stats_stats_outliers

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

No annotations are provided, so the description must carry the full behavioral transparency burden. It does not disclose whether the tool is read-only, destructive, requires authorization, or how it handles invalid inputs. It only states the methods, lacking important behavioral context.

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 extremely concise with two sentences, no redundant information. It is front-loaded with purpose and methods, efficiently using words.

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 there are three parameters and an output schema exists (but is not shown), the description does not explain the return format, edge cases, or interpretation of results. It lacks completeness for a statistical tool that may have complex outputs.

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?

The input schema has 0% description coverage, so the description must compensate. It adds meaning for 'method' and 'threshold' by explaining their roles, but does not explain the 'values' parameter or default behaviors. Partial improvement over raw schema, but not comprehensive.

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 verb 'detect' and the resource 'outliers', and distinguishes from other stats tools by specifying outlier detection. It also mentions two distinct methods, making the purpose specific and clear.

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 explains the two methods (IQR and zscore) and their thresholds, but does not provide guidance on when to use which method or when to avoid using this tool. No explicit alternatives or when-not-to-use information is given.

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