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

Annotations already declare read-only and non-destructive behavior, and the description adds meaningful context about what the tool reports: freshness, row counts, date coverage, and backfill progress. It also clarifies how advertising data is scoped via the resolved profile and raw PPC datasets. No contradiction with annotations exists.

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 two sentences with no unnecessary filler. The core purpose is front-loaded, followed by the intended use and scope. Every clause 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 read-only metadata tool with two optional, well-documented parameters, the description provides enough context about what data is returned and which dataset families are covered. Since there is no output schema, the description's enumeration of freshness, row counts, date coverage, and backfill progress partially compensates, though a bit more detail on output shape would improve completeness.

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 parameters are already well documented in the input schema. The description adds only a small amount of extra meaning through 'for the resolved profile', which lightly connects to profile_id, but it does not meaningfully expand parameter semantics beyond the schema.

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 identifies the resource as per-dataset sync freshness and lists the specific data dimensions returned: row counts, date coverage, and backfill progress. It distinguishes itself from sibling data tools by explicitly covering both seller SP-API datasets and advertising datasets. However, it lacks an explicit verb such as 'retrieve' or 'list', which slightly weakens its action clarity.

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 phrase 'use to caveat answers correctly' gives an explicit intended use case, and the description clarifies the scope across seller and advertising datasets. It does not mention when not to use the tool or name alternative tools, but the use context is clear enough for an agent to select it appropriately.

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