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.
Scanned 6/2/2026
Install via CLI
openskills install majiayu000/claude-skill-registry---
name: gemini-vision
description: 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.
license: MIT
allowed-tools:
- Bash
- Read
- Write
- Edit
---
# 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 objects with bounding boxes (Gemini 2.0+)
- **Segmentation**: Create pixel-level masks for objects (Gemini 2.5+)
- **Document Understanding**: Process PDFs with vision (up to 1,000 pages)
## Supported Formats
- **Images**: PNG, JPEG, WEBP, HEIC, HEIF
- **Documents**: PDF (up to 1,000 pages)
- **Size Limits**:
- Inline: 20MB max total request size
- File API: For larger files
- Max images: 3,600 per request
## Available Models
- **gemini-2.5-pro**: Most capable, segmentation + detection
- **gemini-2.5-flash**: Fast, efficient, segmentation + detection
- **gemini-2.5-flash-lite**: Lightweight, segmentation + detection
- **gemini-2.0-flash**: Object detection support
- **gemini-1.5-pro/flash**: Previous generation
## Usage Examples
### Basic Image Analysis
```bash
# 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
```
### Object Detection (2.0+)
```bash
python scripts/analyze-image.py image.jpg "Detect all objects" --model gemini-2.0-flash
```
### Multi-Image Comparison
```bash
python scripts/analyze-image.py img1.jpg img2.jpg "What's different between these?"
```
### File Upload (for large files or reuse)
```bash
# Upload file
python scripts/upload-file.py path/to/large-image.jpg
# Use uploaded file
python scripts/analyze-image.py file://file-id "Caption this"
```
### File Management
```bash
# List uploaded files
python scripts/manage-files.py list
# Get file info
python scripts/manage-files.py get file-id
# Delete file
python scripts/manage-files.py delete file-id
```
## Token Costs
Images consume tokens based on size:
- **Small** (≤384px both dimensions): 258 tokens
- **Large**: Tiled into 768×768 chunks, 258 tokens each
**Token Formula**:
```
crop_unit = floor(min(width, height) / 1.5)
tiles = (width / crop_unit) × (height / crop_unit)
total_tokens = tiles × 258
```
**Example**: 960×540 image = 6 tiles = 1,548 tokens
## Rate Limits
Limits vary by tier (Free, Tier 1, 2, 3):
- Measured in RPM (requests/min), TPM (tokens/min), RPD (requests/day)
- Applied per project, not per API key
- RPD resets at midnight Pacific
## Best Practices
### Image Quality
- Use clear, non-blurry images
- Verify correct image rotation
- Consider token costs when sizing
### Prompting
- Be specific in instructions
- Place text after image for single-image prompts
- Use few-shot examples for better accuracy
- Specify output format (JSON, markdown, etc.)
### File Management
- Use File API for files >20MB
- Use File API for repeated usage (saves tokens)
- Files auto-delete after 48 hours
- Clean up manually when done
### Security
- Never expose API keys in code
- Use environment variables
- Add API key restrictions in Google Cloud Console
- Monitor usage regularly
- Rotate keys periodically
## Error Handling
Common errors:
- **401**: Invalid API key
- **429**: Rate limit exceeded
- **400**: Invalid request (check file size, format)
- **403**: Permission denied (check API key restrictions)
## Additional Resources
See the `references/` directory for:
- **api-reference.md**: Detailed API methods and endpoints
- **examples.md**: Comprehensive code examples
- **best-practices.md**: Advanced tips and optimization strategies
## Implementation Guide
When implementing Gemini vision features:
1. **Check API key availability** using the 3-step lookup
2. **Choose appropriate model** based on requirements:
- Need segmentation? Use 2.5+ models
- Need detection? Use 2.0+ models
- Need speed? Use Flash variants
- Need quality? Use Pro variants
3. **Validate inputs**:
- Check file format (PNG, JPEG, WEBP, HEIC, HEIF, PDF)
- Verify file size (<20MB for inline, >20MB use File API)
- Count images (max 3,600)
4. **Handle responses** appropriately:
- Parse structured output if requested
- Extract bounding boxes for object detection
- Process segmentation masks if applicable
5. **Manage files** efficiently:
- Upload large files via File API
- Reuse uploaded files when possible
- Clean up after use
## Scripts Overview
All scripts support the 3-step API key lookup:
- **analyze-image.py**: Main script for image analysis, supports inline and File API
- **upload-file.py**: Upload files to Gemini File API
- **manage-files.py**: List, get metadata, and delete uploaded files
Run any script with `--help` for detailed usage instructions.
---
**Official Documentation**: https://ai.google.dev/gemini-api/docs/image-understanding
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