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panera_catering_delivery_info

Get a Panera cafe's catering delivery fees, minimum orders, hours, and lead-time tiers for various order sizes. Includes upcoming delivery dates and order windows.

Instructions

Get one Panera Bread cafe's catering delivery fee, minimum order, hours and lead times. Returns one cafe's catering delivery fee, minimum order amount, weekly delivery hours, order-size lead-time tiers (e.g. a $750+ order needs a longer lead time than a smaller one), and upcoming available delivery dates with their order windows. This is Panera's catering delivery flow specifically -- catering pickup happens at the cafe itself, whose hours are already covered by GET /panera/cafe. Returns 404 if the cafe does not offer catering delivery.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cafe_idYesPanera cafe id, from /panera/locations

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.16.2

TDQS

A4.6/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the exact return categories, confirms the query targets one cafe, excludes pickup behavior, and states the 404 condition. The read-only nature is clear from 'Get' and the tool name.

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?

The description is well-structured: summary, expanded return list, scope clarification, and error condition. There is mild redundancy between the first and second sentences, both listing delivery fee, minimum order, hours, and lead times, but it remains readable and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description fully documents the return values, including lead-time tiers and order windows, and explains the 404 condition. The single parameter is already explained by the schema, and the tool is clearly differentiated from nearby Panera siblings, so an agent has enough to invoke it correctly.

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 coverage is 100%, and the single parameter cafe_id is already described as a Panera cafe id from /panera/locations. The description only reinforces 'one cafe' without adding new parameter semantics, so the baseline score of 3 is appropriate.

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 opening sentence uses a specific verb and resource: Get one Panera Bread cafe's catering delivery fee, minimum order, hours and lead times. It clearly distinguishes this from pickup-oriented tools by stating that catering pickup is covered by GET /panera/cafe, which separates it from sibling panera_* tools.

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 scopes the tool to Panera's catering delivery flow specifically and identifies the alternative for pickup hours via GET /panera/cafe. It also tells the agent when to expect a 404, so it knows when a cafe is not eligible for catering delivery.

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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