mean

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

With no annotations provided, the description carries the full burden. It discloses key behaviors: returns a dict with result or error, raises ValueError on an empty list, and logs the operation. These are genuinely useful behavioral details beyond the schema.

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 clear sections for Args, Returns, Raises, and Notes. It is compact and front-loaded with the purpose. The only minor redundancy is the Args line, which repeats schema information, but overall it is concise and readable.

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?

The tool is simple with one parameter and an output schema, so the description does not need to explain return values in depth. It covers the main error condition, the return shape, and the logging side-effect, making it complete enough for an agent to invoke the tool correctly. It lacks deeper statistical caveats, but they are not essential here.

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 description coverage is 0%, so the description should compensate, but the Args section merely restates what the schema already shows: data is an object containing a list of numbers. It does not add parameter-level meaning such as supported numeric types, formatting constraints, or edge-case handling beyond the empty-list note.

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 operation: 'Calculate the mean (average) of a list of numbers.' This clearly distinguishes it from statistical siblings like median and standard_deviation, and the formula note reinforces the exact meaning.

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 when to use the tool by defining mean and the operation, but it does not explicitly contrast it with alternatives like median or standard_deviation. For a simple arithmetic/statistical tool, the intended usage is reasonably clear, yet no direct guidance or exclusion is provided.

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