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lodordev

mcp-teslamate-fleet

tesla_location_history

Analyze vehicle location patterns by grouping positions into clusters and displaying time spent at each location over a specified period.

Instructions

Where the car has been — top locations by time spent.

Groups positions by proximity and shows time at each cluster.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo

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 full burden. It describes the output behavior (grouping by proximity, showing time per cluster) but doesn't disclose critical traits like whether this is a read-only operation, data freshness, rate limits, authentication needs, or potential side effects. For a location history tool with no annotations, this leaves significant gaps.

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. The first sentence immediately states the purpose, and the second adds necessary detail about clustering. Every word earns its place with zero waste or redundancy.

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 that an output schema exists, the description doesn't need to explain return values. However, for a tool with no annotations, 0% schema description coverage, and multiple similar siblings, the description is minimal. It covers the basic purpose but lacks usage context, parameter semantics, and behavioral transparency needed for full understanding.

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

Parameters3/5

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

The description adds no parameter information beyond what the schema provides. With 0% schema description coverage and 1 parameter ('days'), the description doesn't explain what 'days' means (e.g., lookback period, default behavior). However, since there's only one parameter with a default, the baseline is 3—adequate but with clear gaps in documentation.

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 what the tool does: it shows where the car has been by grouping positions into clusters and displaying time spent at each. It uses specific verbs ('groups', 'shows') and identifies the resource (car locations/history). However, it doesn't explicitly differentiate from sibling tools like 'tesla_top_destinations' or 'tesla_drives', which may have overlapping functionality.

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. With siblings like 'tesla_top_destinations', 'tesla_drives', and 'tesla_state_history', there's no indication of how this tool differs in scope or output. It lacks explicit when-to-use or when-not-to-use instructions.

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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