Scientific Calculator

Percentile Calculator

calculator_percentile

Read-only

Percentile via nearest-rank method. percentile in [0, 100].

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "data": "<data>",
      "percentile": "<percentile>"
    },
    "name": "calculator_percentile"
  }
}

Input Schema

Name	Required	Description	Default
`data`	Yes	Non-empty list of numbers.
`percentile`	Yes	Percentile 0–100.

Output Schema

Name	Required	Description	Default
`result`	Yes
`expression`	Yes
`percentile`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A3.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and destructiveHint=false, so safety is covered. The description adds genuinely useful behavior: the nearest-rank method, which determines exactly how results are computed (no interpolation) and is the key trait distinguishing output values.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two terse sentences, method first then constraint, with zero waste. Front-loading the algorithm is the right priority for a computational tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Output schema exists, so return values needn't be explained. But for a stats tool with many overlapping siblings (median, quartile, rank), the description leaves the selection decision entirely to the agent and says nothing about behavior on unsorted or non-numeric input.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents 'data' as a non-empty list of numbers and 'percentile' as 0–100. The description repeats the percentile range, adding no syntax or edge-case detail beyond what's structured.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Percentile') and specifies the algorithm ('nearest-rank method'), which meaningfully differentiates it from interpolating percentile implementations. However, it doesn't distinguish itself from near siblings like calculator_quartile, calculator_median, or calculator_rank by name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this versus calculator_quartile, calculator_median, or calculator_rank, all of which overlap statistically. The agent must infer selection criteria from tool names alone.

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

All Scientific Calculator tools Inspect

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