distribution_operation

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

With no annotations provided, the description must disclose behavioral traits, but it only enumerates operation names. It does not mention what outputs look like (e.g., numeric, array), edge cases (e.g., invalid parameters), or how operations differ in behavior (e.g., sampling requires n, pdf requires x). The list of operations is a starting point but lacks 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 a single, concise phrase that front-loads the topic and lists operations via a colon. It wastes no words, but it is a fragment rather than a full sentence and could be slightly more structured (e.g., 'Computes the PDF, CDF, ... of probability distributions'). Still, it is appropriately sized for a tool with a rich schema.

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 has 5 parameters and supports 6 distinct operations with different parameter requirements (e.g., sample needs n, pdf needs x). The description does not explain these dependencies or how the operation field selects behavior. Even with an output schema present, the tool's complexity demands more guidance than a list of operation names, making it incomplete.

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 100%, so the baseline is 3. The description adds no parameter meaning beyond the operation list, but it doesn't mislead. It does not clarify which parameters apply to which operations, but the schema already documents each parameter, so the description is not required to compensate heavily.

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 the domain and operations: 'Probability distribution operations: PDF, CDF, quantile, mean, variance, sampling'. It identifies the resource (probability distributions) and lists specific operations, distinguishing it from matrix, ODE, and other math tools. However, it lacks a specific verb (e.g., 'Computes') and could be more explicit about being a computational tool.

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 alternatives like statistics_summary, which likely handles descriptive statistics on data. There is no explicit 'use this for' or 'not for' statement, leaving the agent to infer usage from the operation list alone.

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