Table Row Counts

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 states the operation, default target scope, and a cap. This gives useful transparency, though the exact meaning of 'capped' is left vague.

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, front-loaded sentence with no filler. Every word contributes meaning.

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 core behavior is clear enough for a simple two-parameter tool with an output schema, but the connection parameter is entirely undocumented and the cap is unspecified. Missing these details leaves the agent with ambiguity about scope and limits.

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 must compensate for both parameters. It says 'all user tables by default,' which hints at the optional table_names behavior, but it does not explicitly explain table_names or connection at all. This is a significant gap.

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 verb and resource: return COUNT(*) for each table. It also clarifies the default scope (all user tables) and the cap, which distinguishes it from sibling tools like execute_query and describe_table.

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 purpose implies when to use this tool, but there is no explicit guidance about when not to use it or which sibling to prefer. Given the set of table inspection tools, the description does not help an agent route between them beyond the obvious row-count intent.

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