check_outliers

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It fully explains the methods, the output (counts, sample extreme values, row indices per method), the verbose flag's effect on response size, and the artifact behavior. This goes beyond basic transparency and covers the tool's operational nuances extensively.

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 two paragraphs, but every sentence adds value: method list, output summary, diagnostic note, verbose behavior, and artifact. It is front-loaded with the core purpose and maintains a logical flow. Slightly dense but appropriately sized for the tool's complexity.

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 description covers the tool's purpose, methods, output, and verbosity behavior, but omits details on the `columns` and `max_per_method` parameters and their interplay with default behavior. Given the existence of an output schema, return values are partially explained, but the parameter gaps keep it from being fully complete. Still, it provides substantial context for a complex 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 description coverage is 0%, so the description must compensate. It thoroughly explains `verbose` but leaves `columns`, `source_id`, and `max_per_method` without explicit semantic context. The `top_findings` mention indirectly relates to limits but does not clearly map to `max_per_method`. The description falls short of documenting all parameters given the lack of schema-level descriptions.

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 starts with a specific verb+resource: 'Detect outliers in numeric columns using three methods side-by-side.' It names the exact methods (z-score, IQR, modified z-score) which clearly distinguishes it from sibling tools like check_quality or check_distributions. The purpose is unambiguous and detailed.

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 clearly indicates the tool is for outlier detection in numeric columns and even hints at how to interpret disagreements ('Disagreement between methods is itself diagnostic'). It does not explicitly name alternative tools or provide exclusion criteria, but the context is strong enough for an agent to decide when to use it. It lacks explicit when-not-to-use guidance.

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