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

Annotations already convey readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds that the tool produces a 'bounded fit judgment' and assesses whether the product is 'likely to work', signaling a probabilistic, qualified conclusion rather than an absolute measurement. It also mentions 'fit-driven alternatives', implying the tool may suggest other options. No contradiction with annotations.

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, well-structured sentence that front-loads the purpose and scope, then lists exclusions. Every clause adds either a constraint or a scope detail; there is no redundancy or filler.

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?

The tool has a non-trivial input schema (nested Product, Evidence, UseContext) and no parameter descriptions, yet the description only covers when to use the tool and not how to construct a valid input. It omits any guidance on what constitutes 'evidence', how to phrase the 'question', or what 'bodySignals' and 'interactionSignals' represent, leaving the agent to infer from property names alone. Given the complexity, this is incomplete.

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?

Schema description coverage is 0%, and the description provides no elaboration on any of the six parameters. While parameter names like 'bodySignals' and 'interactionSignals' are somewhat self-explanatory, the description gives no guidance on how to populate the required 'question' and 'product' fields, nor how to structure 'evidence' or 'useContext'. For a complex schema with nested objects, this is a significant gap.

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 ('Use when...') and a clear resource: a bounded fit judgment about whether a specific finished footwear product works for a person in a given use context. It enumerates concrete sub-topics (pressure, toe contact, heel slip, width/size, dynamic use, keep/exchange, alternatives) and explicitly excludes generic education, style, size conversion, and medical diagnosis, making the tool's scope unmistakable even without sibling context.

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?

It provides an explicit trigger condition ('Use when the user needs...') and a clear negative list ('Do not use for...') covering four unrelated domains. This gives an agent unambiguous selection criteria, which is especially important given no sibling tools exist to differentiate against.

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