Interlagos

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

A4.1/5.0

Behavior4/5

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

With no annotations, the description carries full burden. It discloses typo-tolerance, accent-insensitivity, ranking by relevance, filter behavior, precomputed open_now, attributes array, delivery deep-links, and structured hours. No mention of rate limits or authentication, but the level of detail is high.

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 moderately long but well-structured with a clear initial purpose, followed by details on behavior, filters, and output. No superfluous sentences, though the list of amenity slugs could be slightly trimmed.

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 6 parameters (0 required) and no output schema, the description covers filter semantics, output fields, and common amenity slugs, providing sufficient context for the agent to use it 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 baseline is 3. The description adds value by explaining output fields (open_now, attributes, delivery, hours) and filter composition, which goes beyond the schema parameter descriptions.

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 clearly states the tool searches for places (restaurants, cafes, shops) in a neighborhood, using a specific verb ('Search') and resource. It 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 implies usage for searching places with various filters but does not explicitly guide when to use this tool versus alternatives like 'get_place' or 'search_dishes'. No when-not-to-use or exclusion criteria are given.

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

A3.9/5.0

Disambiguation5/5

Every tool targets a distinct Wix resource or action: bookings, events, store, forms, places, menus, etc. The four booking-related tools are clearly separated by domain (appointments, restaurant tables, paid events, free events), with descriptions that eliminate ambiguity.

Naming Consistency4/5

The set follows a consistent verb_noun snake_case pattern (create_, get_, list_, search_, submit_). Minor deviations exist: get_reviews and get_event_tickets return collections (could be list_), and rsvp_event uses an abbreviation, but these do not affect clarity.

Tool Count4/5

At 26 tools, the set is larger than the typical 3–15 well-scoped range, but the server covers a broad umbrella of Wix integrations for a neighborhood directory. Each tool maps to a distinct function, so the count is justified by the scope, though it is on the heavier side.

Completeness4/5

The surface covers discovery and transactional workflows: searching places/dishes, viewing menus/reviews/guides/offers, booking appointments and tables, reserving event tickets, purchasing products, submitting forms, and reading site info. Minor gaps exist (no cancel/update operations), but these are handled via external checkout links and are acceptable for a directory.

Resources

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