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

Annotations already establish readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds genuinely non-obvious behavior: results come back 'in one call' (no pagination/aggregation loop), the time series buckets by UTC days, and there is deliberately no opens metric. The UTC-day bucket boundary and the opens caveat are exactly the kind of context annotations cannot convey.

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?

Three sentences, front-loaded with the return contents, followed by usage and then the opens caveat. Every sentence carries information the agent cannot obtain from the schema, and there is no filler.

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 carries the burden of describing the response, and it does so concretely (five named totals, variant breakdown, step breakdown, daily series). It also preempts a likely agent error by explaining the missing opens metric, leaving nothing essential unstated for a single-parameter read tool.

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%, and the single parameter already documents itself as 'The numeric campaign ID (from list_campaigns)'. The description adds no further meaning about the id (e.g., provenance or format edge cases), so the baseline of 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 uses a specific verb-resource pair ('Returns a campaign's performance') and enumerates exactly what the response contains: totals, per-A/B-variant results, per-sequence-step results, and a daily time series. An agent can distinguish this analytics tool from metadata tools like get_campaign. It stops short of naming a sibling, so it lands just under a 5.

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 it to judge how a campaign is doing or to compare variants' gives explicit usage context tied to the tool's content. There are no when-not conditions or named alternatives (e.g., get_outcomes_report or get_inbox_placement_stats_by_date), so the agent must infer exclusions itself.

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