evaluate_category_for_private_label

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

Annotations provide readOnlyHint=true. Description adds behavioral detail by specifying that the tool returns a per-signal pass/fail breakdown and a Strong/Moderate/Weak verdict. No contradiction between description and annotations.

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?

Description is a single paragraph with purpose front-loaded. Sentences are functional and concise, though slightly verbose in listing example queries. No wasted words overall.

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?

Given no output schema, the description adequately explains the return structure (per-signal pass/fail and verdict) and the evaluation factors (Amazon footprint, seller fragmentation, demand, price band). Covers all needed context.

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%. Description repeats the schema's parameter descriptions without adding new meaning. Per guidelines, baseline is 3 when coverage is high.

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?

Description clearly states the verb 'assess' and the resource 'category or niche' (any depth). Provides example queries that map to user intent, and distinguishes from siblings like evaluate_asin_sourcing and evaluate_brand.

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?

Description includes explicit use cases such as 'is X winnable for private label' and 'should I private-label X'. While it does not explicitly state when not to use or list alternatives, the examples provide clear context for appropriate usage.

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