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JavaScript
Remote

panera_upsell_suggestions

Fetch a Panera Bread cafe's per-item upsell suggestions, returning Panera's suggested add-ons for each menu item using a cafe id from /panera/locations.

Instructions

Get one Panera Bread cafe's per-item upsell suggestions. Returns Panera's own suggested add-ons per menu item (for example "Extra Turkey" and "Extra Bacon" for a Bacon Turkey Bravo sandwich). Item ids on this surface are in a separate id space from /panera/menu's item_id, but both the item and its suggestions carry their own resolved names, so no cross-reference is needed. Cafe ids come from GET /panera/locations.

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

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It explicitly states what is returned (Panera's suggested add-ons) and that both item and suggestions carry resolved names, which is behavioral info. It doesn't state that it's read-only or mention failure modes, but the 'Get' verb implies a safe read operation. The description adds value beyond the schema and is not misleading.

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 three sentences, each purposeful: purpose, example, and identity clarification with parameter source. It is front-loaded and avoids any fluff or redundancy. Every sentence earns its place.

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?

For a simple one-parameter tool with no output schema, the description is largely complete. It explains the purpose, gives a concrete example, clarifies the id space, and tells where to get the parameter. It doesn't detail return structure (e.g., list of suggestions per item) but the example implies it. The missing output format is a minor gap, but overall it's sufficient for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (only cafe_id). The description adds meaning by specifying the source of cafe_id ('Cafe ids come from GET /panera/locations'), going beyond the schema's type description. This helps the agent know exactly how to obtain a valid parameter value.

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 uses a specific verb ('Get') and resource ('one Panera Bread cafe's per-item upsell suggestions') with an example ('Extra Turkey' and 'Extra Bacon'). It clearly distinguishes from sibling tools like panera_menu by stating it returns upsell suggestions, not the menu itself, and clarifies the separate id space.

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

Usage Guidelines4/5

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

The description provides context on where to get the cafe_id (GET /panera/locations) and explains the id space difference from /panera/menu, which prevents misuse. While it doesn't explicitly state when not to use this tool or name alternatives, the id space clarification effectively guides the agent away from cross-referencing. Lacks an explicit exclusion clause but is still useful.

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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