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define-metric

Create standardized metric specifications from YAML frontmatter templates.

21|11|Updated Mar 15, 2026
Search Tags:#documentation#sql#data-analytics#data-quality#define-metric#metric-spec
One-click install
npx skills add https://github.com/ai-analyst-lab/ai-analyst-plugin --skill define-metric
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: define-metric
Source: https://github.com/ai-analyst-lab/ai-analyst-plugin/tree/main/skills/define-metric
Command: npx skills add https://github.com/ai-analyst-lab/ai-analyst-plugin --skill define-metric

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Define a metric clearly and completely using a standardized template so there is no ambiguity about what is being measured, how it's calculated, or how it's interpreted.

Core Features & Use Cases

  • Standardized metric template: ensures consistent definitions across teams.
  • Clear data source and denominator guidance to avoid misinterpretation.
  • Use case: When introducing new metrics or reconciling conflicting definitions across analyses.

Quick Start

Provide a metric name and write its definition using the template to create a complete spec.

Frequently Asked Questions about define-metric

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a standardized metric specification for data analytics?▼

A metric specification eliminates ambiguity by using a standardized template to document the definition, formula, components, segmentation dimensions, data sources, thresholds, known limitations, and related metrics for consistent data analytics calculations.

Why do my analytics metrics show conflicting numbers across different reports?▼

Conflicting metric numbers stem from ambiguous definitions. Standardizing metric specifications clarifies exact data sources, denominators, and calculation formulas to ensure consistent measurements across all analytics projects.

What should be included in a metric definition template to ensure data quality?▼

A metric definition template should include the formal definition, calculation formula, components, segmentation dimensions, data sources, thresholds, known limitations, and related metrics to ensure complete data quality and eliminate misinterpretation.

When do I need to use a formal metric spec in SQL data analytics?▼

You need a formal metric spec when introducing new metrics, reconciling conflicting definitions across analyses, or ensuring consistent metric calculations and interpretations across teams using SQL data sources.

Can I use a YAML frontmatter template to document metric specifications?▼

Yes, you can use a standardized YAML frontmatter template to define precise metric specifications, structuring all components, data sources, and thresholds to eliminate ambiguity in your data analytics documentation.

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