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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the metrics computed but does not disclose whether the tool performs a single calculation or multiple, how it handles missing optional parameters (e.g., clicks, adSpend, conversions), whether it returns all metrics at once, or any assumptions about currency/format. For a calculation tool with no annotations, this is a meaningful gap.

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 two short sentences and front-loads the key metrics. It is efficient and scannable, though the second sentence ('Facebook, Google, TikTok ad analysis.') is somewhat redundant with the first and could be merged or expanded with usage guidance.

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 and no annotations, the description should clarify what the tool returns and how it behaves with partial inputs. It does not explain whether all five metrics are always returned, what happens when optional parameters are omitted, or how the metrics relate to each other. For a 5-parameter calculation tool, this is 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 already documents each parameter's purpose. The description adds the metric names (ROI, ROAS, net profit, CPA, CPC) and maps them to the marketing context, which helps an agent infer which parameters feed which metric, but it does not add detail beyond the schema's field descriptions. 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 names a specific verb ('calculate') and resource ('ROI, ROAS, net profit, CPA, CPC for marketing campaigns'), and mentions the ad platforms (Facebook, Google, TikTok). It is clear about what the tool computes, though it does not explicitly distinguish itself from the sibling calculate_rental_roi or calculate_dropship_profit beyond the marketing-campaign context.

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 implies usage for marketing campaign analysis by listing relevant metrics and platforms, but it does not state when to prefer this tool over alternatives like calculate_break_even or calculate_rental_roi, nor does it give exclusions or prerequisites. The context is clear enough for a marketing ROI scenario, but no explicit when/when-not guidance is provided.

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