table_statistics

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

With no annotations, the description carries the burden and it does disclose a meaningful behavioral trait: it avoids reading business rows, implying a safe, cheap metadata operation. It does not mention whether any side effects occur (e.g., computing/refreshing statistics) or what the response contains, but that is partially covered by the output schema.

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?

A single front-loaded sentence with no filler; every clause earns its place by conveying scope ('lightweight') and a key constraint ('without reading business rows').

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 simple three-string-parameter tool, the description plus the presence of an output schema covers the basics: what it returns is not needed in prose. However, it lacks guidance on how source/schema/table are resolved and how this tool differs from describe_table, so an agent must infer some 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 description coverage is 0%, so the description should compensate by explaining source, schema, and table semantics, but it does not. The parameter names are reasonably self-explanatory, yet the description adds no meaning beyond the input schema.

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 action ('Return') and resource ('lightweight table statistics'), and the qualifier 'without reading business rows' gives a clear sense of scope, distinguishing it from row-reading data tools. It does not, however, explicitly differentiate it from describe_table, which is likely its closest sibling.

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 phrasing 'lightweight ... without reading business rows' implies this is appropriate when a quick, non-data-intensive statistics check is needed, which is a contextual usage signal. It does not explicitly name alternatives or say when not to use it, so the guidance remains implied rather than explicit.

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