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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the safety profile is covered. The description adds value beyond that by disclosing what the tool returns: column types, notes on non-obvious columns, and known data caveats. With no output schema present, this behavioral detail is meaningful.

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?

Two sentences with no filler. The first sentence states the core purpose and output contents, and the second sentence provides usage timing. Every word 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?

For a single-parameter read-only tool with rich annotations, the description covers what the tool returns, why it exists, and when to call it. The sibling tools are clearly different in purpose, and nothing essential is missing for correct selection and invocation.

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%, and the parameter description already gives the table name plus an example. The tool description does not add further parameter semantics, but it does not need to; the baseline of 3 applies because the schema carries the burden.

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 clear verb–resource pair: it returns the columns of one table with their ClickHouse types, plus notes and data caveats. It also distinguishes itself from siblings by scoping to a single table, unlike list_tables which presumably enumerates tables, and unlike run_sql which executes queries.

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 second sentence gives explicit guidance: 'Call before writing SQL against a table.' This tells the agent when to use the tool. It does not explicitly name alternatives or exclusions, so it falls just short of a top score, but the timing rule is concrete and actionable.

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