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Glama

Autocompleta Stazione

autocompleta_stazione

Find Italian railway station codes by entering a name prefix. Returns the full station name and code, such as S01700 for Milano Centrale, for use in departure boards and train details.

Instructions

Suggerisce stazioni ferroviarie per prefisso del nome (es. 'firenze', 'milano'). Restituisce nome esteso e codice stazione (es. S01700 per Milano Centrale). È l'endpoint consigliato per ottenere i codici stazione da usare nei tabelloni e nei dettagli.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prefissoYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral burden. It describes the basic suggestion behavior and the returned fields, but omits operational traits such as case sensitivity, matching limits, rate limits, or authentication needs. Output schema exists, so return value details are not a credit here.

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 three front-loaded sentences that each serve a purpose: function/examples, return example, and recommended use. It is appropriately sized and free of filler, though the example detail is slightly more than strictly necessary.

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?

Given the simple one-parameter autocomplete tool and the existence of an output schema, the description covers purpose, parameter meaning, and recommended usage adequately. It could add behavioral details like matching semantics, but no critical element for invocation is missing.

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%, so the description must explain the single parameter. It does so clearly by stating 'prefisso del nome' and providing concrete examples ('firenze', 'milano'), adding meaning beyond the bare schema type.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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

The description states a specific verb ('Suggerisce') and resource ('stazioni ferroviarie') along with the matching condition ('per prefisso del nome'). It clearly tells the agent what the tool does, but does not differentiate it from siblings like cerca_stazione or autocompleta_stazione_nts.

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?

It explicitly positions itself as the recommended endpoint ('È l'endpoint consigliato') for obtaining station codes to be used in boards and details. This gives clear context for when to use it, though no explicit when-not or alternatives are named.

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