Top Hot Tables

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

With no annotations, the description carries the full burden of behavioral disclosurecars. It only mentions the ordering basis (audit-log visit count) and does not state whether the operation is read-only, what the return shape is, whether there are limits or pagination effects, or how the time-range parameters interact. These omissions are significant for a tool with no annotation safety hints.

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, front-loaded sentence with no wasted words or repetitive phrasing. It is efficient, though it is under-specified rather than economically complete, which prevents a perfect score.

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?

For a tool with no annotations, no output schema, and five optional parameters, the description is too sparse. It omits the return shape, default and cap behavior, time-range coupling, and any guidance on when to choose this tool over siblings. The rich input schema covers parameters, but it cannot compensate for the missing usage and output context.

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 each parameter is individually described with defaults, filtering semantics, and constraints. The description adds only the audit-log context, but it does not need to repeat parameter details because the schema already carries that information, so the 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 states a specific verb ('Get'), a resource ('top hot tables'), and an ordering criterion ('by audit-log visit count'), making the primary purpose clear. It does not explicitly name or differentiate sibling tools like top_bad_tables, but the 'hot' versus 'bad' distinction is inferable from the descriptions and names.

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?

There is no guidance on when to use this tool versus alternatives such as top_bad_tables, analyze_slow_queries_topn, or read_query. The description only states what the tool does, leaving an agent to infer when it should be selected.

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