Scientific Calculator

Regression Calculator

calculator_regression

Read-only

Linear or quadratic least-squares regression with R² and optional prediction.

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": {
      "x": "<x>",
      "y": "<y>"
    },
    "name": "calculator_regression"
  }
}

Input Schema

Name	Required	Description	Default
`x`	Yes	X data.
`y`	Yes	Y data.
`type`	No	linear or quadratic.	linear
`predict_x`	No	Optional X to predict.

Output Schema

Name	Required	Description	Default
`equation`	Yes
`r_squared`	No
`expression`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

B3.4/5.0

Behavior3/5

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

Annotations already declare this as a safe, read-only, closed-world operation, so the safety profile is covered. The description adds useful feature context, R² and optional prediction, but omits behavioral constraints such as requiring x and y to be paired arrays of equal length or minimum data points for quadratic regression.

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?

It is a single front-loaded sentence with no filler. The method, output metric, and optional prediction capability are all stated efficiently.

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

Completeness4/5

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

Given the output schema and full schema parameter descriptions, the description covers the core purpose and capabilities adequately. It could be more complete by mentioning input-pairing constraints or quadratic sample-size requirements, but those are the only notable gaps.

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 description coverage is 100%, so the schema already documents all parameters and their defaults. The description only restates the model type choices and optional prediction without adding format or constraint details beyond the schema.

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?

The description states a specific computation: linear or quadratic least-squares regression, including R² and optional prediction. It is clear what the tool does, but it does not explicitly differentiate itself from sibling tools calculator_linear_regression and calculator_quadratic_regression.

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?

The description implies regression usage but gives no explicit guidance on when to use this tool versus the dedicated linear or quadratic regression siblings. It also provides no when-not conditions or prerequisites.

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

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