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Find Paris and Île-de-France stations or stops by name and return their IDs with serving lines so you can select the correct stop for departure lookups.

Instructions

Find Paris / Île-de-France stations and stops by name and return their IDs.

Use this first when the user names a station (e.g. "Gentilly", "Châtelet",
"Gare de Lyon") and you need its ID for next_departures. Returns up to 5 matches
with the lines serving each one, so you can pick the right station.

Args:
    query: Station or stop name, in French or English spelling. e.g. "Gentilly".

Input Schema

NameRequiredDescriptionDefault
queryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds useful behavior beyond that — a capped result set of 'up to 5 matches with the lines serving each one' — but says nothing about behavior when zero matches are found or how ambiguous partial names are resolved, which is the main risk for a name-search tool.

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 intent and timing are front-loaded in the first two sentences, which is the right ordering. The trailing 'Args:' block partly repeats the station examples already given in the body ('Gentilly' appears twice), which is mild waste for a one-parameter tool.

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 single-parameter tool with no output schema, the definition covers what it does, when to call it, and roughly what comes back (up to 5 matches plus their lines). The notable omission is the no-match / ambiguity case, though the small surface area limits how much damage that causes.

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% — the schema only says 'Query: string' — so the description carries the burden and does add real meaning: the value is a station or stop name, accepted in French or English spelling, with worked examples ('Gentilly', 'Châtelet', 'Gare de Lyon'). It does not address partial matches or accents, but the core semantics are supplied.

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 specific verb and resource ('Find Paris / Île-de-France stations and stops by name and return their IDs') and scopes it geographically. It also ties itself to a sibling by naming next_departures as the consumer of the returned IDs, so an agent can separate it from the other tools without opening a schema.

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?

'Use this first when the user names a station... and you need its ID for next_departures' gives clear triggering context and a downstream dependency. It stops short of explicit exclusions — nothing says when to skip this in favor of plan_journey or traffic_disruptions, which matters since those siblings also take station input.

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