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ubereats_feed

Retrieve restaurants delivering to any location from UberEats, including ratings, delivery estimates, cuisine tags, and cover images, using just latitude and longitude.

Instructions

Browse UberEats location feed. Returns restaurants delivering to a specific location: name, rating, review count, delivery estimate, cuisine tags, and cover image. Credential-free public UberEats data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of restaurants to return, clamped to 50. Default 20
offsetNoResult offset for the location feed. Default 0
latitudeYesDelivery search center latitude
longitudeYesDelivery search center longitude
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 the credential-free nature and specifies the returned fields, giving a clear behavioral picture. It does not detail pagination behavior or rate limits, but the schema already documents limit/offset clamping, so the description adds meaningful context beyond the structured data.

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?

The description is two sentences, front-loaded with the primary action, and every phrase adds value. It avoids redundancy with the schema and includes essential context (credential-free, returned fields) without verbosity.

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 feed-browsing tool with no output schema or annotations, the description covers purpose, return fields, and auth status. It could ideally mention potential limitations such as geographic coverage or result ordering, but the existing detail is sufficient for an agent to select and invoke it correctly.

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 baseline is 3. The description adds minimal parameter semantics beyond the schema: it mentions 'specific location' aligning with latitude/longitude, but the schema already explains 'Delivery search center latitude/longitude.' No new meaning is added for limit/offset.

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?

The description clearly states the tool's function: 'Browse UberEats location feed' and enumerates the returned data fields (name, rating, review count, delivery estimate, cuisine tags, cover image). This distinguishes it from sibling tools like ubereats_search and ubereats_store by focusing on the feed concept.

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 implies usage context: a location feed requiring latitude/longitude to find delivering restaurants. It also notes 'Credential-free public UberEats data,' clarifying that no authentication is needed. However, it does not explicitly name alternatives or state when not to use this tool, so it falls 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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