Skip to main content
Glama

Unlock the doors

toyota_unlock_doors
DestructiveIdempotent

Unlock the car doors after an explicit user request and verify the car's reported door state. Preview the action first with confirm disabled; send only after the user confirms.

Instructions

Unlock the doors, then verify against the state the car reports.

Security-sensitive: only when the user explicitly asked to unlock the car in this conversation, never on your own initiative. Preview with confirm=false unless the user already confirmed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confirmNotrue sends the command to the car; false (default) only previews what would happen and sends nothing.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
doorsNo
detailYes
statusYes'needs_confirmation' = nothing was sent; 'verified' = the car reported the new state; 'accepted' = Toyota accepted the command but the car has not confirmed it yet; 'failed' = the car rejected it.
climateNo
commandYes
chargingNo
elapsed_secondsNo

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 indicate this is mutating (readOnlyHint=false), destructive (destructiveHint=true), and idempotent (idempotentHint=true). The description adds beyond that: post-action verification against reported car state, an explicit security gate, and preview-vs-send behavior that is not available from annotations alone.

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?

Two tight sentences front-load the action and verification, then add the security and confirmation guidance. Every sentence earns its place with no filler or repetition of schema data.

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?

For a single-parameter tool with an existing output schema, the description covers what the tool does, when it is permitted, and how to handle confirmation. The sibling list makes the intended action unambiguous, and no critical usage context is missing.

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?

Schema coverage is 100%, so the baseline is 3. The description adds a meaningful policy on top of the schema: preview with confirm=false unless the user already confirmed. It does not fully restate the schema but reinforces the decision rule, which is helpful for correct invocation.

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 clear action ('Unlock the doors') and adds a verification step, making it distinct from sibling tools like toyota_lock_doors and toyota_unlock_trunk. The verb and resource are specific and immediately recognizable.

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 explicitly says this is security-sensitive, only to be used when the user explicitly asked in the conversation, and never on the model's own initiative. It also gives concrete preview guidance: use confirm=false unless the user has already confirmed. This is model-actionable usage context.

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