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Station Board: Departures

station_board_departures
Read-onlyIdempotent

Get live departures for ANY railway station by its EVA number.

Covers all train categories including local/regional (S/RB/RE) and long distance, with real-time delays, cancellations and disruption messages. Get the EVA from get_city_resource(slug, resource='stations'). Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
evaYesStation EVA number (digits only) from get_city_resource(slug, resource='stations'), e.g. '8011160' (Berlin Hbf).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
metaYes

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. Description adds context about real-time delays, cancellations, and disruption messages, and states 'Read-only', which is consistent. It provides extra behavioral context beyond what annotations convey.

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?

Three sentences with no wasted words. First sentence states purpose, second adds coverage details, third provides parameter sourcing. Information is front-loaded and every sentence earns its place.

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?

Given the single parameter with high schema coverage, an output schema (present), and rich annotations, the description is fully sufficient. It covers the tool's purpose, data scope, and parameter retrieval without gaps.

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%, so baseline is 3. The description reiterates how to get the EVA number from get_city_resource, which the schema already includes. No new parameter semantics are added beyond the schema.

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?

Description clearly states 'Get live departures for ANY railway station by its EVA number', specifying a specific verb and resource. It distinguishes from sibling 'station_board_arrivals' by focusing on departures, and covers train categories and real-time data, leaving no ambiguity.

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?

Description explains when to use (get live departures) and how to obtain the required parameter from another tool. However, it does not explicitly differentiate from siblings like 'transit_departures' or state when not to use this tool, leaving room for confusion about 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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TDQS

A4.1/5.0
Disambiguation3/5

Most tools have distinct purposes, but there is potential confusion between 'get_city_resource' and specific resource accessors like 'weather', 'air_quality', 'transit_departures', 'station_board_arrivals', and 'station_board_departures'. The descriptions do clarify that some specific tools exist for convenience or source-specific details, but the boundary isn't always sharp. Also, 'compare' could overlap with using 'get_city_resource' repeatedly. An agent might hesitate between using the generic resource accessor and the named tool.

Naming Consistency4/5

The naming convention is mostly consistent: verbs like 'get', 'list', 'compare', and 'pois' (abbreviation) are used. The pattern is generally 'verb_noun' (e.g., 'get_city', 'list_cities', 'station_board_arrivals'). Minor deviations include 'pois' being an acronym rather than a full verb phrase, and 'air_quality' vs 'weather' implying a noun rather than an action. But overall it's predictable and readable.

Tool Count5/5

12 tools is a well-scoped count for a city data platform. The function set covers discovery (list_cities, sources), overview (get_city_overview), base data (get_city), specific data types (weather, air_quality, transit_departures, station_board_*, pois), a generic accessor (get_city_resource), and a comparison tool (compare). Each tool feels necessary and the set is not overwhelming.

Completeness4/5

The tool surface is quite comprehensive for a read-only city information server. It provides discovery (list_cities, get_city_overview), base data, and access to 81 data types via get_city_resource. The named tools cover the most common queries (weather, air quality, transit). A minor gap is the lack of a tool to aggregate or search across cities (though 'compare' helps). Editing or write operations are not expected here, but for read-only, it's nearly complete.