Gemini Research Skill

Purpose

Route research tasks to Gemini CLI when:

• Real-time information is needed (Google Search grounding)
• Context exceeds Claude's 200k limit (Gemini has 1M)
• Need web-grounded factual answers

Unique Capability

What Gemini Does Better:

• Google Search grounding for current information
• 1M token context for massive document analysis
• 70+ extensions (Figma, Stripe, Shopify, etc.)
• Web content analysis with source attribution

When to Use

Perfect For:

• Current events, recent documentation
• Large codebase analysis (>150k tokens)
• Literature reviews with many papers
• Real-time API documentation lookup
• Market research, competitor analysis

Don't Use When:

• Offline/airgapped environments
• Complex multi-step reasoning (use Claude)
• Code generation requiring iteration (use Codex)

Usage

Basic Research

/gemini-research "What are the latest React 19 best practices?"

With Context Files

/gemini-research "Analyze architecture" --context @src/

Large Document Analysis

/gemini-research "Summarize all papers" --context papers/*.pdf

Command Pattern

bash scripts/multi-model/gemini-research.sh "<query>" "<task_id>" "json"

Memory Integration

Results stored to Memory-MCP:

• Key: multi-model/gemini/research/{task_id}
• Tags: WHO=gemini-cli, WHY=research

Output Format

{
  "content": "Research findings...",
  "sources": ["url1", "url2"],
  "model": "gemini-2.5-pro",
  "timestamp": "2025-12-28T..."
}

Handoff to Claude

After Gemini research completes:

1. Results stored in Memory-MCP
2. Claude agents read from memory key
3. Use research to inform implementation

// Claude agent reads Gemini research
const research = memory_retrieve("multi-model/gemini/research/{task_id}");
Task("Coder", `Implement using: ${research.content}`, "coder");

Configuration

• Retries: 3 attempts on failure
• Timeout: 60 seconds per query
• Fallback: Claude researcher agent if Gemini unavailable