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

Annotations already establish this as a safe read-only, idempotent lookup, and the description adds meaningful behavioral context beyond that. It discloses how the saved preference is applied automatically, how add_to_cart uses it when size is omitted, and how fit affects product search behavior.

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 compact and front-loads the core action and the key instruction to call it before asking for size. The second sentence is dense and combines automatic application, add_to_cart behavior, and search style mappings, but every element is useful and there is little waste.

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 a zero-parameter read-only tool with rich annotations and an output schema, the description provides everything needed to call it correctly. It covers purpose, timing, fallback behavior when a default exists, and how the result feeds into sibling tools.

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 tool has zero input parameters, so there is no parameter semantics to explain in the description. A baseline of 4 is appropriate because the schema requires no compensation and the description correctly avoids inventing parameter details.

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 states a specific verb and resource: return the shopper's saved default size and fit. It clearly distinguishes this read-only preference lookup from related mutation tools such as set_user_prefs through the get/set naming and saved-data framing.

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 gives explicit timing: call this before asking the user for a size, and apply the default automatically if one exists. It also names concrete downstream alternatives, explaining how add_to_cart can consume the saved size and how search_products should use the saved fit with specific style values.

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