get_sector_benchmark

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

Although no annotations are provided, the description discloses that this is a read operation (Get), explains what the tool returns, and notes the data source. It does not explicitly state side effects (likely none), but for a simple retrieval tool this level of detail is sufficient for an agent to understand behavior.

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 consists of two efficient sentences: the first states the core purpose, and the second enumerates the return values and data recency. Every word adds value without redundancy, making it easy for an agent to parse quickly.

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 compensates by listing return fields. It covers the important aspects (scores, rank, averages, evidence source). It could mention response format or error handling, but for a single-parameter retrieval tool the information is largely complete.

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 only parameter 'sector' has full schema coverage (100%) with its allowed values enumerated in the schema description. The tool description adds no additional meaning beyond referencing 'a specific sector', so it meets the baseline but provides no extra semantic help.

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 clearly states the tool retrieves the AU AI Maturity Index benchmark score for a specific sector, lists the exact return values (overall score, dimension scores, rank, national averages), and specifies the evidence base (Q2 2026). This distinguishes it from siblings focused on patterns, incidents, or regulatory changes.

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?

The description implicitly indicates usage for benchmarking a sector, and the sibling tools cover distinct areas (patterns, incidents, regulatory changes), so an agent can infer when to use this tool. However, there is no explicit guidance on when not to use it or alternative tools, preventing a perfect score.

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