list_engines

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

No annotations are provided, so the description carries the full burden. It discloses the return structure (engines list and summary) but does not mention side effects, authorization, rate limits, or performance characteristics. It does not contradict structured data but lacks behavioral 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 structured as a short paragraph with args and returns sections. It is front-loaded and each sentence adds value. Slightly verbose but clear and efficient.

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 single optional parameter and presence of output schema (though described in text), the description covers the tool's purpose and return format. It lacks mention of paging or instance scope, but is complete for a straightforward list tool.

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%, but the description compensates well by explaining the parameter engine_type with specific values ('presto', 'prestissimo', 'spark', or None) and its effect. Also documents the return structure, adding value beyond the minimal 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 clearly states it lists available Presto, Prestissimo, and Spark compute engines in watsonx.data. It uses specific verbs and resources ('List available ... engines') and distinguishes from sibling tools that create, pause, or scale engines.

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 usage by showing an optional filter but does not explicitly state when to use this tool versus alternatives like list_schemas or list_tables. No when-not-to-use or alternative suggestions are provided.

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