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 adequately discloses return fields (including precomputed open_now and delivery deep-links) and implies a safe read operation. It does not discuss error handling, permissions, or rate limits, but the information provided is sufficient for basic understanding.
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 that efficiently conveys purpose and key fields. It front-loads the primary action and resource, but the dense list of fields could be more readable if restructured.
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?
Given a single required parameter and no output schema, the description comprehensively covers the expected response fields. It does not mention edge cases or error conditions, but these are minor omissions for a simple read tool.
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?
Schema coverage is 100% with a clear description of the 'slug' parameter. The tool description adds only the phrase 'by its URL slug', which aligns with but does not substantially extend the schema. Baseline score of 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 tool retrieves full details for a specific place by URL slug, listing specific fields (opening hours, open_now, attributes, delivery links, ratings, address, neighborhood). This distinguishes it from sibling tools like search_places that search rather than fetch a specific resource.
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 for getting a known place by slug but does not explicitly mention when to use this tool versus alternatives (e.g., search_places for querying). No exclusions or prerequisites are provided.
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 action on a specific resource (e.g., create_booking vs create_checkout vs reserve_event_tickets). Descriptions clearly differentiate purposes, and no two tools overlap in functionality.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., get_availability, list_categories, search_dishes). Verbs like get, list, create, request, rsvp are used uniformly, making the set predictable.
28 tools is above the typical 3-15 range, but the server covers a broad domain (places, events, movies, booking, store, etc.). Each tool serves a clear purpose, so the count is justified for the scope.
The tool surface is extensive, covering searching, details, reviews, booking, events, menus, etc. Minor gaps exist (e.g., no cancel/update operations), but they are likely intentional given the user-facing nature of the server.
