Agent skill

Gemini Vision

Guide for implementing Google Gemini API image understanding - analyze images with captioning, classification, visual QA, object detection, segmentation, and multi-image comparison.

MITAuto-check: notesAI & LLM Engineering

Install Gemini Vision

skills CLI

$ npx skills add einverne/dotfiles --skill gemini-vision -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install einverne/dotfiles gemini-vision --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/einverne/dotfiles.git skills-src && mkdir -p .claude/skills && cp -r skills-src/claude/skills/gemini-vision .claude/skills/gemini-vision && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "gemini-vision" agent skill from https://github.com/einverne/dotfiles/tree/master/claude/skills/gemini-vision into .claude/skills/gemini-vision/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gemini-vision", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/einverne/dotfiles/tree/master/claude/skills/gemini-vision

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add einverne/dotfiles --skill gemini-vision -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install einverne/dotfiles gemini-vision --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/einverne/dotfiles.git skills-src && mkdir -p .agents/skills && cp -r skills-src/claude/skills/gemini-vision .agents/skills/gemini-vision && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "gemini-vision" agent skill from https://github.com/einverne/dotfiles/tree/master/claude/skills/gemini-vision into .agents/skills/gemini-vision/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gemini-vision", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add einverne/dotfiles --skill gemini-vision -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install einverne/dotfiles gemini-vision --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/einverne/dotfiles.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/claude/skills/gemini-vision .cursor/skills/gemini-vision && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "gemini-vision" agent skill from https://github.com/einverne/dotfiles/tree/master/claude/skills/gemini-vision into .cursor/skills/gemini-vision/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gemini-vision", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/einverne/dotfiles.git --path claude/skills/gemini-vision

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add einverne/dotfiles --skill gemini-vision -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install einverne/dotfiles gemini-vision --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/einverne/dotfiles.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/claude/skills/gemini-vision .gemini/skills/gemini-vision && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "gemini-vision" agent skill from https://github.com/einverne/dotfiles/tree/master/claude/skills/gemini-vision into .gemini/skills/gemini-vision/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gemini-vision", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install einverne/dotfiles gemini-vision

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add einverne/dotfiles --skill gemini-vision -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/einverne/dotfiles.git skills-src && mkdir -p .github/skills && cp -r skills-src/claude/skills/gemini-vision .github/skills/gemini-vision && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "gemini-vision" agent skill from https://github.com/einverne/dotfiles/tree/master/claude/skills/gemini-vision into .github/skills/gemini-vision/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gemini-vision", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add einverne/dotfiles --skill gemini-vision -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install einverne/dotfiles gemini-vision --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/einverne/dotfiles.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/claude/skills/gemini-vision .opencode/skills/gemini-vision && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "gemini-vision" agent skill from https://github.com/einverne/dotfiles/tree/master/claude/skills/gemini-vision into .opencode/skills/gemini-vision/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gemini-vision", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: gemini-vision
GitHub stars: 121
Token cost: ~1.6k tokens
SKILL.md length: 586 words
Files: 8 (incl. scripts, references)
Skills in repo: 39
Repo updated: Sep 9, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Guide for implementing Google Gemini API image understanding - analyze images with captioning, classification, visual QA, object detection, segmentation, and multi-image comparison.

Works in 2 steps: Get API Key: Obtain from Google AI Studio → Install SDK: pip install google-genai…
Analyzing images
SKILL.md covers Quick Start, Core Capabilities, Supported Formats and Available Models, plus 8 more sections
Runs Python scripts from its folder; calls python and pip; needs GEMINI_API_KEY

What it does

Gemini Vision is an agent skill from einverne/dotfiles. 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.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `README.md`, `references/api-reference.md` and `references/best-practices.md`).

It sits in AI & LLM Engineering, covering Computer vision and Visual regression testing. It works with Google Gemini. The repository describes itself as: my personal dotfiles managed by dotbot, zinit. The licence is MIT.

When your agent uses it

Analyzing images
Answering visual questions
Detecting objects
Processing documents with vision

Example prompts

“/gemini-vision”

Requirements

Python 3
A credential in GEMINI_API_KEY
Pre-approved tools (allowed-tools): Bash, Read, Write, Edit

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

Get API Key: Obtain from Google AI Studio
Install SDK: pip install google-genai (Python 3.9+)

What it can do on your machine

Read from SKILL.md and the folder at commit c6c0686. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
- Bash
- Read
- Write
- Edit
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 3 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python
- pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- aistudio.google.com
- ai.google.dev
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- GEMINI_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Gemini Vision loads about 1.6k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 77 tokens; SKILL.md has 586 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~77
When it runs · the whole SKILL.md, loaded when a task matches: ~1.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~11k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NoteMentions a .env fileSKILL.md:32

rectory**: `.claude/skills/gemini-vision/.env`

NoteMentions a .env fileSKILL.md:37

3. **Project directory**: `.env` or `.gemini_api_key` in project root

NoteMentions a .env fileSKILL.md:39

commit API keys to version control. Add `.env` to `.gitignore`.

NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
```
allowed-tools: Bash, Read, Write, Edit
```

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from einverne/dotfiles at commit c6c0686, republished under its MIT licence (© einverne). 586 words, ~1,577 tokens.

Download SKILL.mdSave it as .claude/skills/gemini-vision/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.

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.
allowed-tools: Bash, Read, Write, Edit
license: MIT

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

Get API Key: Obtain from Google AI Studio
Install SDK: pip install google-genai (Python 3.9+)

API Key Configuration

The skill checks for GEMINI_API_KEY in this order:

Process environment variable (recommended)
bash
```
export GEMINI_API_KEY="your-api-key"
```
Skill directory: .claude/skills/gemini-vision/.env
```
GEMINI_API_KEY=your-api-key
```
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

Show full SKILL.md (229 more words)Show less

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:

Check API key availability using the 3-step lookup
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
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)
Handle responses appropriately:
- Parse structured output if requested
- Extract bounding boxes for object detection
- Process segmentation masks if applicable
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

Files

SKILL.md and 7 other files (scripts, references) in claude/skills/gemini-vision of einverne/dotfiles.

SKILL.md
README.md
references/api-reference.md
references/best-practices.md
references/examples.md
scripts/analyze-image.py
scripts/manage-files.py
scripts/upload-file.py

Open the folder on GitHubat commit c6c0686

Compare with similar skills

Gemini Vision next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Gemini Vision compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Gemini Vision this skilleinverne/dotfiles	121	—	~1.6k	Automated safety check: Notes	MIT	1 mo ago
ModLens Image Vision Bridgeliustack/modlens	4.2k	—	~1.3k	Automated safety check: Notes	MIT	5 days ago
Vision Model Retry Policyskuramatata/my-pi-agent	114	—	~1k	Automated safety check: Pass	None	3 mo ago
Multimodal Media Feature ExtractionTyrealQ/q-skills	108	—	~2k	Automated safety check: Notes	MIT	16 days ago
Gemini Video Understandingbenchflow-ai/skillsbench	1.8k	—	~2.4k	Automated safety check: Pass	Apache-2.0	2 mo ago
Thumbnail Creatormohitagw15856/pm-claude-skills	1.4k	—	~6.3k	Automated safety check: Pass	MIT	yesterday

Similar skills

ModLens Image Vision Bridge
liustack/modlens
Gives text-only models sight by running the modlens CLI on an image path or URL and returning structured JSON evidence with transcribed text, layout and semantics.
4.2k GitHub stars~1.3k tokensUpdated 5 days ago
AI & LLM EngineeringAuto-check: notes
Vision Model Retry Policy
skuramatata/my-pi-agent
A skill your agent uses when image reading, screenshot analysis, visual diff, design mockup analysis, pasted image handling, or Z.AI Vision MCP fails, times out, returns 429/Too Many Requests, or…
114 GitHub stars~1k tokensUpdated 3 mo ago
AI & LLM EngineeringAuto-check passed
Multimodal Media Feature Extraction
TyrealQ/q-skills
Extracts pixel, video-frame, speech, music and visual-semantic features from image, video and audio files for research datasets, using local tools or the Gemini API.
108 GitHub stars~2k tokensUpdated 16 days ago
Data & AnalyticsAuto-check: notes
Gemini Video Understanding
benchflow-ai/skillsbench
Analyze videos with Google Gemini API (summaries, Q&A, transcription with timestamps + visual context, scene/timeline detection, video clipping, FPS control, multi-video comparison, and YouTube URL…
1.8k GitHub stars~2.4k tokensUpdated 2 mo ago
Media & CreativeAuto-check passed
Thumbnail Creator
mohitagw15856/pm-claude-skills
Generate article or newsletter thumbnail candidates using the Gemini API from inside Claude Code.
1.4k GitHub stars~6.3k tokensUpdated yesterday
Media & CreativeAuto-check passed
Segment Anything Model Guide
Orchestra-Research/AI-Research-SKILLs
Guide to using Meta's Segment Anything Model for zero-shot image segmentation with point, box or mask prompts, or automatic mask generation.
13k GitHub starsUsed in 8 repos~3.3k tokens
AI & LLM EngineeringAuto-check passed

Questions about Gemini Vision

What does Gemini Vision do?

Guide for implementing Google Gemini API image understanding - analyze images with captioning, classification, visual QA, object detection, segmentation, and multi-image comparison. Gemini Vision is an agent skill from einverne/dotfiles. Guide for implementing Google Gemini API image understanding - analyze images with captioning, classification, visual QA, object detection, segmentation, and multi-image comparison.

When should I use Gemini Vision?

Gemini Vision fits situations like: analyzing images; answering visual questions; detecting objects; processing documents with vision.

How do I install Gemini Vision in Claude Code?

Run `npx skills add einverne/dotfiles --skill gemini-vision -a claude-code`. Or copy the skill folder (claude/skills/gemini-vision in einverne/dotfiles) into .claude/skills/gemini-vision in your project. Claude Code loads it when a task matches its description.

How do I install Gemini Vision in Codex?

Run `npx skills add einverne/dotfiles --skill gemini-vision -a codex`. Or copy the skill folder (claude/skills/gemini-vision in einverne/dotfiles) into .agents/skills/gemini-vision in your project. Codex loads it when a task matches its description.

Can I use Gemini Vision in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add einverne/dotfiles --skill gemini-vision -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gemini-vision, .gemini/skills/gemini-vision, .github/skills/gemini-vision and .opencode/skills/gemini-vision in your project.

What does Gemini Vision need to run?

Going by SKILL.md and its folder, Gemini Vision needs Python for the scripts in its folder, the command-line tools its instructions call (python and pip) and credentials named GEMINI_API_KEY. Our summary lists: Python 3; A credential in GEMINI_API_KEY. Its frontmatter pre-approves these tools: Bash, Read, Write, Edit.

Does Gemini Vision access the network?

SKILL.md names 2 domains. As links in the text: aistudio.google.com and ai.google.dev. This is read from the text; nothing was executed.

Is Gemini Vision safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file; pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Gemini Vision use?

Gemini Vision is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Gemini Vision use?

About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 9.8k tokens, read only when the agent opens those files.

What are the alternatives to Gemini Vision?

Skills that share tags, products or a category with Gemini Vision: ModLens Image Vision Bridge (liustack/modlens, 4.2k stars), Vision Model Retry Policy (skuramatata/my-pi-agent, 114 stars), Multimodal Media Feature Extraction (TyrealQ/q-skills, 108 stars) and Gemini Video Understanding (benchflow-ai/skillsbench, 1.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Gemini Vision?

einverne (a GitHub user) maintains it in einverne/dotfiles, which has 121 GitHub stars. The repository holds 39 skills in this directory. The repository was last updated on September 9, 2026.

Source: einverne/dotfiles on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Gemini Vision

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Gemini Vision API Skill

Quick Start

Prerequisites

API Key Configuration

Core Capabilities

Image Analysis

Advanced Features (Model-Specific)

Supported Formats

Available Models

Usage Examples

Basic Image Analysis

Object Detection (2.0+)

Multi-Image Comparison

File Upload (for large files or reuse)

File Management

Token Costs

Rate Limits

Best Practices

Image Quality

Prompting

File Management

Security

Error Handling

Additional Resources

Implementation Guide

Scripts Overview

Files

Compare with similar skills

Similar skills

More from einverne/dotfiles

Related

Questions about Gemini Vision