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Wait for a ride update

wait_for_ride_update
Read-only

Wait for a ride status change and return the updated state, or the current state if the timeout expires. Call repeatedly to track each change and inform the user as it happens.

Instructions

Waits until the ride changes (driver found, driver arrived, trip started, finished, cancelled) and returns the new state, or returns the current state when the wait times out. Call it in a loop to follow a ride and tell the user each change as it happens.

Input Schema

NameRequiredDescriptionDefault
ride_idNoOmit to follow the current active ride.
timeout_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With readOnlyHint=true already covering safety, the description contributes real behavioral detail: the call blocks until a state change, and it returns the current state rather than an error when the wait times out. What is not disclosed is whether the call holds a connection, any rate limiting on repeated loops, or behavior for an invalid or unknown ride_id.

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 sentences, both earning their place: the first defines the blocking behavior and return semantics, the second defines the calling pattern. The blocking behavior is front-loaded, and there is no filler or repetition of the title.

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

Completeness4/5

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

For a two-parameter read-only long-poll tool with no output schema, the description covers the timing and retry model well. The remaining gap is that 'returns the new state' does not hint at what the state object contains (status, driver details), which the agent would need in order to relay changes to the user without an output schema to consult.

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 ride_id parameter is documented in the schema ('omit to follow the current active ride'), but timeout_seconds has no prose at all - only a default and 5-240 bounds - and the description never mentions it. The phrase 'returns the current state when the wait times out' only indirectly conveys what the timeout controls, so the description adds little beyond the schema's 50% coverage.

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 names a specific verb and resource ('waits until the ride changes') and enumerates the exact state transitions it watches for (driver found, arrived, trip started, finished, cancelled). It implicitly separates itself from the snapshot-style sibling get_ride_status by emphasizing that it blocks until a change, though it never names that sibling explicitly.

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

Usage Guidelines4/5

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

'Call it in a loop to follow a ride and tell the user each change as it happens' gives a clear operating pattern and context for use. It stops short of explicit exclusions, e.g. whether to prefer get_ride_status for a one-off check or when to stop looping (for example after finished/cancelled), so there is room left to inference.

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