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foodpanda_restaurant

Look up a foodpanda restaurant by code to get its name, address, coordinates, rating, cuisines, delivery fees, and pickup availability.

Instructions

Get one foodpanda restaurant's detail. Returns one foodpanda restaurant's detail by code: name, address, coordinates, budget tier, rating and review count, cuisines, minimum order amount, minimum delivery fee, delivery/pickup availability, timezone, and a hero image. Supplying latitude and longitude only affects the (optional) computed fields the upstream itself returns for that coordinate; it does not filter or reject the lookup.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "code": "<code>"
    },
    "name": "foodpanda_restaurant"
  }
}

Input Schema

Name	Required	Description
`code`	Yes	Restaurant code, from /foodpanda/search's code field
`market`	No	Delivery Hero market the restaurant belongs to. Defaults to sg.
`latitude`	No	Caller latitude, optional
`longitude`	No	Caller longitude, optional

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv1.17.5Sep 26, 2026

addedInput schema / properties / market / enum

Added value: +[
+  "sg",
+  "pk",
+  "bd",
+  "hk",
+  "my",
+  "ph",
+  "la",
+  "kh",
+  "tw",
+  "mm"
+]

Addedv1.16.2Sep 10, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses a non-obvious behavioral nuance: latitude/longitude only influence optional computed fields and do not filter or reject the lookup. This goes beyond the schema and helps prevent misuse. It does not mention error handling or auth, but these are not critical for a simple read operation.

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 tightly packed sentences with zero filler. The first sentence states purpose and output fields efficiently; the second handles an important edge-case with precision. Information is front-loaded and every clause earns its place.

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?

No output schema, so the description is the primary source of return-value information. It lists the key fields (name, address, coordinates, budget tier, rating, cuisines, etc.) and explains optional coordinate behavior. It does not describe the exact JSON structure or error semantics, but for a single-entity lookup this is adequate. Minor gap: could mention what happens when a code is invalid.

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 real value by explaining the effect of latitude/longitude, which is not inferable from the schema alone. It also implicitly links 'code' to foodpanda_search's output, reinforcing the relationship. This elevates the score above baseline.

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?

Starts with a specific verb ('Get') and a well-defined resource ('one foodpanda restaurant's detail'), then enumerates the exact fields returned. The phrase 'by code' distinguishes it from list-oriented search tools like foodpanda_search, making its scope unambiguous.

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 description clearly implies it is the tool to call when you have a restaurant code, and the schema references foodpanda_search for obtaining that code. It does not explicitly state when not to use it or name sibling tools for menu/reviews, but the lookup-by-primary-key nature is evident and sufficient for most agents.

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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