gemini-image▌
johnlindquist/claude · updated Apr 8, 2026
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Analyze images using Gemini's vision capabilities for OCR, UI analysis, and visual understanding.
- ›Supports PNG, JPEG, GIF, and WebP images including screenshots, diagrams, charts, and code snippets
- ›Built-in analysis templates for common tasks: text extraction, code recovery, UI/UX feedback, error diagnosis, and data extraction from charts
- ›Handles single and multiple image comparisons in a single request
- ›Requires Google Generative AI library and valid GEMINI_API_KEY environment var
Gemini Image Analysis
Analyze images using Gemini Pro's vision capabilities.
Prerequisites
pip install google-generativeai
export GEMINI_API_KEY=your_api_key
CLI Reference
Basic Image Analysis
# Analyze an image
gemini -m pro -f /path/to/image.png "Describe this image in detail"
# With specific question
gemini -m pro -f screenshot.png "What error message is shown?"
# Multiple images
gemini -m pro -f image1.png -f image2.png "Compare these two images"
Analysis Operations
General Description
gemini -m pro -f image.png "Describe this image comprehensively:
1. Main subject/content
2. Colors and composition
3. Text visible (if any)
4. Context and purpose
5. Notable details"
Extract Text (OCR)
gemini -m pro -f screenshot.png "Extract all text from this image.
Format as plain text, preserving layout where possible.
Include any text in buttons, labels, or UI elements."
Code from Screenshot
gemini -m pro -f code-screenshot.png "Extract the code from this screenshot.
Provide as properly formatted code with correct indentation.
Note any parts that are unclear or partially visible."
UI Analysis
gemini -m pro -f ui-screenshot.png "Analyze this UI:
1. What application/website is this?
2. What page/screen is shown?
3. Main UI elements and their purpose
4. User flow/actions available
5. Any UX issues or suggestions"
Error Analysis
gemini -m pro -f error-screenshot.png "Analyze this error:
1. What error is shown?
2. What is the likely cause?
3. How to fix it?
4. Any related information visible?"
Diagram Understanding
gemini -m pro -f diagram.png "Explain this diagram:
1. What type of diagram is this?
2. Main components and their relationships
3. Data/process flow
4. Key takeaways"
Specific Use Cases
Debug Screenshot
gemini -m pro -f debug-screen.png "I'm debugging an issue. From this screenshot:
1. What is the current state?
2. What errors or warnings are visible?
3. What should I look at?
4. Suggested next steps"
Compare Before/After
gemini -m pro -f before.png -f after.png "Compare these before and after images:
1. What changed?
2. Is this an improvement?
3. Any issues in the 'after' version?
4. Anything missing?"
Design Feedback
gemini -m pro -f design.png "Provide design feedback:
1. Visual hierarchy
2. Color usage
3. Typography
4. Spacing and alignment
5. Accessibility concerns
6. Suggestions for improvement"
Data Extraction
gemini -m pro -f chart.png "Extract data from this chart:
1. Chart type
2. Data series and values
3. Axes labels and ranges
4. Key trends or insights
5. Output as structured data if possible"
Form Analysis
gemini -m pro -f form.png "Analyze this form:
1. Form purpose
2. Fields and their types
3. Required vs optional
4. Validation rules visible
5. UX suggestions"
Workflow Patterns
Screenshot to Issue
# Capture screenshot (macOS)
screencapture -i /tmp/bug.png
# Analyze and format as issue
gemini -m pro -f /tmp/bug.png "Create a bug report from this screenshot:
## Summary
[One-line description]
## Steps to Reproduce
[Inferred from screenshot]
## Expected Behavior
[What should happen]
## Actual Behavior
[What the screenshot shows]
## Environment
[Any visible system info]"
UI to Code
gemini -m pro -f ui-design.png "Generate React component code that recreates this UI:
- Use Tailwind CSS for styling
- Make it responsive
- Include proper TypeScript types
- Add appropriate accessibility attributes"
Documentation
gemini -m pro -f app-screen.png "Write user documentation for this screen:
- What this screen is for
- How to use each feature
- Common tasks
- Tips and notes"
Image Types Supported
- PNG, JPEG, GIF, WebP
- Screenshots
- Photos
- Diagrams and charts
- UI mockups
- Code snippets
- Documents
Best Practices
- Use clear images - Higher quality = better analysis
- Crop to relevant area - Remove unnecessary context
- Ask specific questions - Vague prompts get vague answers
- Provide context - Tell Gemini what you're looking for
- Verify extracted text - OCR isn't perfect
- Multiple angles - Use multiple images for complex subjects
How to use gemini-image on Cursor
AI-first code editor with Composer
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 gemini-image
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches gemini-image from GitHub repository johnlindquist/claude and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate gemini-image. Access the skill through slash commands (e.g., /gemini-image) 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
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★74 reviews- ★★★★★Dev Khan· Dec 20, 2024
I recommend gemini-image for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Min Reddy· Dec 16, 2024
gemini-image has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Maya Zhang· Dec 16, 2024
Keeps context tight: gemini-image is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Dhruvi Jain· Dec 12, 2024
We added gemini-image from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Xiao Smith· Dec 12, 2024
Registry listing for gemini-image matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Kofi Torres· Dec 12, 2024
gemini-image fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Dev Farah· Dec 4, 2024
gemini-image fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Meera Rahman· Dec 4, 2024
gemini-image is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Kofi Bhatia· Nov 23, 2024
Keeps context tight: gemini-image is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Rahul Santra· Nov 11, 2024
gemini-image fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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