Diminishing-returns fit per platform or campaign with marginal ROAS and a confidence flag

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds only the HTTP path (POST /v1/analytics/saturation) and a hint at returned fields; it does not say whether the fit requires a minimum data volume, how confidence is derived, whether results are cached, or what happens for sparse campaigns. Marginal added context beyond structured data.

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?

It is one short, front-loaded sentence with no filler, which is good, but the brevity comes at the cost of under-specification rather than efficiency. Nothing extraneous, yet nothing that earns additional credit.

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, an eight-field nested body at 0% description coverage, and no sibling differentiation, the definition is too thin for an agent to call this correctly. Key facts an agent needs (valid date conventions, whether groupBy must match the provided platform/campaignId, expected response shape) are all absent.

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 0% and the single body parameter is a nested object with eight undocumented fields (from/to, groupBy, clientId, currency, platform, campaignId, crossCampaignId). The description only implies the groupBy choice via 'per platform or campaign' and says nothing about the date range semantics, currency handling, or how platform/campaignId/crossCampaignId interact.

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 the analytical artifact (a diminishing-returns fit with marginal ROAS and a confidence flag) and the grouping dimension (platform or campaign), which is more specific than a bare label. However it is essentially the title plus an endpoint path, with no verb describing the operation and no differentiation from sibling analytics tools such as analytics_forecast, analytics_pacing, or analytics_reallocation that an agent could use to pick the right one.

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?

There is no when-to-use guidance: nothing states which questions this fit answers that analytics_forecast or analytics_reallocation do not, nor any prerequisite (date range bounds, client context, minimum spend). Usage can only be inferred from the phrase 'diminishing-returns fit', which leaves the agent guessing among many sibling analytics endpoints.

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