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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false. The description adds substantial behavioral context beyond annotations: it counts finalized invoices by invoice date, excludes drafts and imported invoices, does not indicate payment status, and sums different currencies unless a filter is given.

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 a single, front-loaded sentence that covers purpose, outputs, and key caveats without filler. It is dense but every clause contributes; structure could be slightly improved by splitting the long sentence, but it remains clear.

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 no output schema, the description lists the return contents explicitly (total, monthly breakdown, top ten clients) and covers the safety profile via annotations. It also discloses important limitations (excludes drafts/imported, payment status unknown, currency mixing), leaving no major gap for an agent to call it 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 description coverage is 100%, so the baseline is 3. The description adds meaning beyond the schema by clarifying currency aggregation behavior ('adds different currencies together unless a currency filter is given') and reaffirming the default year, which is important for interpreting results.

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 specifies the verb ('Summarizes'), the resource ('invoiced revenue'), the scope ('one calendar year'), and the exact outputs ('total in cents, a month-by-month breakdown and the ten largest clients'). It also names the use case ('questions about turnover'), making it easy to distinguish from siblings like get_balance or get_client_insights.

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 gives a clear usage context ('Use it for questions about turnover') but does not name alternatives or explicit when-not conditions, such as using get_balance for outstanding amounts. The exclusions it provides are about data scope, not tool selection.

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