Yenta Directory

Venue dietary options by name

venue_dietary_options

Read-onlyIdempotent

List a named venue's declared dietary tags and allergens — the exact spellings venue_menu_search matches literally (the venue's own host calls this get_dietary_options).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`city`	No	Disambiguate a name by city (call list_cities); ignored for a slug.
`venue`	Yes	Venue name or slug; call search_venues to discover one.

Output Schema

TableJSON Schema

Name	Required	Description
`item`	No
`items`	No
`reason`	No
`sample`	No
`source`	No	FR-13: which approved revision an answer was read from, and how fresh. ``source`` is ``approved-content-revision:<id>`` for every read that answers from one venue, and the literal ``directory`` for the two cross-venue reads, which have no single revision to cite.
`status`	Yes
`pagination`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 23, 2026

addedOutput schema / properties / sample

Added value: +{
+  "anyOf": [
+    {
+      "type": "boolean"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Sample"
+}

First observedSep 10, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds behavioral value beyond that by revealing that results are 'declared' tags and 'exact spellings,' meaning the output is a literal vocabulary rather than normalized or computed values. This is genuinely useful for downstream usage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the core action first, then packs in the key semantic constraint about exact spellings and the host-side alias. Every clause contributes value; there is no padding or wasted wording.

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?

The tool is well covered across all dimensions: schema covers all parameters, annotations cover side-effect behavior, output schema exists, and the description clarifies the important literal-matching relationship with venue_menu_search. An agent has everything needed to select and 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 description coverage is 100%, so the schema already documents both parameters, including city disambiguation and venue-as-slug behavior. The description adds only the 'named venue' framing and does not need to repeat schema details. Baseline 3 is appropriate when the schema carries the parameter documentation burden.

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 a specific verb and resource: 'List a named venue's declared dietary tags and allergens.' This clearly distinguishes the tool from siblings like venue_profile or get_venue by focusing on dietary vocabulary. It also adds a useful cross-reference to venue_menu_search, so an agent knows exactly what this tool produces.

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 description communicates when to use the tool: to obtain the exact spellings that venue_menu_search matches literally. That is a clear use case, though it does not explicitly say 'use this instead of X' or list exclusion criteria. Still, the context is strong enough for an agent to route correctly.

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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