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Check a saved commute for a travel date

check_commute
Read-onlyIdempotent

Checks a saved train route against National Rail’s running records for one travel date and works out Delay Repay: the matched train, the delay, the amount, the deadline and a claim pack. When several trains match, the result lists them, each with a service_id. A saved route does not show that the person travelled that day, and the result says so. Nothing is saved or filed. Requires sign-in to Untap.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesThe travel date to check, preferably YYYY-MM-DD. "yesterday" also works.
commute_idYesThe id of a saved commute.
service_idNoThe service_id of a train listed in an earlier result. With it, that train is checked directly.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • changedInput schema / properties / commute_id / description
      Previous value: -"The id returned by save_commute or list_commutes."New value: +"The id of a saved commute."
    • changedInput schema / properties / date / description
      Previous value: -"Specific travel date requested by the person, preferably YYYY-MM-DD. Yesterday also works. Never assume they travelled."New value: +"The travel date to check, preferably YYYY-MM-DD. \"yesterday\" also works."
    • changedInput schema / properties / service_id / description
      Previous value: -"A candidate service_id from an earlier check, to confirm the actual train."New value: +"The service_id of a train listed in an earlier result. With it, that train is checked directly."
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent and non-destructive, but the description adds real context beyond them: 'Nothing is saved or filed', sign-in to Untap is required, and a saved route does not prove travel (with the result stating so). It still doesn't cover rate limits or error modes, so not a 5.

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?

Four compact sentences, front-loaded with what is computed before the caveats and auth note. Each sentence carries distinct information (output, multi-match handling, limitation, side effects/auth) with no repetition.

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 no output schema, the description compensates by enumerating the return contents (matched train, delay, amount, deadline, claim pack, service_id per match) and stating the read-only, sign-in-gated behavior. Nothing an agent needs to call it correctly 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 schema already documents all three parameters; baseline is 3. The description adds operational meaning by tying service_id to the multi-match flow ('When several trains match, the result lists them, each with a service_id'), which explains why that optional parameter exists.

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?

States a precise verb ('checks') and resource ('a saved train route') against a named data source (National Rail running records) for 'one travel date', and its output scope (Delay Repay amount, deadline, claim pack). 'Saved' distinguishes it from sibling check_train_delay, which operates on a one-off journey.

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?

Clear context for use: a saved commute (requiring commute_id) checked for a single date, with the service_id path described for disambiguating multiple matches. It does not explicitly say when to prefer check_train_delay or add_train_journey instead, so it falls short of stating alternatives.

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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