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

The readOnlyHint=true annotation already declares this is a read-only operation, and the description adds useful behavior: it 'pulls live Amazon data,' 'runs the right analyses internally,' and 'returns a complete, user-ready report.' This adds behavioral context about internal orchestration and output format beyond the annotation, though it doesn't disclose rate limits or how history interacts with the internal analysis.

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 focused single paragraph with example queries embedded for usability. It front-loads the purpose and includes the alternative-tool guidance efficiently. Slightly longer than strictly necessary due to the example queries and multiple clauses, but all content earns its place.

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 natural-language agent tool with only 2 params and no output schema, the description adequately covers purpose, alternative tools, and return behavior. The examples illustrate both product-level and niche-level use cases. It's complete enough for an agent to know when and how to invoke it, though the exact report format could be more specific.

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 documents both parameters. The description reinforces the message parameter as a natural-language question with concrete examples, and implies history is for multi-turn context, but doesn't add meaning beyond what the schema descriptions already provide. Baseline 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 clearly states this is an all-in-one Amazon research assistant that accepts natural language queries and returns a finished analysis. It explicitly distinguishes itself from the granular amzscout_* sibling tools by noting no sub-tool selection is needed, which sets it apart from all 11 siblings.

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 explicitly states when to use this tool ('Best for a hands-off answer') and names the alternative ('the granular amzscout_* tools are the alternative when step-by-step orchestration is preferred'). It also provides concrete example queries showing the intended usage pattern.

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