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

With no annotations, the description carries the full behavioral burden and does much of it: it discloses the scoring model and weights, defines the 'all' window precisely (every CVE ever in KEV or with a Metasploit module plus the past year), and notes that week rows carry movement since the previous week. It stops short of describing the return shape for non-week queries or any auth/rate-limit behavior.

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?

It is a single front-loaded paragraph that leads with what the tool returns and then layers on narrowing rules and the week alternative. Dense but nearly every clause carries information; the methodology weighting and URL are borderline extras that could be deferred to the linked page.

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 6-parameter, zero-required, no-output-schema, no-annotation tool, the description covers the critical decision logic (window vs. week, filter semantics, ranking). Gaps remain around valid tech/ecosystem values and the fields returned for non-week queries, which an agent would still have to discover by calling.

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 only 17%, so the description must compensate, and it largely does: it explains the window enum values, the filter enum meanings (critical, kev), the YYYY-Www week format, and critically the matching semantics ('a row matches any listed value of a field and every field passed'). It leaves tech and ecosystem value vocabularies undefined and does not explain the limit parameter's range, so it is not fully complete.

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 names a specific resource (the cve.now Index / leaderboard of worst CVEs) and a specific verb (Get), then immediately bounds the scope to published-or-escalated CVEs across defined windows. It goes further than any sibling tool would by defining what the ranking means, so an agent can tell it apart from get_vulnerability or search without opening a schema.

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?

It gives explicit usage conditions and mutual exclusions: narrow with tech, ecosystem and filter; conversely, pass week 'instead, without tech, ecosystem or filter' for an archived week's top 25. The two modes and the rule that selects between them are stated outright, leaving nothing to inference.

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