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cobanov

teslamate-mcp

get_drive_summary_per_day

Retrieve daily driving statistics for Tesla vehicles, including distance traveled, duration, and energy efficiency metrics from TeslaMate data.

Instructions

Get the drive summary per day for each car. Provides daily driving statistics including distance, duration, and efficiency.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • src/tools.py:62-66 (registration)
    ToolDefinition registering the 'get_drive_summary_per_day' tool with its description and associated SQL query file.
    ToolDefinition(
        name="get_drive_summary_per_day",
        description="Get the drive summary per day for each car. Provides daily driving statistics including distance, duration, and efficiency.",
        sql_file="drive_summary_per_day.sql",
    ),
  • main.py:22-28 (handler)
    Handler factory that creates the execution function for the tool, which runs the SQL query from the specified file synchronously.
    def create_tool_handler(sql_file: str):
        """Factory function to create tool handlers"""
    
        def handler() -> List[Dict[str, Any]]:
            return db_manager.execute_query_sync(sql_file)
    
        return handler
  • main.py:31-39 (registration)
    Dynamic registration loop that creates and registers the handler for each tool, including 'get_drive_summary_per_day', with the MCP server.
    # Register all tools from definitions
    for tool_def in TOOL_DEFINITIONS:
        tool_func = create_tool_handler(tool_def.sql_file)
        tool_func.__doc__ = tool_def.description
        tool_func.__name__ = tool_def.name
    
        # Register the tool with the MCP server
        mcp.tool()(tool_func)
  • Async handler function for executing predefined tools by name, including 'get_drive_summary_per_day', using the async database query execution.
    async def execute_predefined_tool(tool_name: str) -> List[Dict[str, Any]]:
        """Execute a predefined tool by name"""
        if not app_context:
            raise RuntimeError("Application context not initialized")
    
        tool = get_tool_by_name(tool_name)
        return await app_context.db_manager.execute_query_async(
            tool.sql_file, app_context.db_pool
        )
  • main_remote.py:178-186 (registration)
    Registration of all predefined tools, including schema (empty input), in the list_tools MCP method for the remote HTTP server.
    # Add all predefined tools
    for tool_def in TOOL_DEFINITIONS:
        tools.append(
            types.Tool(
                name=tool_def.name,
                description=tool_def.description,
                inputSchema={"type": "object", "properties": {}},
            )
        )
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It states what data is returned but doesn't cover critical aspects like whether this is a read-only operation, authentication requirements, rate limits, or how data is formatted (e.g., aggregated vs. raw). This is inadequate for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise and front-loaded: two sentences that directly state the tool's purpose and what it provides, with no wasted words. Every sentence adds value by clarifying the scope and content of the summary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no parameters, an output schema exists, and no annotations are provided, the description is minimally adequate. It explains what data is returned but lacks context on behavioral traits like safety or performance. With output schema handling return values, the description meets basic needs but could improve by addressing usage scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's output semantics, which aligns with the baseline for zero-parameter tools.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get the drive summary per day for each car' with specific details about what statistics are included (distance, duration, efficiency). It distinguishes itself from siblings like 'get_daily_driving_patterns' by focusing on summary statistics rather than patterns, though the differentiation could be more explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, timing considerations, or how it differs from similar tools like 'get_daily_driving_patterns' or 'get_monthly_driving_summary,' leaving the agent without context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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