Skip to main content
Glama

service_details

Get live times and all stops for a specific train service using its service ID, with real-time updates where available.

Instructions

All stops for one train, with live times where available.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
service_idYesA service_id from another tool (darwin:…, tt:… or rtt:…).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo
modeNotrain
originYes
reasonNo
sourceYes
headcodeNo
operatorNo
cancelledNo
service_idYes
destinationYes
calling_pointsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does disclose the key caveat that live times are only provided 'where available' and implies a read-only lookup. However, it does not address failure behavior, data source freshness, or whether historical services are supported; the output schema covers return structure.

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 a single sentence with the core purpose front-loaded and the live-times caveat appended. Every word earns its place, and there is no redundant or filler content.

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 one-parameter read tool with an output schema, the description plus schema is largely sufficient for an agent to call it correctly. The only notable gap is the lack of explicit usage guidance relative to sibling tools, but that is already captured in the usage_guidelines dimension.

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?

Schema description coverage is 100%, and the parameter description already explains the accepted service_id formats. The tool description adds no new parameter-level meaning beyond implying the ID identifies a train service, so the baseline of 3 is appropriate.

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 identifies the resource ('one train') and the content ('all stops'), and the 'live times where available' qualifier distinguishes it from a static timetable. It lacks an explicit verb, but the intent is unambiguous and it is easily differentiated from siblings like live_departures and timetable.

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

Usage Guidelines3/5

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

The phrase 'for one train' implies when to use this tool, but there is no explicit guidance on when to prefer it over alternatives such as timetable or live_departures. No exclusions or alternative tool names are mentioned, leaving the agent to infer the appropriate context.

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