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jimmy_johns_nearby

Find Jimmy John's restaurants near any coordinates. Returns nearby locations sorted by distance, with restaurant IDs for fetching full menus. Specify radius and result limit for precise search.

Instructions

Find Jimmy John's restaurants near a coordinate. Returns Jimmy John's restaurants within a radius of a coordinate, nearest first, using Jimmy John's own Olo-backed ordering API (a separate host from the locator this family's sitemap and store endpoints read). Each result carries restaurant_id -- pass it to GET /jimmy-johns/menu for that restaurant's full menu. The upstream's own radius parameter does not narrow its result set, so distance filtering and sorting happen here.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum restaurants to return, 1-50 (default 10)
radiusNoSearch radius in miles, 1-100 (default 15)
latitudeYesSearch center latitude
longitudeYesSearch center longitude

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, the description carries the behavioral burden and does so well: it discloses the upstream radius quirk, local filtering/sorting, nearest-first order, and the separate Olo-backed host. It does not spell out read-only status or response-shape details, but for a search tool the disclosed behavior is strong.

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?

Three compact sentences with no filler; the purpose is front-loaded and each subsequent sentence adds behavior or chaining information. It is easy to scan and every clause 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 tool with no output schema, the description covers the essential contract: what is returned, the ordering, the radius behavior, and how to consume restaurant_id. It does not enumerate other returned fields or error behavior, which would have made it fully complete.

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%, so the baseline is 3; the description adds real semantic value by explaining that the upstream radius does not narrow results and that distance filtering/sorting happen locally, which changes how an agent should interpret radius and limit. It also clarifies that returned restaurant_id is the key for the menu call.

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 opens with a specific verb and resource ('Find Jimmy John's restaurants near a coordinate') and sharpens it with radius, nearest-first ordering, and a note on the Olo-backed host. It signals how this differs from sibling store/sitemap/menu endpoints, so an agent can pick it 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 Guidelines4/5

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

It gives clear context for when the tool fits: finding nearby restaurants, then chaining to the menu endpoint ('pass it to GET /jimmy-johns/menu'). It distinguishes this API family from the locator's store/sitemap endpoints, though it stops short of explicit 'use this instead of X' exclusions.

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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