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Crawlora MCP

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taco_bell_store

Get a Taco Bell restaurant's full weekly hours and dayparts from its store number, including address, phone, delivery, and ordering status. Dayparts show when breakfast items are available.

Instructions

Get one Taco Bell restaurant's full record, including the whole week's hours and dayparts. Returns one Taco Bell US restaurant by store number: address and coordinates, phone, open status, timezone, delivery and online-ordering state, Taco Bell's per-store capability flags, mobile-pickup status and geofencing radius. Where GET /taco-bell/stores gives only today's window for each nearby restaurant, this returns the full published week, Monday-first, and each day's dayparts. Dayparts matter for ordering: Taco Bell's menu availability is daypart-scoped, so breakfast items and Balance Of Day items are orderable in different windows of the same day. Store numbers come from GET /taco-bell/stores.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
store_numberYesTaco Bell store number, from /taco-bell/stores

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.16.2

TDQS

A4.4/5.0
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 of behavioral disclosure. It enumerates the returned fields (address, coordinates, phone, open status, timezone, delivery state, capability flags, mobile-pickup, geofencing radius) and explains the daypart concept that affects menu availability. It does not explicitly state the operation is read-only, but that is strongly implied by a single-store lookup; it also does not mention error handling or rate limits, but these are minor for this simple tool.

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 well-structured and front-loaded: it states the primary purpose first, then lists the returned fields, then contrasts with the sibling, explains the significance of dayparts, and finally tells where to get the store number. Each sentence adds value, and there is no redundant or filler content.

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?

Given that there is no output schema and the tool returns a rich record, the description thoroughly lists the categories of data returned and explains the daypart behavior that impacts ordering. It does not mention the exact return format (e.g., JSON) or error behavior, but these are generally assumed for such endpoints, and the description is otherwise complete for a single-store lookup.

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?

The input schema has 100% coverage with a single parameter store_number described as 'Taco Bell store number, from /taco-bell/stores.' The description repeats this source reference but adds no new meaning about format or constraints beyond what the schema already provides. According to the rubric, baseline is 3 when schema coverage is high and the description does not add extra semantics.

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 that the tool retrieves a single Taco Bell restaurant's full record, including weekly hours and dayparts. It specifies the resource (one US restaurant) and the verb (get), and it explicitly contrasts with the sibling taco_bell_stores tool, which only provides today's window for nearby restaurants. This distinguishes it from siblings without needing to open schemas.

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 description explicitly names the alternative taco_bell_stores and states the condition for using this tool: when the full published week and dayparts are needed rather than just today's window. It also provides guidance on obtaining the store_number from GET /taco-bell/stores, giving clear when-to-use and where-to-get-input instructions.

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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