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NYCfoodie

top_rated

Read-only

List the highest-rated restaurants (Infatuation 0–10 scale), with optional cuisine, neighbourhood and price filters. Use for 'best in the city' requests. Differs from search_restaurants: no free-text query, strictly rating-ordered.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoLatitude for proximity search. Must be given together with lng; radius_km defaults to 5 km when omitted. A location outside the NYC coverage area is rejected with an error.
lngNoLongitude for proximity search. Must be given together with lat; radius_km defaults to 5 km when omitted.
cityYesCity slug, always required. Currently 'new-york', covering the five boroughs plus the immediate metro (within 30 km of Manhattan).
limitNoMax results (default 10)
cuisineNoe.g. 'Italian', 'ramen'
occasionNoOccasion tag. Allowed: 'Date Nights', 'Happy Hours', 'Pre-Theater', 'See & Be Seen', 'Serious Takeout Operation', 'Unique Dining Experiences', 'Wasting Your Time & Money'. Hyphens and spaces are flexible ('date-night' works).
radius_kmNoSearch radius in kilometres (default 5 when lat/lng are given without it). Requires lat and lng.
min_ratingNoMinimum Infatuation rating
price_tierNo1 ($) to 4 ($$$$)
neighborhoodNoe.g. 'West Village', or a borough like 'Brooklyn'
include_closedNoInclude known-closed venues (default false)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

The annotations already declare readOnlyHint=true, so the description does not need to restate safety. It adds useful behavioral context beyond the schema: the Infatuation rating scale, strict rating ordering, and the implicit no-free-text constraint. This is more than a bare read, but it does not disclose pagination or error conditions (though those are partly in schema).

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?

Three sentences, front-loaded with the core action and scale, then a clear usage directive, then a differentiation note. No wasted words; every sentence earns its 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?

Given the tool has 11 parameters but a fully descriptive schema, and annotations cover read-only behavior, the description provides the essential extra context (scale and ordering). Nothing needed for correct invocation is missing—the lack of an output schema is acceptable for a list tool.

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 every parameter in detail. The description mentions 'cuisine, neighbourhood and price filters' but adds little beyond the schema; the scale reference ties to min_rating, but overall it does not compensate beyond the baseline for high coverage.

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 states a specific verb ('List'), a clear resource ('highest-rated restaurants'), and the rating scale (Infatuation 0–10). It also explicitly distinguishes itself from the sibling search_restaurants by noting the absence of free-text query and strict rating order, so an agent can immediately tell it apart.

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 gives an explicit use case ('Use for "best in the city" requests') and names the key alternative (search_restaurants) along with the differentiating condition. This tells the agent when to choose this tool over its closest sibling without ambiguity.

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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