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

With no meaningful annotation coverage, the description carries the burden and does so well: it notes the tool returns a session ID and profiling questionnaire, positions itself as a discovery/start operation, and includes the cautions 'Informational only' and 'presents a framework, not advice'. It could still be clearer about whether any organisation data is persisted beyond the session, but it is largely transparent.

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?

The description is dense but not bloated. Every sentence contributes: what it does, what legislation it covers, when to use it, what it returns, and the advisory disclaimer. It is a little long, but the length is justified by the legal scope and use-case guidance.

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?

Without an output schema, the description correctly explains the return value (session ID and profiling questionnaire) and the factors that affect the framework. It does not explicitly mention the likely follow-up steps or sibling tools, but the return value makes the 'start' nature clear enough for safe invocation.

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 has zero parameters and 100% schema coverage, so there is nothing for the description to add about parameters. It instead explains how the no-input operation is shaped by the organisation's context once the questionnaire begins, which 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 names a specific action ('identifies' and 'builds'), a precise resource ('Australian AI governance framework'), and a clear subject ('a specific organisation's use of AI'). It also differentiates itself from siblings by framing this as the starting step that returns a session ID and profiling questionnaire, unlike get/submit tools.

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?

Explicitly states when to use this tool: when an Australian business asks what AI governance it needs, what rules apply, or for a governance framework/policy structure. It does not provide explicit when-not-to-use guidance, nor does it name sibling alternatives, so it misses the top tier.

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