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Crawlora MCP

grubhub_restaurant_menu

Read-only

Grubhub restaurant menu with prices: base, delivery and pickup price per item plus min/max variation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
restaurant_idYesRequired. Grubhub's numeric restaurant id, from /grubhub/search.
include_unavailableNoOptional. Include items the restaurant currently has unavailable. Default false.

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

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safe-read profile is covered. The description adds a modest amount of context about the pricing fields present (base/delivery/pickup and min/max variation), but says nothing about pagination, rate limits, or freshness — and since an output schema exists, this return-content description is largely redundant.

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?

A single front-loaded sentence with zero filler; the key resource leads and the pricing detail follows after the colon. It is dense but every clause carries information, with only minor redundancy against the output schema.

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 low-complexity two-parameter read with full schema coverage, annotations, and an output schema, the description is adequate on purpose and output shape. It is still missing usage context (when to pick it over grubhub_restaurant) and any note that restaurant_id originates from search.

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 both parameters (restaurant_id, include_unavailable) are fully documented in the schema. The description adds no parameter-level meaning beyond that, so the baseline 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 resource (Grubhub restaurant menu) and enumerates the price dimensions returned (base, delivery, pickup, min/max variation), so an agent knows this fetches menu/pricing data rather than reviews or availability. However it does not name a sibling or explain how it differs from grubhub_restaurant or grubhub_availability.

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?

The description contains no when-to-use guidance, no prerequisite (e.g. that restaurant_id must first come from grubhub_search), and no exclusions relative to sibling tools. The only hint about sourcing restaurant_id lives in the schema, not the description.

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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