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

Annotations already cover the safety profile (read-only, idempotent, non-destructive, closed-world), and the description adds genuinely useful context beyond them: results are computed live, the exact output components are enumerated (rho, repeat/first-time split, top-20 concentration share, interpretation sentence), and it flags that the metric is a proxy rather than exploit-timing proof. Authentication state ('public read, no auth') is also stated, which annotations do not express.

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?

Purpose is front-loaded in the first sentence, then mechanics, then the decision framing. Slightly redundant: the 'chase the chronic offenders, or watch for newcomers' question partly repeats the opening stickiness question, and the ALL-CAPS emphasis adds length without information.

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-optional-parameter tool with no output schema, the description carries the right load by enumerating return components and disclaiming interpretation. The only gap is that it never indicates how to read rho direction or magnitude, relying entirely on the returned `interpretation` sentence.

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 coverage is 100%, so the single `days` parameter, its 30-720 bounds and its default are already documented in the schema. The description restates the range and default and clarifies that the window defines which additions count as 'recent', but adds no guidance on how window length shifts the rho result. 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?

States a specific analytical operation: it correlates each product's historical KEV count against recent KEV additions via Spearman rho and splits repeat-offenders from first-time products. The verb+resource is concrete and product-level scope is explicit. It loses a point for never naming the closest sibling, kev-vendor-risk, so the agent must infer the vendor-vs-product distinction itself.

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?

Frames the decision it informs ('chase the chronic offenders, or watch for newcomers') and discloses the caveat that this is a proxy for exploitation dynamics, not proof of exploit timing. However, it gives no explicit when-to-use-this-instead-of guidance relative to kev-vendor-risk, and no exclusion conditions, leaving the sibling choice to inference.

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