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

Annotations declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds genuine behavioral context beyond that: this is a separate dataset whose records carry final sale price and sale date, and that price filters apply to the sold amount, not the listing ask. It does not discuss pagination or result caps beyond what the schema spells out.

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 short sentences, front-loaded with the dataset identity and the key differentiator (sale price vs ask). No filler, every clause earns its place.

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?

With 12 fully documented params, an output schema handling return values, and annotations covering safety, the description supplies exactly the missing context: dataset identity and price-filter semantics. Nothing needed to call this correctly is absent.

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 coverage is 100%, so the baseline is 3, but the description adds real meaning by clarifying that min_price/max_price operate on the final SOLD price rather than the asking price. That is a semantic distinction not visible from the schema alone, warranting above baseline.

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 and resource ('Search Grailed's SOLD-listing index') and immediately contrasts it with the sibling grailed_search as a separate dataset with final sale price and date. An agent can distinguish it from active-listing 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?

Explicitly says it has the same filter shape as grailed_search, that min_price/max_price filter SOLD price rather than asking price, and names the exact use case (sale-price-history/comparable-sales lookups). A clear condition for choosing this over the active-listing sibling is provided.

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