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JavaScript
Remote

pizzahut_menu

Fetch a Pizza Hut location's entire menu with categories, product/bundle types, variants, and USD prices; include store number and order channel for location- and channel-specific pricing.

Instructions

Get one Pizza Hut restaurant's full priced menu. Returns one restaurant's full menu grouped into categories (e.g. "Pizza", "Wings", "Deals"). Every entry is a product, a bundle (a deal or combo), or a standalone priced variant -- type tells callers which -- and carries a price in USD cents plus a decimal dollar value, and an image when the upstream publishes one. A product item also lists variants: every other priced size/crust/style option beyond its default (e.g. a pizza's Personal Pan through Large Original Stuffed Crust). Prices reflect this specific restaurant and order channel, not a national default. channel selects which order channel the menu is priced for (web ordering by default); prices can genuinely differ by channel (e.g. a delivery-marketplace channel vs. web). Some restaurants also carry products with no category at all (e.g. individual dip cup flavors); these are returned separately as uncategorized_items rather than silently dropped.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channelNoOrder channel the menu is priced for (default WEB)
store_numberYesPizza Hut's store number, from /pizzahut/stores

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / channel / enum
      Added value: +[
+  "WEB",
+  "MOBILE",
+  "POS",
+  "KIOSK",
+  "DOORDASH",
+  "UBEREATS",
+  "GRUBHUB",
+  "IOS",
+  "ANDROID",
+  "DELIVEROO",
+  "JUST_EAT",
+  "CALL_CENTER"
+]
  2. Addedv1.16.2

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and delivers: it discloses the category grouping, entry types (product/bundle/standalone variant), price representation (USD cents + decimal dollars), variant lists, channel-dependent pricing, and the uncategorized_items edge case. This gives an agent a precise model of the response without an output 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?

Every sentence contributes a distinct fact about scope, structure, pricing, or edge cases; the main purpose is front-loaded in the first sentence. No filler or repetition.

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?

The description is self-sufficient for a tool with no output schema: it explains the response shape, entry taxonomy, price fields, variant behavior, and the uncategorized-items fallback. The only missing piece is error handling, which is not essential for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds value beyond the schema by explaining that channel changes pricing and giving a concrete example (delivery-marketplace vs. web), which helps an agent decide whether to vary the channel parameter.

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?

States a specific verb and resource ('Get one Pizza Hut restaurant's full priced menu') and distinguishes itself from sibling tools like pizzahut_store and pizzahut_delivery_estimate by focusing on the menu payload. The grouping and entry-type details further clarify exactly what is returned.

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 first sentence establishes the core use case (retrieving a full menu for a specific restaurant), and the channel discussion clarifies when the channel parameter matters. It does not explicitly name alternatives or state when not to use this tool, 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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