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

Annotations already mark readOnlyHint=false and idempotentHint=false, so the write nature is known. The description adds valuable behavioral context by stating the operation is queued (asynchronous) and that a requestId is returned for polling via get_request_status, going beyond the annotations.

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?

A single, well-structured sentence. It front-loads the core action ('Queue generation'), gives the resource and period, and ends by routing to get_request_status. No filler or redundancy.

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?

With an output schema present and thorough parameter schemas, the description covers what matters: the asynchronous nature, the return of requestId, and the tracking step. It does not explicitly mention that results are generated asynchronously and may take time, but that is reasonably implied by 'Queue generation'. Slightly more detail about what to do while waiting would make it a 5, but it is complete enough for 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 coverage is 100%, so the description need not repeat parameter definitions. It lightly reinforces the meanings of reportType and format by listing examples (profit and loss, trial balance, etc.) and mentioning 'reporting period' for dates, which maps to fromDate/toDate. This adds marginal value over the schema, warranting a baseline 3.

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 'Queue generation' with a clear resource ('accounting report') and enumerates formats (spreadsheet, PDF, JSON) and report types. It also names the sibling get_request_status as the follow-up, which distinguishes this async export tool from direct data-retrieval 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?

It clearly indicates when to use this tool: to export a report in spreadsheet/PDF/JSON for a reporting period. It provides a next-step pointer to get_request_status, but does not explicitly exclude alternatives or name when not to use it, falling just short of a 5.

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