| name | gemini-analyst |
| description | Background knowledge for using the Gemini Bridge MCP tools effectively. Teaches Claude when and how to delegate to Gemini in a model-agnostic multi-agent setup. Claude-invocable only.
|
| user-invocable | false |
Gemini Bridge: Usage Patterns
When to Delegate to Gemini
Token Budget Rule
Estimate token count before analysis:
- < 150K tokens → Claude handles directly
-
150K tokens → Delegate to Gemini
Quick estimation: ~750 tokens per ~600 words, ~500 tokens per ~400 lines of code.
Vision Rule
For image analysis tasks where Gemini's vision capabilities or extended context
provide an advantage, prefer gemini_analyze_image. Claude Code can also read
images natively via the Read tool, so use Gemini when the analysis requires
Gemini-specific strengths (e.g., large diagrams, complex OCR, PDF parsing).
Validation Rule
For architecture decisions, security reviews, or critical design choices:
Use gemini_compare_approaches to get an independent assessment.
This implements the "propose with Claude, validate with Gemini" pattern.
Tool Reference
gemini_status()
gemini_analyze_text(prompt, context=None, temperature=0.2)
gemini_analyze_codebase(code_content, task, language=None)
gemini_analyze_image(image_path, question)
gemini_compare_approaches(problem, approach_a, approach_b, criteria=None)
Output Attribution Pattern
Always label Gemini's output clearly:
**Analysis by Gemini 2.5 Pro**
[Gemini's response]
This is important for:
- Transparency in multi-model workflows
- Audit trails in educational settings
- Debugging when models disagree
Model-Agnostic Design Principle
The bridge is designed so that the routing logic lives in agent configuration,
not in application code. To swap Gemini for a different model:
- Set the
GEMINI_MODEL environment variable
- All agents/commands continue working unchanged
This demonstrates to students: good architecture is model-agnostic.
