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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description still adds context beyond them: the fixed 60-day expiry horizon and the fact that the call is "Free" (no credit cost), which is a real behavioral trait an agent cannot infer from structured fields.

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 sentences, front-loaded with the policy report and then the training report, and no filler. The semicolon-chained clause structure is dense and takes a moment to parse, which costs it the top score.

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 no output schema, the description carries the return-value burden and does so: it enumerates the exact buckets reported (confirmed, link waiting, never sent; valid, none, expiring in 60 days). The one gap is not stating what an argument-free call returns, which matters given zero required parameters.

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 50%: `name` is documented in the schema ("Like ai-use-policy") and `training_kind` is a five-value enum. The description's "per kind of training (or one kind)" usefully conveys that training_kind is an optional narrowing filter, but it adds nothing about `name` or about the default scope when both params are omitted. 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?

The description states a specific read/report capability: per-policy confirmation status (confirmed / link pending / never sent) and per-training-kind validity plus 60-day expiry. It is clearly a status report rather than a mutation, which distinguishes it from hr_save_policy, hr_send_policy and hr_record_training, though it never names those siblings explicitly.

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?

"For audits and AI literacy (EU AI Act Art. 4)" gives one concrete use case, which is more than most tools here. But there is no when-not guidance and no pointer to the closest alternative (hr_report, hr_tasks), so an agent must infer the boundary itself.

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