# Metric Governance

> Metric Governance

- Skill: `bkjohn2018/metric-governance-2` (Agent Skill)
- Install (CLI): `npx skillmds@latest add bkjohn2018/metric-governance-2`
- Raw SKILL.md: https://api.skillmd.com/api/skills/bkjohn2018/metric-governance-2/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: bkjohn2018 (https://skillmd.com/u/bkjohn2018)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/bkjohn2018/metric-governance-2

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# Metric Governance

## Purpose
Define standards for metric governance in analytics domains.

## Scope
This skill applies to all declared metrics in governance packages, including:
- workload metrics
- throughput metrics
- quality metrics
- exception metrics

Before drafting governance documentation, check and apply:
.github/skills/finance-documentation-lifecycle

Use it as the source of truth for ISO 9001-inspired terminology, process/procedure/SOP distinctions, documentation lifecycle, and evidence/record expectations.

## Metric standard
Each metric must include:
- formula
- grain
- source
- owner
- steward
- cadence
- threshold
- escalation path

## Writing rules
- Use precise definitions and avoid ambiguity.
- Include measurement units and aggregation logic.
- Specify the operational owner and data steward separately.
- Document the frequency of refresh and review.
- Define acceptable thresholds and escalation triggers.

## Output expectations
- Every metric definition maps to a control point.
- Every metric includes a data source and stewardship statement.
- Use standard metric metadata table format.
- Keep definitions concise and complete.