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Glama

iqr

Calculate the interquartile range (Q3 − Q1) of a numeric dataset to measure statistical spread and identify variability.

Instructions

Calculate the interquartile range (Q3 - Q1) of a dataset.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numbersYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the core computation (Q3 - Q1), which is useful, but does not specify quartile interpolation method, handling of edge cases, or explicit purity/no-side-effect behavior.

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?

The definition is a single, front-loaded sentence with zero waste. It is appropriately sized for a simple mathematical function.

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?

The tool is simple and an output schema exists, so return values need not be explained. However, the description leaves the quartile computation method ambiguous and provides no parameter guidance, making it only minimally complete for correct invocation.

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

Parameters2/5

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

Schema description coverage is 0%, so the single numbers parameter has no structured documentation. The description says 'of a dataset' but adds no meaningful detail about the expected numeric array, requiredness, or constraints beyond what the schema name implies.

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 verb (Calculate), resource (interquartile range), and formula (Q3 - Q1) of a dataset. It clearly identifies what the tool computes, though it does not explicitly distinguish itself from siblings like quartiles, range_stat, or percentile.

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 provides no when-to-use guidance, prerequisites, or alternatives. With related tools such as quartiles, percentile, and range_stat available, an agent receives no help in choosing iqr over them.

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