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

The description adds useful behavioral context beyond the read-only annotation: it is a heuristic label rather than a legal determination, it relies on cross-brand operator signals, and it notes Amazon US/UK scope. One minor caveat is that 'Amazon US/UK' appears narrower than the marketplace_id schema, which lists many Amazon marketplaces, but the clarification is still valuable.

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 compact and front-loaded with the core action and output categories, followed by concrete trigger phrases and a caveat. Every sentence adds relevant information, and nothing is redundant.

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 one required parameter, full schema coverage, and no output schema, the description is nearly complete: it explains what the tool does, what signals inform the label, when to invoke it, and what the label is not. It could be slightly stronger by clarifying whether results include evidence or confidence, but the inferred output of a categorical label is sufficient for an agent.

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 100%: operator_name is described as the seller/operator name, and marketplace_id has a full marketplace mapping. The tool description does not add much parameter-level meaning beyond those schema descriptions, so the baseline of 3 is appropriate.

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 ('Label') and resource ('operator/seller'), enumerates the exact classification labels, and names the underlying signals. It is clearly distinct from sibling operator tools like operator_compare or operator_resells_what, which are about comparisons or resale composition rather than classification.

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 trigger phrases ('what kind of seller is this', 'is this an authorized retailer or an arbitrage seller', 'classify this operator'), so an agent can identify when to call it. It does not explicitly state when not to use it or name a sibling alternative, but the use-case guidance is strong enough.

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