Get full details for a specific place by its URL slug, including opening hours, a precomputed open_now boolean, amenity attributes (slugs), a delivery array of curated delivery-app deep-links (ifood, rappi, uber-eats — each { platform, url }), ratings, address, and neighborhood.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | URL slug of the place, e.g. "cafe-example". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description correctly identifies a read operation and lists returned data. It does not mention permissions or edge cases, but for a simple read, the behavior is transparent enough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence listing many fields, which is efficient but slightly dense. It could be split for readability, but no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description thoroughly enumerates the response contents (opening hours, open_now, attributes, delivery links, ratings, address, neighborhood). This provides sufficient context for the agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'slug' is well-described in the schema (100% coverage). The description reiterates 'by its URL slug' without adding new semantics, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves full details for a specific place by its URL slug, listing included fields. This distinguishes it from sibling tools like search_places (searching) and get_restaurant_menus (menus only).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have a slug and need comprehensive place data. It does not explicitly exclude alternatives, but the context of siblings makes it clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource and action. Even similar operations like create_booking, request_reservation, reserve_event_tickets, and rsvp_event are clearly differentiated by their descriptions and the entities they handle (bookable services, restaurant tables, paid events, free events). No two tools appear to do the same thing.
All tool names follow a consistent verb_noun pattern with lowercase and underscores (e.g., create_booking, get_availability, list_events, search_places). This uniform convention makes the tool set predictable and easy for an agent to understand and select from.
With 28 tools, the set is relatively large, exceeding the typical well-scoped range of 3-15. While each tool serves a specific purpose within the neighborhood directory domain, the count feels heavy and may overwhelm simple use cases. A reduction or grouping could improve coherence.
The tool set covers a broad range of user-facing operations for a neighborhood directory: searching places, browsing menus, booking services, reserving tables and event tickets, listing products and events, retrieving reviews and FAQs, and submitting forms. Minor gaps exist (e.g., no cancellation or create_review tool), but the core workflows are well-supported.
