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

With readOnlyHint=true already marking it as safe, the description adds behavioral context: 'Pure data fetch (no AI analysis)' clarifies that no interpretation is performed, and it enumerates computed aggregates such as revenue concentration and brand spread. There is no contradiction with annotations, though a return-format disclaimer is absent.

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 front-loads the purpose in the first sentence, then adds a behavioral caveat and a structured how-to. The how-to is detailed but relevant to decision-making, with no filler content; it is somewhat long (~70 words) but well-organized.

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?

Since there is no output schema, the description compensates by listing output categories (price/sales/revenue/review distributions, revenue concentration, brand spread) and an example field (revenueTop5SharePercent). It doesn't fully specify return structure or pagination, but it provides enough context for a data-fetch snapshot tool.

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?

The input schema already provides 100% coverage with descriptions for all four parameters (keyword, count, filters, marketplace). The description adds no parameter-level details beyond the schema, only implying the output depends on keyword and count.

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 opens with 'Market snapshot for an Amazon niche/keyword — top products by revenue plus computed aggregates', clearly identifying the resource (niche/keyword) and what it delivers. The 'Pure data fetch (no AI analysis)' line and mention of aggregates distinguish it from siblings like amzscout_analyze_product or amzscout-agent.

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 'How to use' section provides clear context on when to use the tool: to judge niche attractiveness based on demand concentration, price bands, review moats, and brand spread. It also implies when not to use it ('Pure data fetch, no AI analysis'), but it doesn't explicitly name alternative tools or exclusions.

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