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by net.crawlora
OverviewDiscussionsAdmin

ubereats_feed

Read-only

Fetch Uber Eats restaurant records delivering to a specified location, with rating, delivery estimate, and cuisine tags. Use ubereats_search when you want keyword search rather than the location feed.

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": {
      "latitude": "<latitude>",
      "longitude": "<longitude>"
    },
    "name": "ubereats_feed"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoNumber of restaurants to return, clamped to 50. Default 20.
offsetNoResult offset for the location feed. Default 0.
latitudeYesDelivery search center latitude (required).
longitudeYesDelivery search center longitude (required).

Output 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

A4.2/5.0
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 safety profile is covered. The description adds value by naming the record contents (rating, delivery estimate, cuisine tags), but that overlaps with the existing output schema and says nothing extra about pagination, result clamping, or auth. With annotations doing the heavy lifting, a 3 is appropriate.

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 sentences, zero filler, and the primary purpose is front-loaded ahead of the sibling routing clause. Every sentence 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?

For a read-only location feed with an output schema and fully documented parameters, the description covers purpose, routing, and return content. Minor gaps remain: no mention of pagination behavior or how 'clamped to 50' affects paging, but nothing an agent strictly needs to call it correctly is missing.

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%, with latitude/longitude marked required and limit/offset carrying defaults and the clamp-to-50 note in the schema itself. The description adds no parameter 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.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Fetch'), the resource ('Uber Eats restaurant records'), and the scoping condition ('delivering to a specified location'), then names the schema fields returned. It explicitly distinguishes itself from ubereats_search, so an agent can route without opening either schema.

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

Usage Guidelines5/5

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

The second sentence gives an explicit alternative and the condition that selects it: keyword search goes to ubereats_search, whereas this tool serves the location-based feed. This is the when/when-not pattern that leaves nothing to inference.

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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