Break-even volume

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

Annotations already mark this readOnly and idempotent, and the description adds substantial behavioral detail: how contingency is folded into contribution margin, the exclusion of escalation, handling of fixed revenue offset, and edge cases returning null or unitsUnreachable. This goes well beyond what annotations provide and fully discloses the computation's assumptions.

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 long but well-structured: a one-line summary, then logic, args, returns, and examples. It front-loads the purpose and uses sections effectively. Some sentences about contingency could be considered verbose, but they are essential to prevent misuse, so a 4 is fair.

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?

Given the complexity of the model, the description covers assumptions, edge cases (null, unitsUnreachable), return fields, and usage scenarios. It is complete enough for an agent to invoke correctly, and the output schema (though not shown) is further supported by the listed return fields.

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?

The schema describes volume_factor ('Scales planned volume before solving'), and the description adds a default of 1 and clarifies that model has the same shape as cashflow_evaluate_contract. This adds some context, but with only 50% schema coverage the description does not fully compensate for the lack of documentation on the nested model fields, which are already described in the schema itself. Baseline 3 is appropriate.

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 opens with a specific verb and resource: 'Compute the monthly volume at which a contract stops losing money, without running the full schedule.' It clearly distinguishes from the sibling cashflow_evaluate_contract by noting it avoids the full schedule, and it explains the core purpose unambiguously.

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 description gives explicit 'Use when' examples ('How many units a month do we need to cover costs?', 'How much headroom is there between plan and break-even?'). It also contrasts with the full schedule, implying the alternative is cashflow_evaluate_contract, but it does not explicitly name that tool or state when not to use this one, so a 4 rather than 5.

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