feat: add Claude-Gemini collaboration and chat capabilities

- Add collaboration demo showing dynamic context requests
- Implement chat tool for general conversations and brainstorming
- Add tool selection guide with clear boundaries
- Introduce models configuration system
- Update prompts for better tool descriptions
- Refactor server to remove redundant functionality
- Add comprehensive tests for collaboration features
- Enhance base tool with collaborative features

This enables Claude to request additional context from Gemini
during tool execution, improving analysis quality and accuracy.

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

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

tools/chat.py

@@ -0,0 +1,111 @@
+"""
+Chat tool - General development chat and collaborative thinking
+"""
+
+from typing import Any, Dict, List, Optional
+
+from pydantic import Field
+
+from config import MAX_CONTEXT_TOKENS, TEMPERATURE_BALANCED
+from prompts import CHAT_PROMPT
+from utils import check_token_limit, read_files
+
+from .base import BaseTool, ToolRequest
+
+
+class ChatRequest(ToolRequest):
+    """Request model for chat tool"""
+
+    prompt: str = Field(
+        ...,
+        description="Your question, topic, or current thinking to discuss with Gemini",
+    )
+    context_files: Optional[List[str]] = Field(
+        default_factory=list, description="Optional files for context"
+    )
+
+
+class ChatTool(BaseTool):
+    """General development chat and collaborative thinking tool"""
+
+    def get_name(self) -> str:
+        return "chat"
+
+    def get_description(self) -> str:
+        return (
+            "GENERAL CHAT & COLLABORATIVE THINKING - Use Gemini as your thinking partner! "
+            "Perfect for: bouncing ideas during your own analysis, getting second opinions on your plans, "
+            "collaborative brainstorming, validating your checklists and approaches, exploring alternatives. "
+            "Also great for: explanations, comparisons, general development questions. "
+            "Triggers: 'ask gemini', 'brainstorm with gemini', 'get gemini's opinion', 'discuss with gemini', "
+            "'share my thinking with gemini', 'explain', 'what is', 'how do I'."
+        )
+
+    def get_input_schema(self) -> Dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "prompt": {
+                    "type": "string",
+                    "description": "Your question, topic, or current thinking to discuss with Gemini",
+                },
+                "context_files": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "Optional files for context",
+                },
+                "temperature": {
+                    "type": "number",
+                    "description": "Response creativity (0-1, default 0.5)",
+                    "minimum": 0,
+                    "maximum": 1,
+                },
+                "thinking_mode": {
+                    "type": "string",
+                    "enum": ["minimal", "low", "medium", "high", "max"],
+                    "description": "Thinking depth: minimal (128), low (2048), medium (8192), high (16384), max (32768)",
+                },
+            },
+            "required": ["prompt"],
+        }
+
+    def get_system_prompt(self) -> str:
+        return CHAT_PROMPT
+
+    def get_default_temperature(self) -> float:
+        return TEMPERATURE_BALANCED
+
+    def get_request_model(self):
+        return ChatRequest
+
+    async def prepare_prompt(self, request: ChatRequest) -> str:
+        """Prepare the chat prompt with optional context files"""
+        user_content = request.prompt
+
+        # Add context files if provided
+        if request.context_files:
+            file_content, _ = read_files(request.context_files)
+            user_content = f"{request.prompt}\n\n=== CONTEXT FILES ===\n{file_content}\n=== END CONTEXT ==="
+
+        # Check token limits
+        within_limit, estimated_tokens = check_token_limit(user_content)
+        if not within_limit:
+            raise ValueError(
+                f"Content too large (~{estimated_tokens:,} tokens). "
+                f"Maximum is {MAX_CONTEXT_TOKENS:,} tokens."
+            )
+
+        # Combine system prompt with user content
+        full_prompt = f"""{self.get_system_prompt()}
+
+=== USER REQUEST ===
+{user_content}
+=== END REQUEST ===
+
+Please provide a thoughtful, comprehensive response:"""
+
+        return full_prompt
+
+    def format_response(self, response: str, request: ChatRequest) -> str:
+        """Format the chat response (no special formatting needed)"""
+        return response