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

Annotations already cover readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds useful behavioral context by defining scope as tracked=user's watchlist vs universe=all and clarifying the metric is 90-day unit velocity. However, it does not disclose sorting behavior, result limits, or what the response contains, though the schema covers limit 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 front-loaded with the core purpose and key filters, followed by useful query-phrase examples. The phrase list earns its place because it directly helps an agent map user intent to this tool. It is compact and well-organized, though slightly repetitive with the scope explanation appearing in both the filter list and the final instruction.

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 the high parameter count (22), low schema coverage (41%), and no output schema, the description is not complete enough for advanced or nuanced calls. It covers the simplest cases well but does not explain important common controls such as marketplace_id, limit, brand matching, or the many numeric filter thresholds an operator might use to refine a velocity-brand search.

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 only 41%, so the description must compensate for many undocumented parameters. It does explain scope, category, minimum velocity, exclude Amazon private label, and exclude gated, but it ignores 17 other parameters including brand, limit, marketplace_id, and all the min/max control-score, revenue, winner-diversity, and seller-churn filters. This leaves a substantial portion of the parameter surface without meaningful semantics.

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 opening phrase 'Find top brands by 90-day unit velocity' is a specific verb+resource+metric combination that clearly distinguishes this tool from sibling brand tools like brands_gaining_sellers or brand_new_asins. It names the exact metric and the resource ('brands'), so an agent can immediately understand what the tool does.

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?

The description gives explicit conversation triggers ('fastest selling brands', 'top velocity brands', 'brands I track by velocity', etc.) and tells the agent to set scope=tracked when the user says 'my brands' or 'brands I track'. It lacks explicit when-not-to-use guidance or named alternatives, but the usage context is clear and actionable.

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