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

Annotations already cover read-only/idempotent safety, but the description adds substantial context beyond them: paid-plan gating, 1 credit per lookup, +0.5 with history, free for unknown seeds, and the daily cap of 2,000 calls. It also discloses the output shape (up to 6 lists, positions 1-10, first/last observed, marketplaces).

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?

Front-loaded with purpose, then usage triggers, exclusions, and cost in a logical order; nearly every clause carries distinct information. It is dense and long, but the density is justified by the tool's complexity rather than padding.

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 four-parameter tool with no output schema, the description covers return structure, cost model, limits, and country comparability. An agent has everything needed to call it correctly and interpret the result.

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 100%, so the schema already defines the parameters, but the description adds real meaning: history returns every observation since the harvest began, and compare returns each marketplace's primary list plus a position matrix. The comparability caution ('positions are comparable only within one list') is meaningful semantics the schema lacks.

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 and resource: it returns Amazon's own autocomplete suggestion lists for a seed term from a continuous harvest. It clearly distinguishes itself from siblings like shopping and search by declaring what it is not (volume figures, product-ranking map).

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?

Explicit 'USE WHEN' triggers (what buyers type, backend keyword language, product research seeds, country differences) and explicit routing away ('for products pass a term to the shopping tool'). When-not conditions are also given (not volume, not product rankings).

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