Skip to main content
Glama
Crawlora-org

Crawlora MCP

Official
by Crawlora-org
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

datasets_doordash_stores_item

Fetch a stored DoorDash store by its numeric store ID from the doordash-stores dataset, returning available address, phone, and pickup status.

Instructions

Get a stored DoorDash store. Returns one stored DoorDash store by its DoorDash store id (digits only, e.g. 297068) from dataset id doordash-stores. A store discovered but not yet hydrated may have an empty address/phone and no location. display_status, asap_available, and pickup_available are a point-in-time pickup observation at crawl time, not a durable capability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
store_idYesDoorDash store id (digits only), e.g. 297068

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.9

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does add real value: it warns that newly discovered stores may have empty `address`/`phone` and no `location`, and that `display_status`, `asap_available`, and `pickup_available` are point-in-time crawl observations rather than durable capabilities. These data-quality caveats are exactly the kind of context an agent needs; only auth/error behavior is unaddressed, which is minor for a read lookup.

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?

Three sentences, each doing work: identity/return, format example, hydration caveat, and observation-vs-capability caveat are front-loaded with no filler. The 'digits only, e.g. 297068' clause duplicates the schema slightly, keeping it just short of a 5.

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 exists, so the description must characterize the return value, and it does so usefully by naming the fields whose absence or volatility an agent could misread. It stops short of describing the overall record shape, but the caveats cover the highest-risk interpretation errors.

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% for the single `store_id` parameter, and the schema already spells out 'digits only, e.g. 297068'. The description restates the same format constraint rather than adding new semantics, so the baseline of 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 and resource ('Get a stored DoorDash store'), names the source dataset ('doordash-stores'), and pins the identifier domain with an example (digits only, e.g. `297068`). An agent can distinguish this single-record lookup from the nearby/search/facets siblings without opening the schema.

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

Usage Guidelines3/5

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

Usage is implied by the retrieval-by-id framing rather than stated: the agent can infer this is the fetch-one-by-id counterpart to the search/nearby siblings, but the description never says when to use this instead of `datasets_doordash_stores_search` or how a store id is obtained. No exclusions or prerequisites are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools