table_statistics

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

With no annotations, the description carries the burden of behavioral disclosure. It reveals that the tool does not scan business rows, implying efficiency and perhaps approximate or metadata-based statistics. However, it does not mention whether the statistics are up-to-date, if permissions are required, or what happens when statistics are unavailable. The description offers one useful behavioral trait but lacks depth.

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, well-structured sentence that immediately states the purpose and the key differentiator. There is no fluff, and the most important information is front-loaded. Every word contributes to the tool's understanding.

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?

Given the tool's simplicity (three obvious parameters) and the presence of an output schema that likely details the returned statistics, the description is adequate but minimal. It does not mention potential caveats like staleness or permissions, but for a simple statistics tool, the coverage is sufficient, though not comprehensive.

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%, and the description provides no additional meaning for the three parameters (source, schema, table). While the names are self-explanatory, the description does not clarify any constraints, defaults, or format expectations, leaving the agent to infer everything from the parameter names alone.

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 clearly states the verb 'return' and the resource 'table statistics', and the qualifier 'without scanning business rows' differentiates it from heavier operations like full scans. This effectively distinguishes it from sibling tools like get_table_metadata or describe_table, which likely involve more detailed metadata or schema inspection.

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 implies a lightweight, non-scanning use case, but it does not explicitly state when to prefer this tool over alternatives like get_table_metadata or describe_table, nor does it mention any exclusions. The 'lightweight' and 'without scanning' hints provide context but fall short of explicit guidance.

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