Compute percentiles for numeric datasets (default p5–p99) and optionally find the percentile rank of a given value.
Compute percentiles of a dataset (default p5-p99) and optionally find the percentile rank of a given value.
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | Numeric data array | |
| value | No | Optional value to find its percentile rank | |
| percentiles | No | Percentiles to compute (default [5,10,25,50,75,90,95,99]) |
Changes observed during successful MCP inspections.
v0.1.11Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish that this is a read-only, idempotent, non-destructive operation. The description adds useful behavioral details about the default percentile set and optional percentile-rank mode, but it does not describe the response shape or clarify how the two modes are returned.
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 front-loaded sentence with no wasted text. The parenthetical default and optional rank clause both contribute directly to understanding the call.
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?
For a simple calculation tool with rich annotations and full schema coverage, this is adequate to invoke correctly. However, because there is no output schema, the description should ideally specify the return structure, especially how computed percentiles and the optional percentile rank are presented.
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 100%, so all three parameters are already documented. The description adds only a shorthand default note, 'p5-p99', which is actually less precise than the schema's explicit default list [5,10,25,50,75,90,95,99].
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 uses a specific verb and resource: compute percentiles of a dataset, with an optional percentile-rank lookup. That is clear, but it does not distinguish this tool from nearby math/statistics siblings such as descriptive_stats or statistics_calc.
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?
There is no guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The optional value parameter is described, but usage is left implicit rather than directed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.