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

With no annotations provided, the description carries the full burden of explaining behavior. It states only that the tool yields the mean of a population, which is minimal. It does not disclose input source, return format, side effects, or any assumptions about the data, so an agent has little understanding of what happens at invocation.

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 short but not meaningfully concise; it repeats the tool name in the form of a definition ('Mean of population'). Under-specification masks potentially useful details about what data is used and what the tool returns.

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 zero-parameter tool with no output schema and no annotations, the description should clearly state what the tool computes and what the agent receives. The phrase 'Mean of population' is too thin to fully explain invocation, expected inputs (if any via context), or return value, and it does not distinguish the tool from nearby statistical siblings.

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 input schema declares zero parameters and schema description coverage is 100%, so there are no parameter semantics for the description to clarify. Per the baseline for a zero-parameter tool, this is acceptable and needs no additional explanation.

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 'Population Mean: Mean of population' is essentially a tautology that restates the tool's name. It conveys that the tool relates to a population mean but lacks a clear verb, resource, or differentiating detail. While not misleading, it does not meaningfully clarify what the tool computes beyond its own title.

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 no guidance on when to use this tool versus its many statistical siblings such as population-stddev, population-variance, sample-mean, geometric-mean, or weighted-mean. No conditions, exclusions, or alternative tools are mentioned, leaving selection entirely to inference from the name.

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