Get RBA Table

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the base transparency is high. The description adds 'normalised response shape', which offers some insight into output format but does not reveal behavioral traits like error handling or default behavior. No contradiction with 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?

The description is a single sentence with no wasted words. It is front-loaded but uses jargon ('Expert/source-native', 'normalised') which may reduce clarity. Could be more straightforward.

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 tool has 6 parameters, an output schema, and is used for retrieving statistical tables, the description is too sparse. It lacks explanation of pagination, error handling, or typical use cases. The annotation-rich structure mitigates some gaps, but completeness is low.

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% with detailed descriptions for all 6 parameters. The description adds no additional meaning beyond what the schema provides (e.g., 'table_id' is described as non-empty dataset or table id). Baseline 3 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 uses 'retrieval' as the verb and specifies 'RBA statistical table' as the resource, clearly indicating the tool's function. It distinguishes from siblings like 'list_rba_tables' (list vs get) and 'get_abs_data' (different source). The phrase 'normalised response shape' hints at output structure, but the purpose is clear.

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?

No explicit guidance on when to use this tool versus alternatives like 'list_rba_tables' for discovery or other statistical retrieval tools. No exclusions or context are provided. The term 'Expert/source-native' implies specialized use but lacks clarity.

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