Bela Vista

search_places

Search for places (restaurants, cafes, shops, etc.) in this neighborhood. The q match is accent-insensitive and typo-tolerant ("acai" finds "Açaí", "restaurnt" finds "Restaurante"), ranked by relevance. Compose filters for multi-condition queries: category, neighborhood, open_now (true = open at this exact moment), and attributes (amenity slugs, ALL must match). Each result includes a precomputed open_now boolean, an attributes array (amenity slugs), a delivery array of curated delivery-app deep-links (ifood, rappi, 99food, uber-eats — each { platform, url }), rating, and structured hours (Google Maps periods: day 0=Sun–6=Sat, time "HHMM"). Common amenity slugs: wifi, outdoor-seating, wheelchair, dog-friendly, delivery, takeaway, reservations, live-music, vegan, gluten-free (availability varies per place).

Input Schema

TableJSON Schema

Name	Required	Description
`q`	No	Free-text term matched against place name and address — accent-insensitive and typo-tolerant.
`limit`	No	Max results to return (default 20, max 100).
`category`	No	Filter by category label (e.g. "Café"). Case-insensitive substring match.
`open_now`	No	When true, return only places open at the current local time (computed server-side from their opening hours).
`attributes`	No	Amenity slugs a place must ALL have, e.g. ["wifi","outdoor-seating"]. Common slugs: wifi, outdoor-seating, wheelchair, dog-friendly, delivery, takeaway, reservations, live-music, vegan, gluten-free.
`neighborhood`	No	Filter by neighborhood name. Case-insensitive substring match.

TDQS

A4.4/5.0

Behavior5/5

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

No annotations provided, so description carries full burden. It discloses accent-insensitive and typo-tolerant matching, relevance ranking, precomputed open_now, delivery links, hours format, and common amenity slugs. Thorough disclosure.

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?

Single paragraph of 5 sentences, front-loaded with purpose. Efficient but could benefit from bullet points for readability. Generally concise and well-structured.

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?

Despite no output schema, the description explains return fields (open_now boolean, attributes array, delivery array, rating, hours). Covers all 6 parameters and common amenity slugs. Complete for a search tool.

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 has 100% description coverage, but the description adds meaning beyond schema: 'accent-insensitive and typo-tolerant' for q, 'ALL must match' for attributes, 'open at this exact moment' for open_now, and result structure details. Exceeds baseline 3.

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 states 'Search for places' with specific examples (restaurants, cafes, shops) and context 'in this neighborhood'. It clearly distinguishes from siblings like get_place (single place) and search_dishes (dishes only).

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?

The description explains how to compose filters but does not explicitly state when to use this tool versus alternatives like get_place or search_dishes. Usage is implied but lacks direct comparison or 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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TDQS

A4/5.0

Disambiguation5/5

All 28 tools have clearly distinct purposes. Overlaps like create_booking vs request_reservation are well-delineated by descriptions: one for appointments with checkout URL, the other for table requests via email confirmation. Similarly, reserve_event_tickets vs rsvp_event, and get_restaurant_menus vs search_dishes are complementary.

Naming Consistency5/5

Tool names follow a consistent verb_noun pattern in snake_case (e.g., create_booking, get_availability, list_events, search_places). Verbs indicate action type (get/list for retrieval, create/reserve for creation), and nouns are specific entities. No mixing of conventions.

Tool Count4/5

28 tools is above the typical 3-15 range but appropriate for the broad scope of a neighborhood directory with multiple Wix integrations (Bookings, Events, Stores, Reviews, etc.). Each tool covers a distinct feature, and no tool feels redundant.

Completeness4/5

The tool surface covers the main user workflows: searching places, viewing details and menus, checking availability, making bookings/reservations, and managing event tickets. Minor gaps exist (e.g., no update/cancel for bookings, no booking status check), but these are acceptable as the server focuses on initiating actions.

Resources

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