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

No annotations and no output schema, so the description carries the disclosure burden — and it does disclose the four computed return values, which is the main behavioral fact for a deterministic calculator with no side effects. It omits how optional cost inputs default when omitted, a minor gap for a pure computation tool.

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, zero filler, with the triggering condition front-loaded and the return contract immediately after. 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?

With no output schema, the description correctly supplies the return values, and the six parameters are fully covered by the schema. It is nearly complete for a stateless calculator; only the defaulting behavior of the optional cost inputs is left unstated.

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 every parameter is already documented in the schema, including the default note for prompt_reduction_pct. The description adds no parameter-level meaning beyond that, so the baseline 3 applies.

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 states a specific decision-support purpose (fine-tuning vs prompt engineering) and enumerates the exact outputs (training cost, monthly inference savings, months-to-ROI, breakeven volume). It is clearly distinguishable from generic cost calculators by its ROI/breakeven framing, though it never names a sibling tool explicitly.

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?

'Use when a user is considering fine-tuning vs prompt engineering' gives a clear triggering condition. It does not name alternatives such as self-host-breakeven-calculator, which an agent might reasonably confuse it with, so it stops short of full routing guidance.

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