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

Annotations already carry readOnlyHint=true, and the description reinforces this with 'Pure data fetch (no AI analysis) — reason over the returned data yourself.' This adds meaningful behavioral context beyond the annotation: it explicitly tells the agent the tool does NOT perform analysis and that history 'when available' may be absent. That's valuable behavioral disclosure.

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?

Well-structured two-sentence description: first sentence states data granularity and content, second gives usage guidance. No wasted words, but could be slightly tighter — the usage paragraph is a bit long relative to its informational density.

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?

Despite no output schema, the description enumerates expected return fields (price, sales/revenue, reviews, rating, LQS, sellers, history) which substitutes well. The 2-param tool with full schema coverage and a thorough behavioral/usage narrative is complete for an agent to select and use correctly.

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% (both asin and marketplace documented in schema), so baseline is 3. The description adds marginal context by confirming the tool expects an ASIN and that marketplace defaults to COM. It doesn't heavily elaborate beyond the schema, but that's acceptable given full schema coverage.

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 states specific verb+resource ('Full raw data for a single Amazon product by ASIN') and enumerates the exact fields returned (price, sales/revenue, reviews, rating, LQS, sellers, history). It clearly distinguishes from siblings like analyze_niche and compare_products by emphasizing 'single product' and 'full raw data'.

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?

Provides explicit usage context ('audit the product like a sourcing analyst... conclude whether a new seller should enter GO/NO-GO'). Does not explicitly name alternative tools or state when NOT to use it, but the 'single product' vs set/niche distinction is clear enough given sibling names.

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