Vila Buarque

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

A4.8/5.0

Behavior5/5

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

No annotations are present, so the description carries full transparency burden. It discloses accent-insensitive/typo-tolerant matching with concrete examples, explains that open_now is computed server-side for the current moment, details that attributes must ALL match, and describes the delivery array structure and hours format — far beyond a basic 'search' statement.

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 front-loaded with purpose, then logically moves to matching behavior, filter composition, result shape, and amenity slugs. Every sentence adds information; it's appropriately detailed for a search tool with 6 parameters.

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?

The description is complete for the tool's complexity: it covers matching semantics, filter usage, output fields, hours mapping, and amenity slugs. Since there is no output schema, the description's explanation of return fields fills that gap effectively.

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

Parameters5/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds meaningful semantics: q matching behavior, open_now meaning, attributes ALL-match rule, and a list of common amenity slugs, which goes beyond the schema's basic field 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 opens with 'Search for places (restaurants, cafes, shops, etc.) in this neighborhood', which clearly states the tool's action and resource. It distinguishes itself from siblings like search_dishes by targeting generic places rather than specific dishes.

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 provides clear usage context by explaining how to compose filters for multi-condition queries, and lists the available filters and their semantics. It does not explicitly mention when to use this tool over search_dishes or other alternatives, so it lacks explicit exclusion/alternative guidance.

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

A4.2/5.0

Disambiguation5/5

Each tool targets a distinct resource or action: booking services, restaurant reservations, event tickets, and RSVPs are all clearly separated by domain and described with explicit use cases. Similarly, search_places, search_dishes, and get_restaurant_menus cover different granularities of place/menu lookup. The descriptions include guidance on when to use each tool, eliminating ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., list_*, get_*, create_*, search_*). While a few verbs like 'request' and 'rsvp' differ, they accurately reflect the action's semantics and do not break the overall consistency. The naming makes the tool's purpose predictable from its name.

Tool Count4/5

At 28 tools, this is a large set, but it serves a broad multi-domain directory (places, events, movies, store, bookings, content, etc.). Each tool covers a distinct feature or resource, and there are no redundant tools. The count is at the upper boundary but appropriate for the server's comprehensive scope.

Completeness5/5

The tool surface covers the full lifecycle for the directory's main domains: search/discover places, view details, menus, reviews, book services, reserve/RSVP events, browse movies/showtimes, list products, access content (blog, guides, FAQs), submit forms, and check loyalty. There are no obvious dead ends or missing operations for the stated purpose. The inclusion of pairing tools like list_forms→submit_form and get_availability→create_booking shows deliberate workflow completeness.

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