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lodordev

mcp-teslamate-fleet

tesla_top_destinations

Identify frequently visited locations from Tesla vehicle data to analyze travel patterns and common destinations.

Instructions

Most visited locations ranked by number of visits.

Args: limit: Number of destinations to show (default: 15)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions ranking by 'number of visits,' which implies read-only behavior, but doesn't disclose critical details like data freshness, permissions needed, rate limits, or whether it accesses personal or aggregated data. For a tool with zero annotation coverage, this is a significant gap in behavioral context.

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 appropriately sized and front-loaded: the first sentence states the core purpose, and the second provides essential parameter details. There's no wasted text, and the structure is clear with a brief 'Args' section. Every sentence earns its place.

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's low complexity (1 parameter, no nested objects) and the presence of an output schema (which handles return values), the description is minimally adequate. It covers the purpose and parameter semantics but lacks usage guidelines and behavioral transparency, which are notable gaps for a tool with no annotations.

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 description adds meaningful context for the single parameter: 'limit: Number of destinations to show (default: 15).' With 0% schema description coverage (the schema only defines the type and default), this compensates well by explaining the parameter's purpose and default value. However, it doesn't specify constraints (e.g., min/max values), so it's not a full 5.

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: 'Most visited locations ranked by number of visits.' It specifies the verb ('ranked') and resource ('locations'), and distinguishes it from siblings like 'tesla_location_history' or 'tesla_drives' by focusing on ranking rather than raw history or trip data. However, it doesn't explicitly differentiate from all siblings (e.g., 'tesla_charging_by_location'), so it's not a perfect 5.

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, context (e.g., historical data availability), or compare it to siblings like 'tesla_location_history' for unfiltered data or 'tesla_longest_trips' for distance-based rankings. This leaves the agent with minimal direction.

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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