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belgrano9

Renfe MCP Server

by belgrano9

find_station

Search for train stations in a Spanish city and retrieve their IDs and names for Renfe journey planning.

Instructions

Search for train stations in a city and return matching options.

Useful for checking what stations are available in a city before searching for journeys.

Args: city_name: City name to search for (e.g., "Madrid", "Barcelona", "Valencia") api_key: API key for authentication (optional if configured via environment)

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
city_nameYes
api_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description bears full burden. It mentions returns as a formatted string with IDs and names, and that api_key is optional. However, it does not disclose potential side effects, rate limits, or error behavior, which is a gap for a network call tool.

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, front-loading the purpose in the first sentence, followed by a clear use case and structured Args/Returns sections. No redundant information.

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 tool has only 2 parameters and an output schema exists, the description provides all necessary context: what it does, when to use it, parameter explanations, and return format. It is complete for this simple tool.

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?

Schema description coverage is 0%, but the description compensates fully by explaining city_name with examples (e.g., Madrid, Barcelona) and clarifying api_key's optional nature and purpose. This adds significant meaning beyond the bare 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 explicitly states 'Search for train stations in a city and return matching options.' It uses a specific verb (Search) and resource (stations), and clearly distinguishes from sibling tools like get_train_prices and search_trains.

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 gives clear context: 'Useful for checking what stations are available in a city before searching for journeys.' This explains when to use the tool, but does not explicitly state when not to use or mention alternatives beyond the implied sequence.

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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