percentile

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

With no annotations, the description carries the full burden, but it only mentions 'calculate' without disclosing return type, edge-case handling (e.g., empty data, interpolation method), or side-effect profile. This significant gap leaves the agent without critical 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 a single, focused sentence beginning with the action verb. It contains no redundant information and is well-structured for quick parsing.

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?

Although the tool is simple and an output schema exists, the description lacks essential context: no usage guidance, no differentiation from sibling statistical tools, and no behavioral disclosure. This minimal description is insufficient for an agent to correctly select and invoke the tool within the suite.

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 adds minimal semantic value by mapping 'dataset' to data and 'percentile' to the percentile parameter, but it does not explain data format, percentile interpretation, or constraints beyond the schema. It fails to compensate for the lack of schema 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 clearly states the tool calculates a specific percentile of a dataset, using a specific verb and resource. It even specifies the 0-100 range, but does not explicitly differentiate it from sibling tools like stats_summary or statistics_analysis, so it lacks sibling differentiation.

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 guidance on when to use this tool versus alternatives. It only defines what the tool does, with no context about overlapping sibling tools or when a percentile calculation is appropriate.

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