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 are provided, so the description carries full burden. It thoroughly describes the return payload (opening hours, open_now, attributes, delivery links, ratings, address, neighborhood), implying read-only behavior. It does not mention permissions or rate limits, but for a GET operation this is acceptable. No contradictions with annotations.
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 front-loads the core purpose ('Get full details...') and then lists key return fields. While it is somewhat long, every clause adds value; there is no redundancy or fluff. Properly structured for quick parsing.
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 the tool's simplicity (1 parameter, no output schema), the description is fully adequate. It covers the return structure in detail, enabling an agent to understand exactly what data will be retrieved. No additional context is necessary for correct invocation.
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 input schema has 100% coverage with a clear description of the 'slug' parameter and an example. The description reinforces that the slug is a URL slug, adding no new meaning beyond the schema. Baseline 3 is appropriate as schema already does the work.
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 action ('Get full details') and the resource ('a specific place') with an explicit input ('by its URL slug'). It lists comprehensive return fields, distinguishing it from sibling tools like search_places (which returns a list) and get_reviews (which returns reviews 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 a single place's full details are needed. It does not explicitly mention when not to use it or alternatives, but the sibling tools (e.g., search_places, get_reviews) provide clear context for differentiation. The context is clear enough for an agent to decide.
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 has a clearly distinct purpose, even among similar actions like booking, reservation, and ticket purchase—their descriptions clarify the domain and flow. No two tools could reasonably be confused.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., create_booking, get_availability, list_blog_posts). There are no deviations or mixed conventions.
At 28 tools, the surface is larger than ideal for a single server, but each tool covers a distinct feature of the neighborhood directory (bookings, events, store, etc.). It borders on heavy but is still manageable for an agent.
The tool set covers the full lifecycle of browsing and acting on a neighborhood directory: search, details, reviews, menus, events, booking, reservations, store, loyalty, and more. No obvious gaps exist for the intended use case.