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Glama

Vila Madalena

by io.github.junoventures

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
NameRequiredDescriptionDefault
qNoFree-text term matched against place name and address — accent-insensitive and typo-tolerant.
limitNoMax results to return (default 20, max 100).
categoryNoFilter by category label (e.g. "Café"). Case-insensitive substring match.
open_nowNoWhen true, return only places open at the current local time (computed server-side from their opening hours).
attributesNoAmenity 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.
neighborhoodNoFilter by neighborhood name. Case-insensitive substring match.

TDQS

A4.3/5.0
Behavior4/5

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

No annotations provided, so the description carries full burden. It discloses accent-insensitive and typo-tolerant matching, ranking by relevance, and output details like precomputed 'open_now', 'attributes', and 'delivery' arrays. Missing mention of pagination or auth, but sufficient.

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 adequately sized, front-loaded with purpose, and every sentence provides useful information. It is well-structured but could be slightly more concise without losing detail.

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?

Given no output schema and no annotations, the description covers input behavior, filter usage, and output fields (including examples of amenity slugs). It does not cover error handling or defaults, but is fairly 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?

All 6 parameters have schema descriptions (100% coverage), but the description adds value beyond schema: it explains how 'q' matching works, that 'attributes' requires ALL matches, and that 'open_now' checks current local time.

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 specifies the action 'Search for places' and the resource (places like restaurants, cafes, shops). It distinguishes from sibling tools like 'get_place' (specific 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 Guidelines4/5

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

The description explains when to use this tool (for searching with free-text and filters) and provides details on composing filters. It does not explicitly state when not to use or compare to siblings, but the context is 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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TDQS

A4/5.0
Disambiguation5/5

Each tool targets a distinct resource or action: search, get, list, create, submit, etc. Potential overlaps like create_booking vs request_reservation vs reserve_event_tickets are clarified by descriptions distinguishing appointment booking, restaurant table requests, and event ticket holds.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with underscores (e.g., list_services, get_place, create_booking). No mixing of styles, and verbs accurately describe the operation.

Tool Count4/5

28 tools is slightly above typical range but well-justified given the breadth of the site (places, events, movies, food, booking, forms, etc.). Each tool serves a clear purpose without feeling bloated.

Completeness4/5

Covers major read and action scenarios for a neighborhood directory. Missing update/delete operations for places and bookings, but those are likely not exposed via this API. Minor gaps like canceling reservations are handled externally.

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