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datasets_doordash_stores_nearby

Find nearby stored DoorDash stores within a radius, sorted nearest first, using latitude, longitude, and radius in meters.

Instructions

Find nearby stored DoorDash stores. Returns stored DoorDash stores within a radius of a point, nearest first, from dataset id doordash-stores. lat, lon, and radius_m are required. Unlike the live /doordash/search endpoint (which is a proximity search capped at roughly five stores), this queries the stored directory, so it can return every discovered store in the radius. Coverage is best-effort rather than provably exhaustive: a store DoorDash never surfaced, or one not yet hydrated with coordinates, will not appear.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesCenter latitude, from -90 through 90
lonYesCenter longitude, from -180 through 180
tagNoSingle marketplace tag filter
pageNoOffset page number, defaults to 1; ignored by cursor pagination except page=1 to start
cursorNoOpaque continuation token returned in next_cursor; use with pagination=cursor and the same location and filters
countryNoISO-3166-1 alpha-2 country filter
radius_mYesSearch radius in meters, 1 through 50000
page_sizeNoPage size, defaults to 20 and maxes at 100; the 10,000-result cap applies only to offset pagination
paginationNoPagination mode: offset or cursor. Cursor mode supports full enumeration beyond the offset result window.
dash_pass_onlyNoKeep only DashPass-eligible stores

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.9

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose meaningful behavior: nearest-first ordering and, importantly, that coverage is best-effort (un-surfaced or un-hydrated stores are absent). It omits pagination/limit behavior and any auth or rate-limit context, which the schema partly covers.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action, then progressively adds scope, required inputs, and caveats. Four sentences with no padding, though 'stored DoorDash stores' is repeated and the comparison sentence is slightly long.

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 10-parameter, no-annotation, no-output-schema tool, the description supplies the key semantics (ordering, best-effort coverage, contrast to the live endpoint). What's missing — pagination strategy and result-window limits — is largely handled by the schema, so the definition is close to complete.

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 every parameter (lat, lon, radius_m, tag, page, cursor, country, page_size, pagination, dash_pass_only) is already documented in the schema. The description only restates that lat/lon/radius_m are required, adding no semantics beyond structured data. Baseline 3 is correct.

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 ('Find nearby stored DoorDash stores'), the scoping (within a radius of a point, nearest first) and the backing dataset id. It explicitly distinguishes itself from the live /doordash/search endpoint, so an agent can tell the two apart 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 Guidelines4/5

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

Names the alternative (live /doordash/search, capped at ~5 stores) and the condition that favors this tool (full stored-directory enumeration in the radius). Clear routing context, though it never states an explicit 'do not use this when...' case or prerequisites.

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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