Describe Dataset

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

Annotations already declare readOnly, destructive, idempotent, and openWorld hints. The description adds key behavioral context: the output includes native IDs ('without hiding native IDs'), which is not conveyed by annotations.

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 sentence that is front-loaded with the core action and resource. Every word serves a purpose, with no redundancy or filler.

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?

Given the high schema coverage and presence of an output schema, the description covers the essential purpose. However, it does not elaborate on the content of the description (e.g., metadata fields), which could be helpful given the number of sibling tools.

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 100% and the schema descriptions are detailed. The tool description does not add any parameter-specific information beyond what the schema already provides, so baseline score 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 'Describe' and a clear resource 'source-native ABS, RBA, or APRA dataset'. It distinguishes from siblings like 'get_abs_data' by focusing on description rather than data retrieval, and adds nuance with 'without hiding native IDs'.

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 implies usage for describing datasets from ABS, RBA, or APRA, and contrasts with data-retrieval siblings. However, it lacks explicit guidance on when not to use it or comparisons with similar description tools.

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