gemini

Google Gemini AI models for multimodal tasks. Use for multimodal AI.

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byG1Joshi

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Best use case

gemini is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Google Gemini AI models for multimodal tasks. Use for multimodal AI.

Teams using gemini should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/gemini/SKILL.md --create-dirs "https://raw.githubusercontent.com/G1Joshi/Agent-Skills/main/skills/ai-ml/gemini/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/gemini/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How gemini Compares

Feature / Agent	gemini	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Google Gemini AI models for multimodal tasks. Use for multimodal AI.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Gemini

Gemini is Google's native multimodal model. Uniquely, it accepts **video** and huge context (2M+ tokens) natively. 2025 sees Gemini 2.0/3.0.

## When to Use

- **Massive Context**: "Here is a 1-hour video. Find the timestamp where..."
- **Multimodal Live**: Real-time voice/video interaction.
- **Google Ecosystem**: Integrated with Vertex AI, Search (Grounding), and Workspace.

## Core Concepts

### Models

- **Pro**: The best all-rounder.
- **Flash**: Extremely fast and cheap. High throughput.
- **Ultra**: The largest reasoning model.

### Grounding

Connects the model to Google Search to provide citations and up-to-date info.

### Context Initial Caching

Cache the context (e.g., a massive manual) to reduce cost/latency on subsequent queries.

## Best Practices (2025)

**Do**:

- **Use Flash for RAG**: 2.0 Flash is smart enough for most RAG & cheaper/faster.
- **Use Grounding**: Eliminate hallucinations by enforcing "Google Search" grounding.
- **Upload Video**: Don't transcribe video manually; Gemini watches it.

**Don't**:

- **Don't confuse with PaLM**: Gemini replaced PaLM 2 completely.

## References

- [Gemini API Documentation](https://ai.google.dev/)