Blended MER, platform overlap and assists, lagged spend correlation (not causal)

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. Beyond that the description only adds the '(not causal)' caveat about how to read the lagged correlation, and says nothing about the POST body requirement, computation cost, or the lag/platform caps that shape results.

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 a single short fragment with no wasted words, but the space saved is space that should have been used; the only structural element is the trailing endpoint path, which is metadata rather than 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?

This is a complex analytics endpoint with a ten-property nested request body, no output schema, and no annotation-level detail about returns. The description does not explain required date range semantics, defaults for maxLag/maxPlatforms, or what the response contains, leaving the agent unable to call it correctly from the definition alone.

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 top-level parameter is a nested body with ten undocumented properties (maxLag, lookbackDays, maxPlatforms, currency, platform, campaignId, crossCampaignId, clientId). The description supplies no meaning for any of them; only faint topical hints ('lagged' -> maxLag, 'platform overlap' -> maxPlatforms) exist, which is far short of compensating for the coverage gap.

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 analytics concepts the endpoint produces (blended MER, platform overlap, assists, lagged spend correlation) which does differentiate it from siblings like analytics_breakdown or analytics_pacing. However it is a bare noun phrase copied from the title with no verb and no statement of what the tool actually returns or computes, so the agent must infer the operation.

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, no exclusions, and no reference to the many adjacent analytics siblings (analytics_compare, analytics_timeseries, analytics_saturation, analytics_reallocation). The parenthetical '(not causal)' hints at interpretation limits but says nothing about when this tool should be selected over alternatives.

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