lom_enums

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

With no annotations provided, the description must carry the behavioral disclosure burden. It clearly signals a read-only query operation and describes the return shape and the effect of omitting type_name. It does not discuss invalid input behavior, but that is a minor gap for a simple query tool.

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 compact and well-structured: a one-sentence summary followed by Args and Returns sections. Every sentence adds useful information with no redundancy or filler.

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?

For a single-optional-parameter query tool with an output schema, the description is complete. It covers the parameter semantics, the default behavior, and the return type. Nothing critical for correct invocation is missing.

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 schema only provides a defaulted string parameter with no description. The tool description fully compensates by explaining the dotted enum name format, giving a concrete example ('Song.Quantization'), and stating the behavior when omitted. This is exactly what an agent needs to invoke it correctly.

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 ('Query') and resource ('Live enum types'), and mentions the returned data ('member names and integer values'). It is clear about what the tool does, though it does not explicitly differentiate itself from sibling tools like lom_describe.

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 parameter-level guidance ('Omit to list enum types') and the purpose implies use when enum information is needed. However, it does not explicitly state when to prefer this tool over alternatives such as lom_describe or lom_get, leaving tool-selection comparisons implicit.

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