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

Annotations already declare readOnlyHint and idempotentHint, so safety is covered. The description usefully adds that the output is a paste-ready response targeted at OneTrust, Whistic, or client emails, but it says nothing about sourcing, citation behavior, latency, or coverage limits for the legal grounding it claims.

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, zero filler: the purpose and the return-value framing are both front-loaded. Nothing in the text is redundant with the schema or annotations.

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 a 2-param schema fully documented, read-only annotations, and an output schema handling return values, the description only needs to establish purpose and framing, which it does. It could be stronger by noting the legal-domain boundaries or how answers are grounded, but nothing essential for invocation is missing.

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 both parameters (question, company_name) are fully documented with examples and defaults in the schema. The description adds no extra parameter semantics, so the baseline of 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 uses a specific verb+resource ('answer... procurement, security questionnaire, or RFP question') scoped to EU AI Act, GDPR, and data sovereignty, which is clear on its own. It does not explicitly differentiate itself from the sibling regulation_lookup, which an agent might reasonably confuse with this domain-specific answering tool.

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?

Usage is only implied: the agent must infer that this is the tool for answering third-party procurement/security questions rather than looking up regulations. There is no explicit when-to-use/when-not guidance and no mention of when regulation_lookup or list_regulations would be the better choice.

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