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

Annotations already declare this a safe, idempotent, non-destructive read operation (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the safety profile is covered. The description adds that results are aggregated into 'groups', but does not explain how groups are formed, ranked, or whether similar messages are collapsed, leaving meaningful behavioral detail unstated.

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 short, well-formed sentences with the core purpose front-loaded and the finding-the-useful hint at the end. No wasted words.

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 100% schema coverage and annotations covering the safety profile, the definition is largely sufficient for invocation. The only minor gap is that it does not hint at the shape of the returned groups (e.g., group plus occurrence count), though no output schema exists to compensate.

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%, so the schema fully documents all 8 parameters, including count range (1-25), date filters, Lucene query fields, and severity. The description contributes no additional parameter meaning, so the baseline 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?

States a specific verb and resource: it identifies the most frequent/common error groups in a log, which is more specific than a generic list. However, it does not differentiate itself from the sibling messages_list_recent or messages_count, so an agent must infer the distinction between 'frequent' and 'recent' grouping.

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 phrase "Great for finding 'noisy' bugs" implies a use case, but there is no explicit when-to-use/when-not guidance or named alternative among siblings like messages_list_recent. Usage is implied rather than stated.

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