Dim Hour

Get venue details

get_venue

Read-only

Get the full Dim Hour record for one venue: description, signature dishes, address, hours, phone, happy hour, reservation platform, awards, website, Instagram, and (for Iconic 50 venues) the long-form story.

Input Schema

TableJSON Schema

Name	Required	Description
`id`	No	Venue id from search_venues
`city`	Yes	City name or key
`name`	No	Venue name (used if id not given)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes
`lat`	No
`lng`	No
`url`	Yes
`name`	Yes
`tags`	Yes
`hours`	Yes
`phone`	Yes
`price`	No
`score`	No
`story`	No
`awards`	Yes
`dishes`	Yes
`iconic`	No
`opened`	No
`address`	Yes
`cuisine`	Yes
`website`	Yes
`photoUrl`	Yes
`trending`	No
`city_name`	Yes
`instagram`	Yes
`happy_hour`	Yes
`highlights`	No
`price_tier`	No
`description`	Yes
`reservation`	Yes
`neighborhood`	Yes
`other_locations`	No

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed1 schema field changedAug 12, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "address": {
+      "type": "string"
+    },
+    "awards": {
+      "type": "string"
+    },
+    "city_name": {
+      "type": "string"
+    },
+    "cuisine": {
+      "type": "string"
+    },
+    "description": {
+      "type": "string"
+    },
+    "dishes": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "happy_hour": {
+      "type": "string"
+    },
+    "highlights": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "hours": {
+      "type": "string"
+    },
+    "iconic": {
+      "type": "boolean"
+    },
+    "id": {
+      "type": "number"
+    },
+    "instagram": {
+      "type": "string"
+    },
+    "lat": {
+      "type": "number"
+    },
+    "lng": {
+      "type": "number"
+    },
+    "name": {
+      "type": "string"
+    },
+    "neighborhood": {
+      "type": "string"
+    },
+    "opened": {
+      "type": "string"
+    },
+    "other_locations": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "phone": {
+      "type": "string"
+    },
+    "photoUrl": {
+      "type": "string"
+    },
+    "price": {
+      "type": "string"
+    },
+    "price_tier": {
+      "type": "number"
+    },
+    "reservation": {
+      "type": "string"
+    },
+    "score": {
+      "type": "number"
+    },
+    "story": {
+      "type": "string"
+    },
+    "tags": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "trending": {
+      "type": "boolean"
+    },
+    "url": {
+      "type": "string"
+    },
+    "website": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "id",
+    "name",
+    "cuisine",
+    "neighborhood",
+    "tags",
+    "description",
+    "dishes",
+    "happy_hour",
+    "address",
+    "hours",
+    "phone",
+    "reservation",
+    "awards",
+    "website",
+    "instagram",
+    "url",
+    "city_name",
+    "photoUrl"
+  ],
+  "type": "object"
+}

First observedAug 5, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already mark it as read-only and non-destructive. The description adds useful conditional detail (long-form story only for Iconic 50 venues) and clarifies the record's composition, providing value beyond the structured annotations.

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 a single sentence that front-loads the main purpose and then lists fields in a dense, readable manner. It is slightly long but every word adds value, with no filler.

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 a read-only annotation, full schema coverage, and an output schema, this description is sufficiently complete for a single-record retrieval tool. It does not elaborate on error handling or sibling differentiation beyond implied usage, but those gaps are minor given existing structured metadata.

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?

All three parameters are fully described in the schema (100% coverage), and the tool description does not add extra meaning beyond labeling the record as 'full.' The schema already explains id/name/city roles, so the description contributes minimal additional parameter context.

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 clearly states the tool fetches the full Dim Hour record for a single venue and enumerates the included fields (description, signature dishes, address, hours, etc.). This specific verb+resource pairing distinguishes it from sibling tools like search_venues or fetch.

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 implies use for retrieving detailed records after a search, and the input schema explicitly notes the id comes from search_venues. However, it does not state when not to use it or mention alternatives for list/lightweight data, leaving room for more explicit guidance.

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

All Dim Hour tools Inspect

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TDQS

A3.8/5.0

Disambiguation2/5

fetch and get_venue both describe retrieving the full record for a venue, differing only in an extra long-form story for Iconic 50 venues, making their boundaries unclear. Similarly, search and search_venues both search the same catalog with overlapping descriptions, leaving an agent unsure which to call.

Naming Consistency3/5

The list_* tools are consistently verb_noun, but search and search_venues repeat the same action with different names, and fetch breaks the otherwise intuitive get_* pattern. The naming is readable but not systematic.

Tool Count3/5

Seven tools is a reasonable count for a venue-discovery server, but redundancy between fetch/get_venue and search/search_venues inflates the set and makes it feel less tight than the domain requires.

Completeness4/5

The surface covers searching, retrieving details, browsing curated lists, and listing new venues across cities, so core discovery workflows are supported. Minor gaps exist around filtering/sharing list results, but agents can generally complete end-to-end tasks.

Resources

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