Get table statistics

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds transparency by disclosing that disk size requires the MONITORING privilege, which is important for permission planning, and by naming the exact system views queried. It does not contradict 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?

One sentence front-loads the action and return value list, then adds the privilege caveat. No unnecessary words or redundancy.

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?

The description covers purpose, key outputs, source views, and a privilege caveat, which is adequate for a simple read-only stats tool. It does not mention behavior for missing tables or schema handling, but the schema already documents the default, and annotations cover safety. Slightly more detail about output shape would be helpful, but it is not essential.

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?

The input schema already provides descriptions for both parameters, including the default for schema_name, so the description adds no additional parameter semantics. With 100% schema coverage, the baseline score of 3 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 ('Return') and clearly enumerates the exact outputs (row count, table type, column-store flag, primary key flag, disk size). It distinguishes this tool from sibling tools like hana_get_column_stats by focusing on table-level statistics and naming the source system views.

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 clearly implies when to use this tool: when table-level statistics are needed, including disk size. It does not explicitly exclude alternatives or name sibling tools, but the 'table stats' versus 'column stats' distinction is implicit. There is no misleading guidance.

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