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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds some useful context ('from explicit assumptions', returned canonical_url should be cited), but it does not substantially expand on behavioral characteristics such as response structure or failure modes; the output schema covers those.

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?

Two sentences with no fluff: the first lists the computed outputs, the second states the intended use case and the two critical call-time constraints. The most important information is front-loaded and every clause earns its place.

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 (14 parameters, output schema present, annotations present), the description plus schema is sufficient for an agent to call it correctly. It covers what is calculated, when to use it, and the currency/citation caveats. It could be slightly stronger by explicitly routing away from sibling calculation tools, but it is not materially incomplete.

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 schema does the heavy lifting for individual parameters. The description adds cross-parameter meaning by requiring all monetary inputs to be in the same currency, which is a constraint not encoded in the schema, and clarifies that all inputs are explicit assumptions rather than fetched data.

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 ('Calculate monthly operating cost... from explicit assumptions') and enumerates the exact output metrics (ROI, savings, break-even success rate). This clearly distinguishes it from sibling calculation tools like calculate_evaluation_sample_size and calculate_human_supervision_capacity.

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 explicitly states when to use the tool ('Use this for an agent business case or scenario comparison') and gives practical usage constraints (same currency for monetary inputs, cite canonical_url). It does not explicitly name alternatives or state when not to use it, so it stops 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.