Get the full profile of a restaurant by URL slug. Returns name, address, coordinates, rating, reviews count, phone, opening hours, photos, services, cuisine type, price level, current Flow offers, and cultural context.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Restaurant URL slug. Example: 'anima-e-cuore-osteria-bilbao'. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description lists returned fields but does not disclose behavioral traits like authentication requirements, rate limits, or side effects. It is a read operation but not explicitly marked.
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?
Two sentences, no wasted words. Front-loaded with verb and resource, then enumerates returned data efficiently.
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 is fairly complete. It lists return fields but could mention error conditions or edge cases.
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%; the description does not add extra meaning beyond what the schema already provides for the 'slug' parameter. 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 'Get the full profile of a restaurant by URL slug' and lists the specific data returned. It distinguishes from siblings like get_restaurant_reviews (only reviews) and get_flow_offers (only offers).
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?
It implies use when full restaurant details are needed, but does not explicitly state when not to use it or mention alternatives. Sibling tools exist for specific subsets (e.g., reviews, offers).
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 distinct purpose: reservation booking, landmark-based search, cultural context, flow offers, restaurant details, reviews, and general search. No overlapping functionalities.
All tools follow a consistent verb_noun pattern (e.g., book_flow_reservation, get_restaurant_details), making it easy to infer actions.
Seven tools cover the core domain (search, details, reviews, offers, booking, cultural context) without being excessive or insufficient.
Core workflows are covered, but the set lacks reservation cancellation or update functionality, which is a minor gap for a booking system.
