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Crawlora MCP

papajohns_menu_item

Read-only

Papa John's US/Canada menu item: one SKU with this store's price plus its product group's full customization axes -- every size, crust and preparation instruction it can be ordered with.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skuYesRequired. A product sku from GET /papajohns/menu.
store_idNoOptional. A store id from GET /papajohns/store or GET /papajohns/nearby, so the price is that restaurant's. Omit for the national default price.

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

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description usefully adds that the price is store-specific and that the response carries the product group's full customization axes (sizes, crusts, preparation instructions), which is real context beyond the annotations. It says nothing about auth, rate limits, or behavior when a SKU is unknown, so it is not rich.

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?

A single front-loaded sentence that carries the scope, price behavior, and return depth with no filler. It is somewhat jargon-heavy ('customization axes', 'preparation instruction'), which costs a little readability, but nothing is wasted.

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?

An output schema exists, so the description need not explain return values, and it nonetheless signals what the payload emphasizes. Combined with the fully covered two-parameter schema and read-only annotations, an agent has enough to call this correctly; only explicit sibling routing is missing.

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 both parameters are already documented, establishing a baseline of 3. The description reinforces that store_id changes which restaurant's price is returned and that sku selects one item, but adds no syntax, format, or fallback detail beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb (retrieving) and resource (one Papa John's US/Canada menu SKU), and clarifies that it returns a single item with price and full customization axes. That scope ("one SKU") implicitly distinguishes it from a menu-listing sibling like papajohns_menu, but it never names an alternative, so it stops short of the clearest sibling differentiation.

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 only implied: an agent can infer this is the detail call for a specific item once it has a SKU. There is no explicit when-to-use vs when-not, and no routing language such as 'use papajohns_menu to list items first.' The schema's reference to GET /papajohns/menu supplies some routing context, but the description itself does not.

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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