (analyze, extract, describe, recognize, transcribe, read)

Error Handling

  • Status code 1004: Authentication error - check API key and region
  • Status code 2038: Real-name verification required
  • Invalid image: File doesn't exist or URL is inaccessible
  • Unsupported format: Image format not in JPEG, PNG, WebP
how to use minimax-image-understanding

How to use minimax-image-understanding on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add minimax-image-understanding
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/imsus/pi-extension-minimax-coding-plan-mcp --skill minimax-image-understanding

The skills CLI fetches minimax-image-understanding from GitHub repository imsus/pi-extension-minimax-coding-plan-mcp and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/minimax-image-understanding

Reload or restart Cursor to activate minimax-image-understanding. Access the skill through slash commands (e.g., /minimax-image-understanding) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.725 reviews
  • Maya White· Dec 20, 2024

    minimax-image-understanding has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Maya Malhotra· Nov 11, 2024

    minimax-image-understanding reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Alexander Verma· Oct 2, 2024

    I recommend minimax-image-understanding for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Soo Malhotra· Sep 17, 2024

    minimax-image-understanding has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Rahul Santra· Sep 5, 2024

    minimax-image-understanding reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Pratham Ware· Aug 24, 2024

    I recommend minimax-image-understanding for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Ren Ramirez· Aug 8, 2024

    Useful defaults in minimax-image-understanding — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Hana Robinson· Jul 27, 2024

    I recommend minimax-image-understanding for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Sakshi Patil· Jul 15, 2024

    Useful defaults in minimax-image-understanding — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Sofia Abebe· Jun 18, 2024

    minimax-image-understanding reduced setup friction for our internal harness; good balance of opinion and flexibility.

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