SOP for assigning calibrated confidence scores to causal claims based
Scanned 9/5/2026
Install to Claude Code
npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill confidence-scoring --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Confidence Scoring?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/yogsoth-ai-confidence-scoring)More formats (shields.io, HTML) on the badges page.
---
name: confidence-scoring
description: SOP for assigning calibrated confidence scores to causal claims based
on evidence quality and quantity.
execution: sop
---
# 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 }`
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!