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

Annotations already declare readOnlyHint and closed-world, so the safety profile is covered. The description adds real value beyond them: a severity model (in-force-without-evidence = critical, due within 180 days = medium) and the precondition that an organization API key is required.

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; the finding categories follow the purpose rather than preceding it. It is dense and slightly run-on but every clause carries information an agent would otherwise have to guess.

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?

No output schema exists, so the description carries the return-value burden, and it does so by enumerating the six finding classes and their severity mapping. It stops short of saying whether results are counts, a verdict, or per-system entries, which is a modest remaining gap.

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?

The tool takes zero parameters, so the baseline is 4. The only parameter-adjacent information worth having — the organization API key requirement — is stated, which is more than the empty schema conveys.

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-scope ('compliance check') plus the exact finding categories returned (prohibited practices, Article 5 screens, in-force obligations, upcoming high-risk duties, stale-logged systems). This clearly separates it from sibling mutations like ai_act_system_save and from ai_act_export, though no sibling is named 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?

'What a customer's due-diligence or a regulator would flag today' implies the audit use case, but there is no explicit when-to-use vs when-to-use-instead guidance against ai_act_register, ai_act_export, or gov_ai_inventory_check. Usage is inferred, not stated.

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