mcp_cook_whatToEat

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

No annotations are provided, so the description carries the transparency burden. It discloses that the tool performs a recommendation based on people count and returns dish combinations, but it does not mention side effects, limitations, or output structure. This is adequate but not detailed.

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 a single, direct sentence that wastes no words and leads with the user need. It is perfectly sized for the simplicity of the tool.

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 tool with one well-documented parameter and no annotations or output schema, the description covers the core purpose and expected output at a high level. It could specify the return structure or mention that it only uses peopleCount, but overall it is reasonably complete.

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 input schema already fully describes the 'peopleCount' parameter, including range and behavioral effect, so the description adds no additional parameter-level meaning. Baseline 3 applies due to high schema coverage.

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 recommends suitable dish combinations based on the number of diners, which is a specific verb+resource+condition. However, it does not explicitly differentiate itself from the sibling tool 'recommendMeals', so it falls short of a 5.

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 opening question '不知道吃什么？' and the condition '根据人数' provide a clear context for when to use this tool. It does not mention exclusions or alternative sibling tools, but the use case is well implied.

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