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doordash_feed

Find nearby DoorDash stores by latitude and longitude, returning ID, name, cover image, tags, and reported metrics (rating, price, delivery fee, ETA). No account or token required.

Instructions

Get DoorDash store discovery feed. Returns nearby stores for a location from the Android mobile guest experience: store ID, name, cover image and tags, plus rating, price range, delivery fee and ETA when the upstream feed surface reports them. Those metric fields are omitted rather than estimated when it does not, so treat their absence as "not reported". No DoorDash account or caller-supplied token is required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax stores to return
offsetNoNumber of stores to skip
latitudeYesConsumer latitude
longitudeYesConsumer longitude

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.16.2
    • changedInput schema / properties / offset / description
      Previous value: -"Feed offset"New value: +"Number of stores to skip"
  2. Added

TDQS

A4.2/5.0
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 that metric fields are omitted rather than estimated when the upstream feed doesn't report them, and explicitly states no authentication is required. It could add more about pagination or rate limits, but the key behavioral traits are covered.

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 three sentences, each earning its place: what it returns, how missing fields behave, and the auth requirement. It is front-loaded with the core purpose and avoids redundancy.

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 feed tool with 100% schema coverage and no output schema, the description covers the essential behavior, return fields, and auth requirements. It could mention pagination behavior or rate limits, but nothing critical is missing for an agent to call 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 schema already documents all four parameters. The description adds context that latitude/longitude are consumer coordinates and that limit/offset control pagination, but it doesn't add much beyond what the schema provides. Baseline 3 is appropriate.

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 states a specific verb ('Get'), a specific resource ('DoorDash store discovery feed'), and the key scope ('nearby stores for a location from the Android mobile guest experience'). It also lists the returned fields, which clearly distinguishes it from sibling tools like doordash_search, doordash_explore, and doordash_store.

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 indicates this is for the discovery feed surface and notes it requires only latitude/longitude, with no account or token. It does not explicitly name sibling alternatives or state when not to use it, but the context of 'discovery feed' and 'guest experience' provides clear usage context.

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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