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Search Dim Hour

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Search Dim Hour's curated restaurant, bar and venue catalog across all 20 cities. Returns ranked venues with a dimhour.com link for each. Use for questions about where to eat or drink — by cuisine, dish, neighborhood, city, vibe, or award.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesWhat to look for, e.g. 'best ramen in NYC', 'michelin dallas', 'rooftop bar miami'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYes

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: it returns 'ranked venues with a dimhour.com link for each' and clarifies the catalog is curated across all 20 cities. This goes beyond just repeating annotations.

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?

Two sentences, front-loaded with the main purpose in the first sentence, and the second sentence gives usage guidance. No wasted words; every sentence contributes.

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 simple search tool with one parameter and an output schema, the description is complete: what it searches (curated catalog, 20 cities), what it returns (ranked venues with links), and when to use it (food/drink questions by various facets). No major gaps.

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% – the 'query' parameter has a description with examples. The tool description itself adds nothing about the parameter beyond what the schema already provides, so the baseline of 3 is appropriate.

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?

The description states a specific verb ('Search') and resource ('Dim Hour's curated restaurant, bar and venue catalog'), and adds scope details ('across all 20 cities'). It clearly differentiates itself from the broad sibling 'search_venues' by emphasizing 'curated' catalog and providing a dimhour.com link, but it does not explicitly name alternatives or contrast with siblings like 'search_venues'.

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 gives clear usage context: 'Use for questions about where to eat or drink — by cuisine, dish, neighborhood, city, vibe, or award.' This is explicit and helpful, but it does not mention when not to use the tool or point to alternatives, so it stops short of a 5.

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

A4/5.0
Disambiguation2/5

There are two pairs of nearly identical tools: `fetch` and `get_venue` both retrieve full venue records by ID, differing only in an optional long-form story; `search` and `search_venues` both perform catalog searches with overlapping scope and filtering. This creates real ambiguity about which tool to select for a given task.

Naming Consistency3/5

Naming mixes single verbs (`fetch`, `search`) with verb_noun snake_case (`get_venue`, `list_cities`, `search_venues`). The pattern is not uniform, and synonyms like fetch/get and search/search_venues further muddy the naming convention.

Tool Count5/5

Seven tools is a reasonable number for a venue discovery server. Even accounting for redundancy, the count is well within the typical range and each tool ostensibly serves a distinct operation (search, retrieve, list).

Completeness4/5

The tool surface covers the core workflows: discovering venues (search, search_venues), retrieving details (fetch, get_venue), and listing collections (list_cities, list_curated, list_new_venues). No major lifecycle operations are missing, though the redundant pairs suggest the design could have been more streamlined.

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