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Use Gemini CLI for research with Google Search grounding and 1M token context
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Baseado na classificação ocupacional SOC
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Use when conducting comprehensive code review for pull requests across multiple quality dimensions. Orchestrates 12-15 specialized reviewer agents across 4 phases using star topology coordination. Covers automated checks, parallel specialized reviews (quality, security, performance, architecture, documentation), integration analysis, and final merge recommendation in a 4-hour workflow.
Create Claude Code hooks with proper schemas, RBAC integration, and performance requirements. Use when implementing PreToolUse, PostToolUse, SessionStart, or any of the 10 hook event types for automation, validation, or security enforcement.
| name | gemini-research |
| description | Use Gemini CLI for research with Google Search grounding and 1M token context |
| allowed-tools | Bash, Read, Write, TodoWrite, WebFetch, Glob, Grep |
Before writing ANY code, you MUST check:
.claude/library/catalog.json.claude/docs/inventories/LIBRARY-PATTERNS-GUIDE.mdD:\Projects\*| Match | Action |
|---|---|
| Library >90% | REUSE directly |
| Library 70-90% | ADAPT minimally |
| Pattern exists | FOLLOW pattern |
| In project | EXTRACT |
| No match | BUILD (add to library after) |
Route research tasks to Gemini CLI when:
What Gemini Does Better:
/gemini-research "What are the latest React 19 best practices?"
/gemini-research "Analyze architecture" --context @src/
/gemini-research "Summarize all papers" --context papers/*.pdf
bash scripts/multi-model/gemini-research.sh "<query>" "<task_id>" "json"
Results stored to Memory-MCP:
multi-model/gemini/research/{task_id}{
"content": "Research findings...",
"sources": ["url1", "url2"],
"model": "gemini-2.5-pro",
"timestamp": "2025-12-28T..."
}
After Gemini research completes:
// Claude agent reads Gemini research
const research = memory_retrieve("multi-model/gemini/research/{task_id}");
Task("Coder", `Implement using: ${research.content}`, "coder");