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?
With no annotations, the description fully explains the returned data (opening hours, open_now, attributes, delivery, ratings, address, neighborhood). It covers the behavioral output well, though error handling is not discussed.
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, well-structured sentence that front-loads the purpose and efficiently lists the returned fields without waste.
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?
For a simple tool with one parameter and no output schema, the description covers the return content comprehensively. Minor gaps like error handling or case-sensitivity do not significantly impact completeness.
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 only parameter 'slug' is well-described in the schema with an example. The description adds little beyond 'by its URL slug', but schema coverage is 100%, 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 the verb 'Get full details' and the resource 'place', and specifies the identifier 'URL slug'. It distinguishes from sibling tools like search_places and other entity-specific get tools.
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?
Usage is implied: use when needing full details of a specific place by slug. However, no explicit when-not-to-use or alternatives are mentioned, though sibling tools provide context.
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 domain (e.g., booking, restaurant reservation, event RSVP, movie showtimes) with clear descriptions that prevent confusion. Overlapping verbs like 'create' are used for different resource types, and the descriptions explicitly distinguish their contexts.
All 28 tools follow a strict verb_noun pattern with underscores, e.g., create_booking, get_availability, list_events. No mixing of conventions or inconsistent verb styles.
28 tools is at the upper end of reasonable for a broad neighborhood directory server covering places, bookings, events, movies, store, forms, and more. While each tool serves a distinct purpose, the count feels slightly high for a single server.
The tool surface covers core discovery and booking initiation (search, detail, book, reserve), but lacks lifecycle operations like cancel, update, or list user's existing bookings. Several operations require external checkout or confirmation links, creating workflow gaps.