DealerMax

Get NLT offer details

get_nlt_offer_details

Read-onlyIdempotent

Dettaglio completo di una singola offerta NLT (catalogo Noleggio Lungo Termine).

Espone tutto quello che search_nlt_offers ritorna nel hit + extra:
  - description_full (descrizione_ai completa)
  - image_url + gallery (foto multiple veicolo)
  - quotazioni[] (18 combinazioni durata×km/anno)
  - anticipo_scenari_eur (3 importi EUR: zero/medio/standard)
  - tags[] categoria (es. Promo, Stock pronto, GreenChoice)
  - accessori_inclusi[] dell'offerta
  - network_offers[] (tutti i pioneer DealerMAX con loro canone)

Usa dopo search_nlt_offers quando l'utente vuole approfondire una
specifica offerta. Esempio: utente chiede "dimmi tutto sulla BMW X1
sDrive18d 36 mesi" → passa lo slug dell'offerta a questo tool.

Args:
  slug: Slug canonico dell'offerta NLT (es. "business-bmw-x1-sdrive18d").
    Recuperato dal campo `slug` di un hit di search_nlt_offers.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`slug`	Yes	Canonical slug of the NLT offer (e.g. 'business-audi-q3-35-2-0-tdi-business-advanced-s-tronic'). Obtain via the 'slug' field of a search_nlt_offers hit.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.4/5.0

Behavior4/5

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

The annotations already mark this as read-only, idempotent, and non-destructive, so no safety caveat is needed. The description goes beyond annotations by explaining that it exposes the full search hit plus additional data groups such as quotazioni, anticipo_scenari_eur, tags, accessori_inclusi, and network_offers, giving the agent a clear picture of the returned detail.

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 front-loaded with a clear summary, followed by structured bullets and practical usage guidance. It is slightly longer than strictly necessary because the Args section partly duplicates the input schema, but the bullet list and the user-example earn their place.

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 single-parameter, read-only detail tool, this description covers what the tool does, what extra data it returns, when to use it, and where the slug comes from. The workflow relationship with search_nlt_offers and the concrete user-question example leave no practical gap for an agent to invoke it correctly.

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 coverage is 100% and the schema already documents slug as canonical and obtainable from a search_nlt_offers hit. The description repeats this and adds an example slug, but it does not materially extend the parameter meaning beyond the schema, so the baseline 3 applies.

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 opens with 'Dettaglio completo di una singola offerta NLT' and clearly identifies the resource and scope. It explicitly distinguishes the tool from search_nlt_offers by stating it returns the same hit plus extra fields, and the bullet list gives concrete evidence of what that extra detail covers.

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

Usage Guidelines5/5

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

The description says 'Usa dopo search_nlt_offers quando l'utente vuole approfondire una specifica offerta' and provides a concrete user-request example with the slug to pass. This clearly defines the triggering context, the preceding tool, and the expected input flow with nothing left to inference.

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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TDQS

A4.3/5.0

Disambiguation5/5

Each tool maps to a distinct resource and intent: dealer directory, used-car search and detail, NLT search and detail, catalog specs, and market FAQ. The descriptions explicitly cross-reference the other tools and state when not to use them, so misselection is unlikely.

Naming Consistency5/5

All tool names use lowercase snake_case with a clear verb_noun structure: find_* for dealers, search_* for the two inventory searches, and get_* for details and specs. The pattern is predictable and uniform.

Tool Count5/5

Seven tools is well-scoped for a read-only automotive marketplace server: two search/detail pairs for the two offer types, plus dealer lookup, model specs, and market FAQ. No tool feels redundant.

Completeness5/5

The server covers the full discovery lifecycle for its domain: search and drill-down for both used vehicles and NLT offers, dealer lookup, catalog specs independent of inventory, and explanatory FAQ content. Every search entry point has a corresponding detail tool, so there are no dead ends.

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