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malkreide

SBB Open Data MCP Server

by malkreide

sbb_get_rolling_stock

Read-onlyIdempotent

Retrieve technical data for SBB rolling stock, including seat capacity, build year, length, and weight. Filter by vehicle type like IC 2000 or FV-Dosto.

Instructions

Ruft technische Daten zum SBB-Rollmaterial (Züge, Triebzüge, Wagen) ab.

Enthält Fahrzeugtyp, Sitzplatzkapazität (1./2. Kl.), Baujahr, Länge und Gewicht.

Args: params (RollingStockInput): Parameter: - vehicle_type (Optional[str]): Fahrzeugtyp, z.B. 'IC 2000', 'TGV', 'FV-Dosto' - limit (int): Max. Resultate - offset (int): Paginierung - response_format (str): 'markdown' oder 'json'

Returns: str: Rollmaterial-Daten mit Kapazität, Baujahr und technischen Kennzahlen. Schema: {vehicle_type, built_year, seats_1st, seats_2nd, total_seats, length_mm, weight_t}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds meaningful context such as the return format and fields, though it does not detail pagination behavior beyond the parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with separate sections for purpose, arguments, and returns. It is front-loaded with the German purpose and avoids unnecessary verbosity, though it could be slightly more concise.

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?

The description, combined with annotations and the output schema reference, fully covers the tool's behavior, parameters, and return types. It is complete for a simple query tool with pagination.

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 description coverage is 0%, but the description lists each parameter with its purpose and examples, compensating well. It adds details like default values and enum options 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?

The description clearly states it retrieves technical data about SBB rolling stock, listing specific attributes (vehicle type, seat capacity, etc.). It distinguishes from sibling tools by focusing solely on rolling stock, not stations or infrastructure.

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 description does not explicitly state when to use this tool versus alternatives. While siblings are clearly different, there is no guidance on when not to use it or prerequisites, leaving usage context implied.

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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