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

The description discloses behavioral traits beyond annotations: no side effects, no network/storage access, idempotent, non-destructive, and specific error behavior for division by zero or non-finite inputs. While annotations already signal read-only idempotent non-destructive, the description adds deterministic behavior and explicit error handling, which is genuinely useful.

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 well-organized with labeled sections (purpose, when to use, behavior, returns, parameters), but the formula is stated twice: once in the opening sentence and once in the explicit Formula section. Minor redundancy aside, the structure is front-loaded and scannable.

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 deterministic calculation with three numeric parameters, coverage is comprehensive: annotations handle safety, schema handles parameter definitions, and the description supplies usage conditions, behavioral guarantees, error behavior, return shape, and interpretation of negative results. No output schema exists, but the RETURNS section fully documents the response.

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% with each parameter described and exemplified, so the baseline is 3. The description adds meaning by tying the three parameters to the formula (DSO + DIO - DPO), clarifying they are components that produce days, and noting a negative result means operating on supplier cash. This goes slightly beyond the schema's per-parameter examples.

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 object ('Calculate the cash conversion cycle') and immediately distinguishes it from sibling component tools by presenting the composite formula CCC = DSO + DIO - DPO. It clearly identifies the tool as the aggregate measure, not one of the individual day/ratio tools in the sibling list.

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?

Explicit WHEN TO USE and WHEN NOT TO USE sections give direct guidance: use as the definitive working-capital efficiency measure, but avoid unless all components are on a consistent 365-day basis and comparable periods. This goes beyond generic context and helps an agent decide when to invoke this tool versus component-level tools.

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