list_tables

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

Annotations already declare the tool to be read-only, idempotent, and non-destructive. The description adds the useful scope constraint 'queryable' and lists the return fields, but does not disclose additional behavioral details such as pagination or ordering. This is acceptable given the strong annotation coverage.

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, well-structured sentence that front-loads the action and resource, then appends the exact returned fields. No filler or redundant wording.

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 tool is simple, has no parameters, strong annotations, and an output schema. The description fully conveys the purpose, scope, and returned information, so an agent can confidently invoke it for table discovery.

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 tool has zero parameters, so the schema covers all parameter semantics by definition. The description still adds value by clarifying what 'all' means in the output scope.

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 ('List'), a clear resource ('all queryable tables and views'), and the exact metadata returned ('source file, kind and row count'). It clearly distinguishes this discovery tool from siblings like describe_table or query.

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 context is clearly implied: use this tool to enumerate available tables and views before drilling into details. However, it does not explicitly mention when not to use it or name alternatives such as search_columns or describe_table.

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