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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and closed-world, so safety is covered. The description adds real behavioral context beyond that: the 365 default / 1825 max window, the ms-timestamp requirement for explicit dates, and the engagement coverage semantics (`coverageStartAt`, `state`, `reason` distinguishing measured zeroes from partial history). That is solid added value, though it says nothing about response size, cost, or failure modes.

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?

Information is front-loaded by importance (what you get, then interval/include, then timeframe, then targeting) and most sentences carry distinct content. Some redundancy exists: the date-window constraints are restated in both the description and the schema property descriptions, which adds length without new meaning.

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?

An output schema exists, so return values need not be enumerated, and the description still covers the non-obvious parts: metric families, optional include views, engagement coverage interpretation, timeframe scoping rules, and campaign targeting. For an 8-parameter read tool this is essentially complete.

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?

With 88% schema coverage the baseline is 3, but the description earns more by explaining what `include=engagement` actually groups and by documenting the campaignId fallback to GROWSURF_CAMPAIGN_ID. Minor gap: it lists `interval` as day/week/month while the schema enum also allows `total`, and it does not explain how `days` interacts with explicit start/end dates.

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 ('Fetch analytics for your GrowSurf program') and enumerates the concrete metrics returned (participants, referrals, impressions, shares, affiliate revenue/commission/payout). It does not, however, distinguish this tool from closely named siblings like growsurf_get_campaign_activation_analytics or growsurf_get_participant_analytics.

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?

It gives clear operational guidance: use `interval` for a per-period series, use `include` for extra views, and scope time via `days` or an explicit start/end window. It states that `timezone` and `platform` apply only to engagement, which is useful scoping. It stops short of saying when to prefer this tool over the sibling analytics tools.

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