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belgrano9

SNCF MCP Server

by belgrano9

find_station

Search for train stations by name to get matching options with IDs and full names. Use it to confirm station names before planning a journey or when the exact name is uncertain.

Instructions

Search for a train station by name and return matching options.

Useful for checking station names before searching for journeys, or when you're not sure of the exact station name.

Args: station_name: Station name to search for (e.g., "Paris", "Munich", "Lyon")

Returns: A formatted string showing matching stations with their IDs and full names.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
station_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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 states that it returns matching options as 'a formatted string showing matching stations with their IDs and full names,' and notes it's useful for checking station names. This provides a decent picture of the operation and output, though it doesn't explicitly mention non-destructive behavior or edge cases like no results.

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 concise and well-structured, with the main purpose stated in the first sentence, followed by usage context and a structured 'Args' and 'Returns' section. Every sentence adds value with no repetition or fluff.

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 tool with one parameter and an output schema, the description covers purpose, usage context, parameter semantics, and return format. It provides enough information for an agent to select and invoke the tool correctly without confusion, making it complete for its complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema only provides the parameter name and type, with 0% description coverage. The description compensates fully by including an 'Args' section that explains station_name with concrete examples ('Paris', 'Munich', 'Lyon'), making the parameter's meaning and expected format clear.

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 the tool's function: 'Search for a train station by name and return matching options.' This uses a specific verb and resource, and it distinguishes itself from sibling tools like search_trains (which searches journeys) and get_train_prices (which gets prices).

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 explicitly says it is 'Useful for checking station names before searching for journeys, or when you're not sure of the exact station name,' which gives clear context for when to use it. It doesn't explicitly name alternatives, but the context implies it should be used before journey searches, which is clear enough.

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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