check_distributions

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

No annotations are provided, so the description carries the burden. It discloses several behavioral traits: flags specific distribution issues, suggests transforms, and notes 'Output size: small'. This gives a clear sense of behavior and non-destructiveness, though it does not explicitly state that no data is modified or describe edge cases.

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 three concise sentences, front-loaded with the core purpose, followed by specific checks and a note on output size. Every sentence adds value with no redundancy or fluff.

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 the output schema exists, the description need not explain return values. It adequately covers what the tool does, the nature of checks, and output size. However, it lacks usage guidance and parameter semantics, leaving the agent to infer some context, so it is slightly incomplete for a complex analytical tool.

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 coverage is 0% and the description does not elaborate on parameters. It mentions 'numeric column', which is a useful hint for `columns`, but does not explain that `columns` is optional and null means all numeric columns. `source_id` is left entirely to the schema's title, offering no additional semantics.

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 specifies the tool's function: 'Distribution shape per numeric column' with concrete checks (heavy skew, multimodality, zero-inflation, heavy tails) and suggested transforms. This distinguishes it from sibling tools like `check_outliers` or `plot_distribution`, which focus on different aspects.

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 includes 'Level 1', implying it is an initial exploratory check, but it does not explicitly state when to use it instead of alternatives such as `profile`, `describe_source`, or `plot_distribution`. No exclusions or alternative tool references are provided.

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