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

Goes well beyond the readOnly/openWorld/destructive annotations by disclosing that the call is asynchronous, bounded to 20 SKUs, does not mutate the listing or replace the materialized baseline, and returns requested/queued/enqueue_failed state rather than an observed price. These are the exact behavioral traits an agent needs to avoid misinterpreting the result.

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?

Two tightly packed sentences with zero waste. The core action and its bound are front-loaded, and the second sentence delivers the scope and result-state caveats.

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 an async enqueue tool with full schema coverage, rich annotations, and an output schema, the description supplies everything else needed: async/bounded nature, no baseline mutation, and the meaning of the returned state. Nothing material is left ambiguous.

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%, so the schema already documents skus (1-20), include_raw_rows, and include_diagnostics. The description only restates the SKU bound and adds no format or interaction detail beyond the schema, so the baseline 3 applies.

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 (refresh listing offer observations) plus precise scope: bounded, asynchronous, up to 20 explicitly selected seller SKUs. It is clear what the tool does, though it never names a sibling (e.g., get_listing_offers) to sharpen the contrast.

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?

Gives clear context for when this applies — a bounded refresh request over an explicit SKU list — and clarifies scope ('reads Amazon only; it never changes a listing or replaces the materialized baseline'). It does not, however, state exclusions or point to the read-path alternative for obtaining observed prices.

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