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Shortlist Pass Local Businesses

Search Shortlist businesses

search_businesses

Find real local businesses on Shortlist Pass (food trucks, restaurants, shops, HOAs and more). Filter by town slug (e.g. "myrtle-beach"), by category key (e.g. "food_truck", "restaurant", "bakery"), and/or by a free-text query matched against the name, headline and type. Returns up to 25 matches with each business's subdomain — pass that subdomain to get_business, get_menu or get_upcoming_events. Demo and test pages are never returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
townNoTown slug, e.g. "myrtle-beach"
queryNoFree text, e.g. "empanadas"
categoryNoBusiness category key, e.g. "food_truck"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose real behavior: a hard cap of 25 matches, the subdomain field in each result, and the guarantee that demo/test pages are never returned. It does not mention auth requirements, rate limits, or pagination behavior beyond the cap.

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 sentences, no filler, with the core purpose front-loaded and filter details and return behavior following in priority order.

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?

There is no output schema, so the description must cover return values, and it does (up to 25 matches, each with a subdomain). Combined with the documented filter semantics, an agent has everything needed to call this tool correctly.

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 schema baseline is 3, but the description adds genuine meaning: it explains that the free-text query is matched against name, headline and type, and gives richer category examples (food_truck, restaurant, bakery) than the schema's single example.

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 and resource (find local businesses on Shortlist Pass) with concrete domain examples (food trucks, restaurants, HOAs). It also distinguishes itself from siblings by explaining that the returned subdomain feeds get_business, get_menu and get_upcoming_events.

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?

Explains the three filter modes and how they combine ('and/or'), and routes the agent to the sibling tools that consume the result. It lacks an explicit when-not-to-use or an alternative search tool, but the context is otherwise clear.

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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