get_hours
Return opening hours for a restaurant. restaurant_id and entity_id are aliases; pass either.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | No | ||
| restaurant_id | No |
Return opening hours for a restaurant. 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, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that restaurant_id and entity_id are aliases, which is a behavioral trait beyond the schema. However, it does not mention edge cases like conflicting IDs or invalid inputs. With annotations covering safety, a 3 is appropriate.
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 concise sentences with no wasted words. The purpose is front-loaded, and the alias information is efficiently stated in the second sentence.
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?
The tool is simple with no output schema, and the description adequately covers the core purpose and parameter relationship. However, it omits details about return format, error behavior, or what happens if neither parameter is supplied. For a low-complexity read tool, this is nearly complete but leaves minor gaps.
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?
With 0% schema description coverage, the description must compensate. The alias note ('restaurant_id and entity_id are aliases; pass either') provides essential meaning beyond the schema's bare property definitions. It clarifies the relationship between the two parameters, but could also detail parameter constraints or expected formats.
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 'Return opening hours for a restaurant', which includes a specific verb and resource. Though it does not explicitly mention alternatives, the resource is distinct from sibling tools like get_restaurant or check_availability. The alias note adds clarity about parameter use but does not further differentiate the tool's purpose.
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 retrieving opening hours but provides no explicit guidance on when to use this tool versus alternatives. No exclusions or alternative tool suggestions are given. The alias note is parameter-oriented rather than usage-oriented.
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.