Get the food menu for a specific restaurant on this site. Returns menus with their sections, dishes, descriptions, prices, and dietary labels (vegan, gluten-free, etc). Use search_places or list_categories first to find the restaurant's place_slug.
| Name | Required | Description | Default |
|---|---|---|---|
| place_slug | Yes | The slug of the restaurant, e.g. "bar-do-ze" (from search_places or a place URL). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains the return value (menus with sections, dishes, descriptions, prices, dietary labels) but does not mention error handling or edge cases. Still, for a simple read tool, it sufficiently discloses the main behavior.
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 concise with two sentences, front-loading the purpose and return, then providing prerequisite information. No unnecessary words or redundancy.
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 simplicity of the tool (one required parameter, no output schema), the description covers the essential aspects: purpose, return content, and prerequisite steps. It is complete for the tool's complexity.
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 schema already describes the place_slug with an example. The description adds value by instructing how to obtain the slug via other tools, which is helpful context beyond the schema.
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 gets the food menu for a specific restaurant, specifying the returned data (sections, dishes, descriptions, prices, dietary labels). It distinguishes from siblings like search_dishes by focusing on menus after finding the restaurant, and mentions prerequisite tools.
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 explicitly instructs to use search_places or list_categories first to obtain the place_slug, providing clear guidance on when and how to use this tool, effectively differentiating it from other place-related tools.
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.
Every tool has a clearly distinct purpose, with detailed descriptions that prevent ambiguity. Overlaps like create_booking vs request_reservation are clarified by domain (appointments vs restaurant) and mechanics.
All tool names follow a consistent verb_noun pattern (e.g., create_booking, list_events, search_places). The same conjugation style (snake_case) is used throughout, with no mixing of conventions.
At 28 tools, the set is slightly larger than the typical well-scoped range (3-15), but each tool corresponds to a distinct feature of the neighborhood directory, making the count reasonable for the breadth of functionality.
The tool surface covers all major user-facing actions: searching, browsing, booking, purchasing, and retrieving information. No obvious gaps exist for the stated purpose of a neighborhood directory.
