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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the time-bucketed aggregation behavior and the focus on engagement changes, which is useful. However, it does not disclose details like default time range, pagination, or how metrics are computed, so it adds only moderate context beyond annotations.

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?

Two sentences with no filler. The first sentence front-loads the core function and metric types, and the second adds the analytical use case. Every word earns its place.

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?

For a read-only metrics tool with 88% schema coverage and no output schema, the description is largely complete: it names the metrics, the time-bucketing behavior, and the analytical purpose. It could mention default time range or that campaign_id is required, but the schema already marks campaign_id as required. The main gap is not explaining what 'conversion' means in Customer.io context, but that is a minor omission.

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 88%, so the schema already documents most parameters well. The description adds the concept of time-bucketing and the metric types, which maps to resolution and campaign_id, but it does not add meaning for parameters like message_type, timezone, or start/end beyond what the schema provides. 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 states a specific verb ('Return'), a specific resource ('Customer.io delivery, bounce, open, click, unsubscribe, and conversion metrics for one campaign'), and the analytical purpose ('Answers how a lifecycle campaign performed and when engagement changed'). It clearly distinguishes from siblings like cio_list_campaigns and cio_list_messages, which are list-oriented rather than metrics-oriented.

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 when to use it: when you need time-bucketed campaign performance metrics and engagement trends. It does not explicitly name alternatives or exclusions, but the sibling list shows other Customer.io tools that are list-focused, making the context reasonably clear. It lacks explicit 'use X instead' guidance, so it falls short of a 5.

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