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Glama

Itinerario Treno Canvas

itinerario_treno_canvas

Returns a visual tree of a train's route, showing stop by stop whether departure or arrival has occurred and if the train is currently stopped at a station.

Instructions

Restituisce la rappresentazione visuale ad albero (tratteCanvas) dell'itinerario del treno, indicando fermata per fermata se la partenza o l'arrivo sono già avvenuti e se il treno è fermo in stazione.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numero_trenoYes
data_partenzaYes
codice_stazione_origineYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It does disclose behavioral content beyond a bare name - stop-by-stop flags for whether departure/arrival occurred and whether the train is currently stopped - but omits permissions, rate limits, and how the data is scoped or refreshed.

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 with no wasted phrasing; the purpose leads and the output detail follows. Efficient, though it could be marginally tighter.

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

Completeness2/5

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

An output schema exists, so return-value explanation is unnecessary, but the description leaves critical gaps: with 0% parameter coverage, no annotations, and amiguous integer fields, it does not supply enough for an agent to call a 3-required-param tool correctly.

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

Parameters2/5

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

Schema description coverage is 0% across 3 required parameters, so the description must compensate; it does not. It never clarifies the format of data_partenza (integer - epoch? YYYYMMDD?), the meaning of codice_stazione_origine, or how numero_treno should be supplied.

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?

States a specific verb (returns) and resource (the visual tree representation tratteCanvas of the train itinerary), which distinguishes it from a plain status lookup. It is clear what the tool produces, though it does not explicitly name or contrast with siblings like stato_treno.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no prerequisites, and no mention of alternatives such as stato_treno or cerca_numero_treno for overlapping needs. The agent must infer the use case entirely from the purpose statement.

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