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Glama

Tabellone Arrivi

tabellone_arrivi

Get real-time arrival board for an Italian train station by station code, including origin, scheduled time, delay, platform, and arrival status.

Instructions

Restituisce il tabellone degli arrivi in tempo reale per una stazione ferroviaria (es. 'S01700' per Milano Centrale). Fornisce: treni in arrivo, stazione di provenienza, orario programmato, ritardo in minuti, binario programmato ed effettivo, e se il treno è già giunto in stazione.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
data_oraNo
codice_stazioneYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the real-time nature of the data and enumerates the fields returned, but says nothing about read-only semantics, auth needs, rate limits, or failure behavior for invalid station codes. The field enumeration largely duplicates what the output schema already provides.

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?

A single front-loaded sentence plus a compact field list; the purpose and scope land immediately with no filler. Slightly over-specified on return fields that the output schema already covers.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so the return-value enumeration is not strictly needed, and the description never addresses the undocumented data_ora parameter. It is adequate for calling the tool with a station code but leaves a real gap for the second parameter and for how to obtain valid codes.

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?

Schema description coverage is 0%, so the description must compensate. It does document the required codice_stazione format via the 'S01700' example, which the schema lacks, but the optional data_ora parameter is never mentioned, leaving half the parameters undocumented.

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 ('Restituisce il tabellone degli arrivi in tempo reale per una stazione ferroviaria') and anchors it with a concrete station-code example ('S01700' per Milano Centrale). The arrivals-vs-departures distinction is unambiguous against the sibling tabellone_partenze.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The real-time framing implies the usage context, but there is no explicit when-to-use guidance, no mention of the natural alternative (tabellone_partenze), and no stated prerequisites such as needing a valid station code from cerca_stazione or autocompleta_stazione. Usage is inferable from the name only.

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