distribution_operation

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

No annotations are provided, so the description carries full burden for disclosing behavioral traits. It merely lists operations without mentioning side effects, session requirements, or output behavior. There is no statement about whether this is a read-only computation or if it modifies any state.

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 sentence that front-loads the core purpose and lists all supported operations. There is no wasted wording, and it is easily skimmable for an agent.

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?

Given that an output schema exists and the input schema fully documents all parameters (including distribution names and operation values), the description is mostly complete for tool selection and invocation. It lacks explicit mention of how to combine operations with parameters, but the schema covers this. Minor ambiguity around 'quantile' (needs probability vs x) is acceptable.

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 does not add additional meaning beyond the schema; it restates operation names that are already enumerated in the operation parameter. It does not clarify relationships like x being needed for pdf/cdf/quantile and n for sampling, but the schema descriptions already cover these roles.

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 identifies the tool as handling probability distribution operations, listing specific operations (PDF, CDF, quantile, mean, variance, sampling). This distinguishes it from sibling tools that focus on algebra, calculus, or other math domains. However, it lacks a strong verb like 'compute' or 'evaluate', instead using the nominal 'operations'.

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 explicit guidance on when to use this tool versus alternatives like statistics_summary or calculate_expression. It lists the operations but does not give context about which distribution or scenario warrants this tool. Usage is only implied by the tool's name and sibling context.

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