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

Annotations already declare readOnly, idempotent and non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: the bucket granularity follows the selected period and results are split by severity, which tells the agent what shape of answer to expect. It stops short of describing pagination or limits.

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?

A single front-loaded sentence with the core question first and the granularity parenthetical immediately after; nothing is wasted. The parenthetical is slightly dense but still readable.

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 11 optional parameters and no output schema, the description should say more about the returned structure (e.g. a series of buckets each with per-severity counts). It conveys the split and granularity but leaves the exact response shape and empty-bucket behavior to inference.

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 every one of the 11 parameters is already documented in the schema. The description only alludes to 'a filter' generically and adds no syntax or interaction detail (e.g. how range interacts with from/to) beyond what the schema provides, 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?

The description states a specific verb and resource ('How many CVEs ... were published') plus the aggregation granularity (hour/day/week/month/year) and the severity split, which clearly separates it from a plain search or stats tool. It does not name a sibling tool explicitly, so it falls short of 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 for trends and exact counts' gives a hint about intent, but there is no explicit when-not guidance and no mention of alternatives such as get_stats or search_cves. Usage is implied rather than prescribed.

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