calc_metric

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

With no annotations, the description must carry the full burden of behavioral disclosure, but it only says 'COMPUTE' and 'Exact.', implying a pure calculation without side effects. It does not describe return format, error behavior, or any side effects. 'Exact' hints at precision, but this is minimal context that does not adequately inform the agent about the tool's behavior.

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, concise sentence with no wasted words. The leading 'COMPUTE.' verb is front-loaded, making the tool's primary action immediately clear. It is well-structured for its limited content, though it sacrifices detail for brevity.

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 tool's complexity (3 parameters, one a nested object, no output schema, no annotations), the description is severely incomplete. It does not mention what the tool returns, how to use the 'params' object, or what metrics are supported beyond a partial list. Sibling tools include a list function (calc_list_metrics) that might help, but the description does not reference it or provide enough context 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?

The schema has 0% description coverage, so the description must compensate, but it only provides example values for the 'metric' parameter (ltv, cac, rule_of_40, nrr). It does not explain the structure or purpose of the 'params' object or the 'currency' parameter, leaving the agent without enough information to construct valid inputs.

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 states the tool's purpose: it computes exact business/SaaS/finance metrics, with examples like ltv, cac, rule_of_40, and nrr. This distinguishes it from more specific sibling tools (e.g., calc_npv, calc_irr) by serving as a generic metric calculator, though it could be more explicit that it accepts a metric name and computes the corresponding value.

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?

No usage guidance is provided. The description does not mention when to use this tool versus alternatives like calc_npv or calc_irr, nor does it indicate any prerequisites or exclusions. Users are left to infer that it handles a range of business metrics, but there is no explicit when-to-use or when-not-to-use guidance.

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