get_restaurant
Return full schema.org Restaurant page (E2-A /get slice). restaurant_id and entity_id are aliases; pass either.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | No | ||
| restaurant_id | No |
Return full schema.org Restaurant page (E2-A /get slice). restaurant_id and entity_id are aliases; pass either.
| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | No | ||
| restaurant_id | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds that it returns a 'full' page and explains the alias behavior, but does not disclose other behavioral details like error handling or response format. This is minimal additional value.
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 two short, front-loaded sentences. The first states the purpose, the second gives essential parameter guidance. 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?
For a simple get-by-ID tool with good annotations and no output schema, the description adequately indicates the return type ('full schema.org Restaurant page') and the alias mechanism. It is sufficient for an agent to select and invoke, though it could mention not-found behavior.
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 description coverage is 0%, so the description must compensate. It clarifies that restaurant_id and entity_id are aliases and that either can be passed, which resolves ambiguity not evident from the schema alone. However, it does not elaborate on each parameter's meaning further.
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 returns a full schema.org Restaurant page, which is a specific verb and resource. It does not explicitly distinguish this from sibling tools like get_entity or get_details, so it misses the top score.
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?
No guidance is provided on when to use this tool compared to alternatives such as get_entity or get_details. The only usage note is about parameter aliases, which is not a usage guideline.
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.
There is notable overlap among search, search_web, search_restaurants, and search_salons, as well as between filter_restaurants/filter_salons and search with constraints. However, descriptions clarify the intended vertical or corpus, and entity getters are distinct. The overlap is manageable but could cause misselection.
Names mostly follow a get_/list_/search_/register_/delete_/submit_/vote_ pattern in snake_case. Minor deviations like 'recall', 'remember', 'research', and 'travel_health' are less predictable but still readable. Overall consistent and clear.
38 tools is on the heavy side for a single MCP server, exceeding the typical well-scoped range. While the server covers multiple subdomains (search, travel disruptions, memory, feedback, research), the sheer number may overwhelm agents and suggests potential consolidation.
The tool surface covers core workflows: search and entity retrieval for restaurants/salons, disruption monitoring with standing queries and webhooks (register/list/delete), research submission/polling, and memory/feedback mechanisms. Minor gaps exist (e.g., no cancel for research jobs, no explicit entity list endpoint), but these are workable and do not break typical agent tasks.