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The Dinner Table Club

Get dinner details

get_dinner_details
Read-onlyIdempotent

Get full details for one The Dinner Table Club dinner returned by find_dinners: the event description with the restaurant and menu as listed, plus answers to common questions (coming solo, age, what the ticket includes, dietary needs, bringing a friend, cancellations).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dinner_idYesThe id of a dinner from find_dinners.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dinnerYes
faq_urlYes
descriptionNoEvent description from the listing: the restaurant, menu and how the night runs
good_to_knowYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / properties / dinner / properties / image_url
      Added value: +{
      +  "description": "Photo from a past Dinner Table Club dinner, for display",
      +  "type": [
      +    "string",
      +    "null"
      +  ]
      +}
  2. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds useful scope context about what content the details contain (description, restaurant/menu, FAQ topics), but since an output schema exists, much of this is restated rather than new behavioral disclosure.

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 naming the resource before the details. The parenthetical FAQ list is somewhat dense but each item conveys real scope information, and there is no filler or repetition.

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?

With an output schema present, return-value explanation is unnecessary and annotations cover safety, so the remaining burden is naming the purpose and the id provenance, both of which are handled. Nothing critical is missing, though it could note behavior if the dinner_id is invalid or stale.

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 single dinner_id parameter is fully described in the schema as coming from find_dinners. The description reinforces that provenance but adds no syntax, format, or validation detail beyond the schema, so 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?

States a specific verb (get) and resource (full details for one dinner) and explicitly ties the record to find_dinners, distinguishing it from the list/search sibling. It further enumerates the detail categories returned, so an agent knows this is the drill-down tool rather than the discovery tool.

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 phrase 'returned by find_dinners' clearly establishes the precondition that an id must come from a prior find_dinners call, which is the key usage context. It does not, however, state any exclusion or offer an alternative tool, so it stops short of full when/when-not guidance.

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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