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Crawlora MCP

fiveguys_search

Read-only

Five Guys restaurants matching a free-text location query (city, zip, address, or landmark) via Yext's Answers API -- the same query understanding restaurants.fiveguys.com's own search box uses. Each result carries a geomodifier area label, address, phone, weekly in-store hours plus a separate delivery-hours schedule when published, price tier, amenities, pickup/delivery services, order/delivery/menu URLs, a Google Place id, and distance from the resolved location.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoOptional. Maximum restaurants to return, 1-50, default 10.
queryYesRequired. Free-text location: a city, a zip/postal code, a street address, or a landmark. Yext's own query understanding geocodes this server-side, the same way restaurants.fiveguys.com's own search box works.
offsetNoOptional. Result offset for paging through total_results, default 0.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds that Yext's query understanding geocodes the query server-side and returns distance from the resolved location, which is genuinely useful behavioral context, but it stops short of noting rate limits, error behavior, or empty-result handling.

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 first sentence front-loads purpose and input types efficiently. The second sentence is a long enumeration of return fields that largely duplicates the output schema, which dilutes conciseness, though it is not confusing.

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?

An output schema exists, so return values need not be explained, yet the description enumerates them anyway. Combined with clear purpose and annotations covering safety, an agent has enough to call the tool correctly; only the sibling differentiation and paging guidance are thin.

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 query, limit, and offset. The description restates the query semantics (city, zip, address, landmark) without adding format or syntax detail beyond what the schema provides, so the baseline of 3 applies.

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?

States a specific verb and resource ('Five Guys restaurants matching a free-text location query') with the accepted input types (city, zip, address, landmark). It is clear and self-contained, but never distinguishes itself from close siblings like fiveguys_nearby, fiveguys_directory, or fiveguys_store.

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

Usage Guidelines3/5

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

The phrase 'matching a free-text location query' implies when the tool applies, but there is no explicit when-to-use guidance and no alternative tool is named. The agent must infer that this is for location-based lookups rather than menu or FAQ queries.

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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