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Crawlora MCP

pizzahut_delivery_estimate

Read-only

Check Pizza Hut delivery serviceability and estimated fee for one store and address.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesRequired. Delivery address city.
stateYesRequired. Delivery address state, two-letter code.
address1YesRequired. Delivery address line 1.
address2NoOptional. Delivery address line 2.
latitudeYesRequired. Delivery address latitude.
longitudeYesRequired. Delivery address longitude.
pickup_atNoOptional. RFC3339 pickup time. Default 30 minutes from now.
postal_codeYesRequired. Delivery address postal code.
country_codeNoOptional. Delivery address country code. Default US.
store_numberYesRequired. Pizza Hut's store number, from /pizzahut/stores.
order_subtotalYesRequired. Order subtotal before fees, in dollars.
delivery_providerNoOptional. One of DOORDASH, MOCK_DOORDASH, INTERNAL. Default INTERNAL.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds the single-store/single-address scope, but does not mention that store_number must come from a prior stores lookup or that lat/long are required, which would be useful behavioral context.

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?

A single sentence with zero waste, and the core action is front-loaded. Nothing to trim.

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?

With an output schema present, return values need not be explained, and the schema covers all parameters. The only gap is the lack of guidance on prerequisite flows (obtaining store_number from /pizzahut/stores), which is minor.

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 all 12 parameters are already documented in the schema, making 3 the baseline. The description's 'one store and address' phrasing adds scope framing but no syntax or format detail beyond the schema.

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 ('Check') plus the resource ('Pizza Hut delivery serviceability and estimated fee') and the scope ('one store and address'). An agent can distinguish this from sibling tools like pizzahut_stores or pizzahut_menu 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?

The description implies the pre-order delivery-feasibility use case but gives no explicit when-to-use guidance, prerequisites, or named alternatives (e.g., store lookup before calling). Usage is inferable but not stated.

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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