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

Annotations already establish readOnlyHint=true and destructiveHint=false. On top of that, the description adds meaningful behavioral detail about what the tool returns: top 10 sellers, top 10 brands, and week-over-week deltas. This is useful beyond the annotations, though it does not disclose edge cases or filtering 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?

Two sentences with no filler. The core purpose is front-loaded, the output is summarized concretely, and the usage trigger is placed at the end in natural language. Every sentence 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?

For a tool with 30 parameters and no output schema, the description is too thin. It gives a high-level sense of the output but does not explain how the many filter parameters affect results, whether they are optional, how they interact, or what the returned data structure looks like. The high complexity demands more guidance than this.

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 10%, so the description carries a heavy burden for explaining parameters. It does not. It only hints at 'brand or category root' as entry points, but gives no guidance on the 30 parameters, their meanings, or how to combine them. The three schema-described params (seller_name, marketplace_id, dominant_category_velocity_tier_in) carry the only real semantic weight.

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 uses a specific verb ('Map') with a clear resource ('competitive landscape for a brand or category root') and states concrete outputs: top 10 sellers by observed buybox days held, top 10 brands by winner-diversity HHI, and week-over-week deltas. It also directly ties to user intents like 'who's winning this category?' which distinguishes it from nearby sibling tools.

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 explicitly says when to use the tool: when the user asks 'who's winning this category?' or 'who controls the buybox here?'. It provides clear context for selection, though it does not name alternatives or state when not to use it.

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