# Consensus Measurement

> Compute consensus score from collected judgments using the appropriate statistical method.

- Skill: `yogsoth-ai/consensus-measurement` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/consensus-measurement`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/consensus-measurement/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: yogsoth-ai (https://skillmd.com/u/yogsoth-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/yogsoth-ai/consensus-measurement

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# Consensus Measurement

Compute a quantitative consensus score from the collected judgments. Automatically selects the appropriate measurement method based on data type (IQR for continuous, percentage agreement for categorical, Kendall's W for rankings).

## Execution

Spawn a subagent that analyzes the judgments array, determines the appropriate consensus metric, computes the score, and reports whether the consensus threshold is met.

## Why Subagent

- Statistical computation is a pure function with clear input/output
- Method selection logic is self-contained
- Result feeds directly into round-decision

## HARD-GATE

Output MUST contain: `consensus_score` (numeric), `method_used` (string), `threshold_met` (boolean), and `interpretation` (string). Score must be computed, not estimated.

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## Available SOPs

Optional, no fixed order; the final leaf is always a sop.

| SOP | When to use |
| --- | --- |
| spawn-agent | Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent. |

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