list_tables

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

Since no annotations are provided, the description carries the full burden. It details the return format (tables list, total_count, echo) and notes parameter sources. It does not explicitly state read-only, but it is implied by 'List tables'. Good for a listing operation.

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 well-structured with a clear purpose sentence and separate Args/Returns sections. It is informative without being verbose, though minor trimming could make it more concise.

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 existence of an output schema covering return values, the description is complete for a list tool. It covers purpose, parameter sources, and return format. Could mention pagination or limits, but 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?

Schema coverage is 0% with no parameter descriptions. The description compensates by providing examples for catalog_name and noting that schema_name and engine_id come from other tool outputs, adding significant meaning beyond the 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 purpose is clearly stated: 'List tables in a watsonx.data schema.' The verb 'list' and resource 'tables' are specific, and the scope 'in a schema' distinguishes it from siblings like describe_table and list_schemas.

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 provides usage context by noting that schema_name comes from list_schemas and engine_id from list_engines, implying a workflow. However, it does not explicitly state when not to use or suggest alternatives.

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