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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is covered. The description usefully adds that results are "real" US sales and are the most recent, but says nothing about coverage limits, latency, auth, or how many comps come back.

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, zero filler. The what-and-returns statement is front-loaded and the usage condition follows immediately.

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 single-parameter read tool with full annotation coverage and no output schema, the description conveys the resource, freshness, and returned metrics, which is essentially what an agent needs. Only minor operational detail (volume or limits of returned comps) 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?

There is exactly one parameter and the schema documents it fully at 100% coverage, including length bounds and formatting advice. The description's "brand, model or pattern, a few specific words" merely paraphrases the schema, so the baseline 3 is appropriate.

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+resource: retrieves the most recent real eBay US sold comps for a query, and even names the returned statistics (count, median, quartiles). That is far more specific than a tautology, but it never names or contrasts with the obvious siblings (price_item, worth_it), so it stops short of a 5.

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?

"Use when the user wants to see what actually sold and for how much" gives a clear triggering condition and implicitly separates it from speculative pricing tools. It supplies no explicit when-not guidance and does not name an alternative sibling, so it is context without exclusions.

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