mcp-teslamate-fleet

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions what data is shown but doesn't cover critical aspects like authentication requirements, rate limits, data freshness, or whether this is a read-only operation. For a tool accessing vehicle data with no annotation coverage, this is a significant gap in transparency.

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

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

The description is appropriately sized and front-loaded: the first sentence states the core functionality, and the second adds key details without redundancy. Every sentence earns its place by providing essential information efficiently, with no wasted words.

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

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

Given the tool's moderate complexity (historical data retrieval), no annotations, and the presence of an output schema (which handles return values), the description is minimally adequate. It covers the basic purpose and parameter semantics but lacks behavioral context and usage guidelines, leaving gaps for an AI agent to infer proper use.

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

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

The description adds meaningful context for the single parameter 'days' by specifying it as 'the last N days,' which clarifies its purpose beyond the schema's basic type (integer) and default (30). With 0% schema description coverage, the description effectively compensates by explaining the parameter's role, though it doesn't detail constraints like valid ranges.

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

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

The description clearly states the tool's purpose: retrieving charging sessions over a specified time period with specific data fields (energy added, duration, battery range, location). It uses specific verbs ('shows') and identifies the resource ('charging sessions'), but doesn't explicitly differentiate from sibling tools like 'tesla_charging_by_location' or 'tesla_drives' which might overlap in scope.

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

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 sibling tools like 'tesla_charging_by_location' (which might filter by location) or 'tesla_drives' (which might include driving data), nor does it specify prerequisites or exclusions. Usage is implied through the description but not explicitly stated.

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