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

Annotations only declare readOnlyHint and destructiveHint; the description adds substantial behavioral context beyond them. It explains the three data sources being merged, how seed terms expand to ASINs, the volume_source variants with their calibration levels, the sort order, and the presence of standard pagination, giving a clear model of what the tool does step by step.

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 a dense, single-paragraph run-on, but it is front-loaded with the core purpose (reverse-ASIN lookup) before diving into data sources and result semantics. Every clause contributes information, and the length is justified by the tool's complexity, though clearer structure would improve scannability.

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 no output schema, the description adequately enumerates the result fields (matched_asins, match_count, volume, volume_source, search_frequency_rank, relevance_score) and sorting behavior. It still leaves gaps around the meaning of weeks and min_match_count and the exact response envelope, but it covers the essential return semantics for an agent to reason about outcomes.

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 only 50%, and the description meaningfully explains the `terms` expansion and hints at offset/limit via 'standard pagination'. However, it does not clarify `limit`, `weeks`, `min_match_count`, or `offset` details, so it only partially compensates for the undocumented parameters.

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 a specific verb and resource: 'every keyword phrase the input ASINs are known for', clearly framing a reverse-ASIN lookup. It distinguishes itself from sibling keyword tools by emphasizing multi-input, merged first-party sources, and competitor ASIN support, so an agent can immediately recognize its unique purpose.

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?

Usage context is strongly implied by the reverse-ASIN angle and 'works for competitor ASINs', but the description never explicitly states when to choose this over related siblings like brand_sqp, brand_top_search_terms, or ppc_search_terms. There are no exclusions or alternative-routing statements, so an agent must infer the appropriate context.

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