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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds genuine behavioral context by specifying that results are granular aggregates partitioned by provider (Google Workspace, Microsoft 365), individual mailboxes, and reply sentiment. It stops short of describing response shape, sorting, or any latency/limit behavior, which keeps it out of the top band.

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, each doing distinct work: identity/dimensions first, return semantics second, routing rules last. Front-loaded with the payoff and free of filler or restated name text.

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 one-parameter, read-only analytics tool with no output schema, the description supplies enough to call it correctly and interpret roughly what comes back. It does not clarify the granularity of the returned aggregates (e.g., ordering, nesting per dimension) or the fact that the numeric 'days' field only meaningfully accepts 7/30/90, leaving minor gaps.

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?

Only one parameter exists and schema description coverage is 100%, so the schema already defines 'days' with its 7/30/90 guidance. The description adds no range, default, or semantics beyond that, which is the expected baseline for a single fully-documented parameter.

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?

Names a specific analysis resource and enumerates the three breakdown dimensions (provider, mailbox, sentiment), which is far more precise than the generic name suggests. It explicitly distinguishes itself from get_campaign_stats and get_overview, so an agent can route correctly without opening sibling schemas.

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?

Contains an explicit 'USE THIS to diagnose deliverability issues across providers or compare mailbox performance' trigger plus two 'DO NOT use' exclusions that each name the correct alternative tool and the condition selecting it. Nothing about when to prefer this tool is left to inference.

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