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

No annotations are present, so the description must fully disclose behavior. Instead it contradicts the schema by referencing two integers and leaves 'discarded' unexplained, with no mention of return values, side effects, or which inputs are actually used.

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 text is very short, but it is under-specified rather than concisely informative. The sentence is internally inconsistent and contains no front-loaded verb, scope, or operational detail that earns its place.

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 nine-parameter tool with no annotations and no output schema, the description needs to explain what happens with the inputs and what the call returns. It does neither and misleads the agent, leaving the tool effectively uncallable from the definition alone.

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 itself documents all nine parameters well, but the description references 'two integers' that do not exist in the schema and provides no mapping to any string parameter. This active confusion outweighs the high schema coverage and makes the description unhelpful for parameter handling.

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 claims the tool computes the LCM of two integers, but the input schema accepts nine string properties and has no numeric parameters. The phrase 'numbers discarded' is self-contradictory, so an agent cannot determine what the tool actually does or how it differs from siblings like calc-eval.

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?

There is no statement of when to use lcm-ok versus any alternative tool. No context, conditions, or exclusions are provided, and the one-line description gives no actionable selection guidance.

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