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

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds real behavior that the annotations do not cover: the call returns an asynchronous job that must be polled, and each failure mode is given a distinct error name with its meaning. That is a genuine value-add. It does not say what the job payload contains while it polls or whether polling is rate-limited, so this is not a 5.

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 front-loaded: the first sentence defines the return value, followed by dependency, workflow, and error taxonomy. Every sentence adds information, and there is no filler. The terse error-list formatting is compact without becoming cryptic.

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?

An output schema exists, so the description does not need to explain the returned schema's contents. The description covers the prerequisite, the async job workflow, and the failure taxonomy, which is a lot for a two-parameter tool. The remaining gap is the unexplained session_id and the lack of detail on what to do with the schema once obtained, but neither blocks a correct invocation.

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 0%, so the description has to carry the semantics of both parameters. It does a good job on product_sku: the value comes from the cache populated by catalog_search, it must be in the cache before the call, and a miss raises ProductNotFoundError. It says nothing at all about session_id, which is required and undefined in both the schema and the description, leaving one of the two parameters opaque.

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 and resource: 'Return the strict JSON schema the LLM must fill to configure a product.' That tells an agent exactly what it produces, and the title reinforces the point. It does not explicitly contrast this tool with catalog_configure_product, which is the closest sibling, but the purpose itself is unambiguous.

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?

It states a hard prerequisite: product_sku must be resolved from a cache that a prior catalog_search populated, and the ProductNotFoundError branch says 'search first'. The description also explains the correct next step ('poll until SUCCEEDED') and names the poll_job-style workflow. It stops short of stating when not to use this tool versus catalog_configure_product, so it does not reach a 5.

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