distribution

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

No annotations are provided, and the description does not disclose whether operations are read-only, modify state, or have side effects. The phrase 'evaluate, fit, and sample' suggests primarily read operations, but fitting may involve computation without persistence—uncertain.

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 sentence, which is concise but sacrifices critical details. It front-loads the main purpose but lacks structure and completeness.

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?

With 7 parameters (2 required) and no parameter explanations, the description is inadequate. An output schema exists but is not described. The tool's complexity demands more detailed usage guidance.

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%, and the description does not explain any of the 7 parameters (name, operation, params, x, q, size, random_state). The agent must infer meaning from names alone, which is insufficient for correct invocation.

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 'evaluate, fit, and sample probability distributions', which clearly identifies the tool's domain and actions. However, it lacks specificity to distinguish from the sibling 'random_sample' tool, which also involves sampling distributions.

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?

No guidance is provided on when to use this tool versus alternatives like 'random_sample' or 'hypothesis_test'. The description does not mention prerequisites or exclusions.

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