# Confidence Scoring

> SOP for assigning calibrated confidence scores to causal claims based on evidence quality and quantity.

- Skill: `yogsoth-ai/confidence-scoring` (Agent Skill)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/confidence-scoring`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/confidence-scoring/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/confidence-scoring

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# Confidence Scoring

Assign calibrated confidence scores to causal claims.

## Tool

CC file edit

## Protocol

1. Count supporting evidence (weighted by evidence hierarchy)
2. Count contradicting evidence (weighted similarly)
3. Calculate net confidence: support_weight / (support_weight + contradict_weight)
4. Adjust for mechanism plausibility (+0.1 if strong mechanism, -0.1 if no mechanism)
5. Update claim page frontmatter confidence field

## HARD-GATE

<HARD-GATE>
Confidence must be between 0.0 and 1.0. Must cite the evidence used in calculation.
</HARD-GATE>

## Yield

Returns: `{ claim: string, confidence: number, evidence_count: number }`