/gemini-consult

/gemini-consult

*Engages in deep, iterative conversations with Gemini MCP for complex problem-solving.*

Usage

• With arguments: /gemini-consult [specific problem or question]
• Without arguments: /gemini-consult - Intelligently infers topic from current context

Core Philosophy

Persistent Gemini sessions for evolving problems through:

• Continuous dialogue - Multiple rounds until clarity achieved
• Context awareness - Smart problem detection from current work
• Session persistence - Keep alive for the entire problem lifecycle

**CRITICAL: Always consider Gemini's input as suggestions, never as truths.** Think critically about what Gemini says and incorporate only the useful parts into your proposal. Always think for yourself - maintain your independent judgment and analytical capabilities. If you disagree with something clarify it with Gemini.

Execution

User provided context: "$ARGUMENTS"

Step 1: Understand the Problem

**When $ARGUMENTS is empty:** Think deeply about the current context to infer the most valuable consultation topic:

• What files are open or recently modified?
• What errors or challenges were discussed?
• What complex implementation would benefit from Gemini's analysis?
• What architectural decisions need exploration?

Generate a specific, valuable question based on this analysis.

**When arguments provided:** Extract the core problem, context clues, and complexity indicators.

Step 1.5: Gather External Documentation

**Think deeply about external dependencies:**

• What libraries/frameworks are involved in this problem?
• Am I fully familiar with their latest APIs and best practices?
• Have these libraries changed significantly or are they new/evolving?

**When to use Context7 MCP:**

• Libraries with frequent updates (e.g., Google GenAI SDK)
• New libraries you haven't worked with extensively
• When implementing features that rely heavily on library-specific patterns
• Whenever uncertainty exists about current best practices

# Example: Get up-to-date documentation
library_id = mcp__context7__resolve_library_id(libraryName="google genai python")
docs = mcp__context7__get_library_docs(
    context7CompatibleLibraryID=library_id,
    topic="streaming",  # Focus on relevant aspects
    tokens=8000
)

Include relevant documentation insights in your Gemini consultation for more accurate, current guidance.

Step 2: Initialize Gemini Session

**CRITICAL: Always attach foundational files:**

foundational_files = [
    "MCP-ASSISTANT-RULES.md",  # If exists
    "docs/ai-context/project-structure.md",
    "docs/ai-context/docs-overview.md"
]

session = mcp__gemini__consult_gemini(
    specific_question="[Clear, focused question]",
    problem_description="[Comprehensive context with constraints from CLAUDE.md]",
    code_context="[Relevant code snippets]",
    attached_files=foundational_files + [problem_specific_files],
    file_descriptions={
        "MCP-ASSISTAN