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find_nearby_restaurants

Returns an MCP App card of restaurants near a point or address. The default radius is a quarter mile.

Input Schema

NameRequiredDescriptionDefault
cityNoOptional city filter.all
limitNoMax restaurants to return (1-100).
addressNoOptional street address; resolved to lat/lng via Google Maps Geocoding API. Used only if latitude/longitude are not supplied.
latitudeNoCenter latitude in decimal degrees. Required if no address is provided.
history_nNoHow many recent inspections to include per restaurant. Default 3.
longitudeNoCenter longitude in decimal degrees. Required if no address is provided.
radius_milesNoSearch radius in miles. Defaults to 0.25 (a quarter mile).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full disclosure burden. It does usefully reveal that the output is an MCP App card rather than raw records, but it omits permissions, geocoding failure behavior, result ordering, and any pagination or rate-limit context.

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 front-loaded sentences, with the purpose stated first and the radius default as secondary supporting detail. Nothing is padded or redundant enough to distract.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a seven-parameter tool with no annotations and no output schema, the description covers the return shape at a high level but says nothing about the location requirement, the inspection history dimension, or the sibling relationship. The rich schema compensates for parameter gaps, but the sibling ambiguity remains unresolved.

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 every one of the seven parameters is already documented, including the lat/lng versus address precedence and the 0.25-mile default. The description only restates the default radius and adds no new meaning.

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 names a concrete verb and resource — returns a card of restaurants near a point or address — and mentions the spatial scoping, so an agent knows what it retrieves. It does not, however, distinguish itself from the sibling search_restaurants, despite the two names being easily confused.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use or when-not-to-use statement, and the most obvious alternative, search_restaurants, is never referenced. The agent must infer from the name alone that this is a proximity search rather than a keyword search.

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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