Maître d'MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It successfully explains the key behavioral trait of automatically merging dietary restrictions across group members and discloses the return value structure ('Restaurant recommendations with notes on dietary compatibility'). It does not address potential rate limits or authentication requirements.

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 well-structured with the value proposition front-loaded in the first two sentences, followed by Args and Returns sections. While the docstring format is slightly verbose, it is necessary given the zero schema coverage; every sentence adds value either explaining core logic or parameter semantics.

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 presence of an output schema (not shown but indicated), the description appropriately focuses on the tool's unique group-based filtering logic rather than return value details. It adequately covers the single required parameter constraint (group_name) and the tool's specific domain (dietary compatibility).

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 Args block in the description provides crucial semantic meaning for all five parameters (e.g., 'group_name: Name of the saved group,' 'location: Where to search near'), fully compensating for the lack of JSON schema documentation.

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 'Search[es] for restaurants suitable for a saved group' and distinguishes itself from the sibling 'search_restaurants' by emphasizing automatic merging of 'members' dietary restrictions.' However, it stops short of explicitly naming the sibling tool or contrasting use cases directly.

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 context by referencing 'saved group,' which suggests prerequisite setup via 'manage_group.' However, it lacks explicit guidance on when to prefer this over 'search_restaurants' (e.g., for individuals vs. groups) or warnings about required group existence.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.