mcp_howtocook_whatToEat

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

No annotations are provided, so the description carries full burden. It mentions '推荐' (recommend) but doesn't disclose behavioral traits such as whether this is a read-only operation, how recommendations are generated, potential limitations, or what the output format looks like. For a tool with zero annotation coverage, this is a significant gap.

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 appropriately sized and front-loaded: a single sentence that directly states the tool's purpose without unnecessary words. Every part earns its place, making it efficient and clear.

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 complexity (a recommendation tool with 1 parameter), no annotations, no output schema, and 0% schema coverage, the description is incomplete. It lacks details on how recommendations work, output format, or differentiation from siblings, making it inadequate for an agent to use effectively without additional context.

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 description adds some meaning beyond the input schema: it explains that 'peopleCount' is used to '根据人数' (based on number of people) for recommendations. However, with 0% schema description coverage and only 1 parameter, the baseline is 4, but the description doesn't fully compensate by detailing constraints like valid ranges or examples, so a 3 is appropriate.

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's purpose: '根据人数直接推荐适合的菜品组合' (recommend suitable dish combinations based on number of people). It specifies the verb '推荐' (recommend) and resource '菜品组合' (dish combinations), though it doesn't explicitly distinguish from sibling tools like mcp_howtocook_recommendMeals, which appears similar.

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 provides minimal guidance: it implies usage when '不知道吃什么' (don't know what to eat) and based on number of people. However, it offers no explicit when-to-use vs. alternatives, no prerequisites, and doesn't differentiate from sibling tools like mcp_howtocook_recommendMeals, leaving the agent to guess.

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