Agent skill · Testing & QA

gemini-vision

Guide for implementing Google Gemini API image understanding - analyze images with captioning, classification, visual QA, object detection, segmentation, and multi-image comparison. Use when analyzing images, answering visual questions, detecting objects, or processing documents with vision.

majiayu000github.com/majiayu000GitHub ↗
claude-codecan modify filesMIT
Install
npx skills add majiayu000/claude-skill-registry --skill gemini-vision-alex-tgk-saasquatch-2 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 6 KB
Bundled scripts: none
Allowed tools: -Bash-Read-Write-Edit
Path: skills/ai-ml/gemini-vision-alex-tgk-saasquatch-2/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Gemini Vision API Skill This skill enables Claude to use Google's Gemini API for advanced image understanding tasks including captioning, classification, visual question answering, object detection, segmentation, and multi-image analysis. ## Quick Start ### Prerequisites 1. **Get API Key**: Obtain from [Google AI Studio](https://aistudio.google.com/apikey) 2. **Install SDK**: `pip install google-genai` (Python 3.9+) ### API Key Configuration The skill checks for `GEMINI_API_KEY` in this order: 1. **Process environment variable** (recommended) ```bash export GEMINI_API_KEY="your-api-key" ``` 2. **Skill directory**: `.claude/skills/gemini-vision/.env` ``` GEMINI_API_KEY=your-api-key ``` 3. **Project directory**: `.env` or `.gemini_api_key` in project root **Security**: Never commit API keys to version control. Add `.env` to `.gitignore`. ## Core Capabilities ### Image Analysis - **Captioning**: Generate descriptive text for images - **Classification**: Categorize and identify image content - **Visual QA**: Answer questions about image content - **Multi-image**: Compare and analyze up to 3,600 images ### Advanced Features (Model-Specific) - **Object Detection**: Identify and locate

What's inside
Steps it walks through
  1. Quick Start
  2. Prerequisites
  3. API Key Configuration
  4. Core Capabilities
  5. Image Analysis
  6. Advanced Features (Model-Specific)
  7. Supported Formats
  8. Available Models
  9. Usage Examples
  10. Basic Image Analysis
  11. Object Detection (2.0+)
  12. Multi-Image Comparison
  13. File Upload (for large files or reuse)
  14. File Management
Ships with 1 file
  • metadata.json
Commands it runs
export GEMINI_API_KEY="your-api-key"
Analyze a local image
python scripts/analyze-image.py path/to/image.jpg "What's in this image?"
Analyze from URL
python scripts/analyze-image.py https://example.com/image.jpg "Describe this"
Specify model
python scripts/analyze-image.py image.jpg "Caption this" --model gemini-2.5-pro
python scripts/analyze-image.py image.jpg "Detect all objects" --model gemini-2.0-flash
python scripts/analyze-image.py img1.jpg img2.jpg "What's different between these?"
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About this skill
What does the gemini-vision skill do?

Guide for implementing Google Gemini API image understanding - analyze images with captioning, classification, visual QA, object detection, segmentation, and multi-image comparison. Use when analyzing images, answering visual questions, detecting objects, or processing documents with vision.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill gemini-vision-alex-tgk-saasquatch-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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