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

Annotations already establish readOnly/openWorld, and the description adds real behavioral context: it is a distinct dataset, each item carries final sale price and sale date, and min_price/max_price apply to the sold price rather than the asking price. Return-shape details are not described, but the output schema covers that.

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?

Three tightly written sentences, front-loaded with what the dataset is, then the key filtering distinction, then the use case. No 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?

An output schema exists so return values needn't be spelled out. The description covers the crucial differentiators (sold vs active, price semantics) for a read-only search tool. Only the undocumented non-price filters keep it from being fully 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?

Schema description coverage is 0% across 12 params, so the description must compensate. It clarifies min_price/max_price semantics ('filter the SOLD price, not the original asking price') and points to grailed_search for the rest, but leaves the other 10 params (q, sort, size, designer, condition, etc.) undocumented.

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?

States a specific verb (Search) and resource (Grailed's SOLD-listing index) and immediately differentiates it from the active-listing sibling: 'a separate dataset from active listings'. An agent can tell it apart from grailed_search without opening either schema.

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?

Gives a clear use case ('sale-price-history/comparable-sales lookups') and references the alternative (grailed_search) with the same filter shape. It stops short of an explicit when-not-to-use, but the sold-vs-active framing effectively routes the agent.

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