fix: increase output token limit to prevent response truncation

- Add MAX_OUTPUT_TOKENS constant set to 32,768 (Gemini 2.5 Pro's limit)
- Update all tools and chat handler to use MAX_OUTPUT_TOKENS
- Add comprehensive tests for output token configuration
- Update README with configuration details and system prompt docs

This fixes the issue where Gemini responses were being cut off at 8192 tokens,
causing Claude to repeatedly ask for the same analysis.

Fixes #1

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

tools/base.py

@@ -9,6 +9,8 @@ import google.generativeai as genai
 from mcp.types import TextContent
 from pydantic import BaseModel, Field
 
+from config import MAX_OUTPUT_TOKENS
+
 
 class ToolRequest(BaseModel):
     """Base request model for all tools"""
@@ -17,7 +19,7 @@ class ToolRequest(BaseModel):
         None, description="Model to use (defaults to Gemini 2.5 Pro)"
     )
     max_tokens: Optional[int] = Field(
-        8192, description="Maximum number of tokens in response"
+        MAX_OUTPUT_TOKENS, description="Maximum number of tokens in response"
     )
     temperature: Optional[float] = Field(
         None, description="Temperature for response (tool-specific defaults)"
@@ -78,7 +80,7 @@ class BaseTool(ABC):
             temperature = getattr(request, "temperature", None)
             if temperature is None:
                 temperature = self.get_default_temperature()
-            max_tokens = getattr(request, "max_tokens", 8192)
+            max_tokens = getattr(request, "max_tokens", MAX_OUTPUT_TOKENS)
 
             # Create and configure model
             model = self.create_model(model_name, temperature, max_tokens)