base_tableUsage

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

Annotations already provide readOnlyHint=true and idempotentHint=true, so the description doesn't need to repeat safety. It adds behavioral context about output: 'showing which objects are most actively queried and by whom' and explains the persist parameter behavior. This adds value beyond 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 concise and well-structured: purpose sentence, usage guidelines, alternative, then parameter list. No fluff, every sentence earns its place.

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?

Despite no output schema, the description hints at the output format ('showing which objects...' and 'returns table name' for persist). It is fairly complete for a tool with clear annotations and parameters, though more detail on the output structure would help.

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 description coverage is 100%, so the schema already documents both parameters. The description repeats the parameter descriptions verbatim without adding new meaning beyond the schema, so baseline of 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?

Description starts with a specific verb+resource: 'Report access frequency and per-user query patterns for tables and views in a Teradata database'. It clearly states what the tool does and distinguishes itself from sibling base_tableAffinity by explicitly mentioning that alternative.

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: 'Use when the user asks how often tables are accessed, which tables are most popular, or which users are running queries against a database.' Also provides an explicit alternative: 'For discovering which tables appear together in the same queries, use base_tableAffinity instead.'

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