mhlb_get_menu

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

Annotations already declare readOnlyHint=true, so the read-only nature is structured. The description adds the context that it is the 'read half' of placing an order, which hints at a typical workflow but does not disclose additional behavioral traits like response format, pagination, or error handling. Since annotations carry the safety profile, the description adds modest value, earning a 3.

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?

Two sentences with zero redundancy. The first sentence states the action, scope, and content list; the second provides a contextual hook. Information is front-loaded and every word earns its place. Excellent structure for an agent to parse quickly.

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 simple read-only tool with two straightforward parameters and no output schema, the description is fully complete. It enumerates the expected return fields (vendor, items, sizes, add-ons, prices, ordering deadline) and clarifies the single-student single-date scope. An agent can invoke the tool correctly without needing 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 input schema documentation covers 100% of parameters (both date and studentId are described with formats and provenance). The description does not add any semantics beyond the schema—it does not elaborate on date validation or studentId usage. Per the baseline for full schema coverage, this scores 3.

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 uses a specific verb ('Get') and resource ('orderable menu') with precise scope ('one student on one date'). It lists the contents (vendor, items, sizes, add-ons, prices, ordering deadline), clearly distinguishing it from sibling tools like mhlb_get_cart or mhlb_get_order_form. This is not a tautology and leaves no ambiguity about the tool's function.

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 phrase 'This is the read half of placing an order' provides clear context that this tool should be used as a precondition to placing an order. It does not explicitly name alternatives (e.g., mhlb_get_order_form) or state exclusions, but the context is sufficient for an agent to infer when to use it. No misleading guidance is present.

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