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Glama

Refresh vehicle data

toyota_refresh_data
Read-onlyIdempotent

Refresh vehicle status, telemetry, and location from Toyota's cloud after parking to get the latest data without waking the car.

Instructions

Re-fetch status, telemetry and location from Toyota's cloud.

Rarely needed — the car pushes new data only at ignition-off, so answers refresh themselves as the car is driven. Use only when the user just parked and wants the very latest position or status. This reads Toyota's cloud; it never wakes the car.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteYes
freshnessYes
refreshedYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already signal read-only and non-destructive behavior, and the description adds value beyond them: it clarifies that the tool reads Toyota's cloud but 'never wakes the car.' It also explains the data freshness model, which helps the agent predict side effects and latency expectations.

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 compact and front-loaded: it states the action first, then the rare-use justification, then the safety-relevant non-behavior. Every sentence earns its place with no redundant filler.

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

Completeness5/5

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

With zero parameters, an output schema present, and annotations covering read-only/idempotent/non-destructive safety, the description supplies the missing contextual pieces: when the refresh is warranted and that it does not wake the vehicle. Nothing essential is left unspecified.

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 tool has zero parameters and 100% schema description coverage, so the description has no parameter semantics to explain. The baseline of 4 for a zero-parameter tool is appropriate.

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

Purpose5/5

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

The description states a specific verb and resource: 'Re-fetch status, telemetry and location from Toyota's cloud.' It also distinguishes itself from the getter siblings by noting that answers refresh themselves as the car is driven, and from wake_vehicle by explicitly saying it never wakes the car.

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

Usage Guidelines5/5

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

The description gives explicit when-to-use guidance: 'Use only when the user just parked and wants the very latest position or status.' It also explains when not to use it, calling it 'Rarely needed' because the car pushes data at ignition-off and answers self-refresh while driving.

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