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kintscher

swiss-rail-mcp

by kintscher

get_disruptions

Check currently active disruptions on the Swiss rail network, filtered by location or line, to anticipate travel delays.

Instructions

Return currently active rail-traffic disruptions on the Swiss network.

Use this tool when the user asks "are there any disruptions today?", "is the line to X working?", or wants context on whether to expect delays on a route. Source: SBB rail-traffic-information feed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of events to return (1-50). Defaults to 10.
scopeNoOptional free-text fragment (station, line, or place name) used to filter the feed (e.g. "Bern", "Gotthard", "S6"). Matches ``title`` or ``description``. If omitted, all active events are returned.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It conveys that results are 'currently active' and cites the SBB feed, providing some context. Yet it omits details like response format (though output schema exists), potential latency, or any limitations beyond 'active' status. It is adequate but not rich.

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 extremely concise—two well-structured sentences that front-load the purpose, provide usage triggers, and mention the source. Every sentence adds value, and there is no filler.

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?

For a simple two-optional-parameter tool with an output schema, the description is complete. It clarifies the temporal scope ('currently active'), geographic scope ('Swiss network'), and provides practical example queries. It paints a full enough picture for an agent to select and invoke the tool correctly.

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 input schema has 100% coverage for both parameters (limit and scope) with detailed descriptions. The tool description itself does not add any extra parameter semantics or examples, 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.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear action with a specific resource: 'Return currently active rail-traffic disruptions on the Swiss network.' It mentions the scope ('Swiss network') and distinguishes itself from sibling tools focused on stations, connections, and stationboards.

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?

The description provides explicit use-case examples ('are there any disruptions today?', 'is the line to X working?'), giving clear context for when to invoke the tool. However, it does not explicitly mention alternatives or when not to use it, so it falls short of a full 5.

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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