evidence-adjudicator

Synthesizes investigator evidence into ranked root cause verdicts with confidence scores.

8|1|Updated Jan 24, 2026
One-click install
npx skills add https://github.com/bordenet/superpowers-plus --skill evidence-adjudicator
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: evidence-adjudicator
Source: https://github.com/bordenet/superpowers-plus/tree/main/skills/engineering/evidence-adjudicator
Command: npx skills add https://github.com/bordenet/superpowers-plus --skill evidence-adjudicator

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill consolidates fractured investigator outputs after an incident to produce a single, evidence-weighted root cause verdict, resolving contradictions and avoiding over-counting agent agreement.

Core Features & Use Cases

  • Evidence synthesis: Aggregate supporting and disconfirming findings from multiple investigator branches and deduplicate repeated facts.
  • Reasoning trees & confidence: Build a structured reasoning tree with confidence-weighted scores and calibrated verdicts.
  • Adversarial validation: Run a disconfirmation pass to surface alternative explanations and reduce confirmation bias.
  • Use Case: After parallel investigator runs on a production outage, produce a ranked list of hypotheses with supporting evidence, gaps, and escalation flags for human review.

Quick Start

Ask the evidence-adjudicator to synthesize all investigator branch evidence and return a ranked root cause verdict with supporting and disconfirming evidence and confidence scores.

Frequently Asked Questions about evidence-adjudicator

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

FAQPage Schema
How do I consolidate multiple investigator branches into a single root cause verdict?▼

Consolidate fractured investigator branches by synthesizing supporting and disconfirming evidence, deduplicating facts, and applying confidence scoring to produce a ranked root cause verdict.

What is the best way to resolve contradictions in post-incident investigation evidence?▼

Resolve contradictions in post-incident investigation evidence by applying contradiction detection and adversarial disconfirmation passes to surface alternative explanations and eliminate confirmation bias.

How does confidence scoring work for incident response root-cause analysis?▼

Confidence scoring for incident response root-cause analysis works by building a structured reasoning tree that weights supporting and disconfirming findings into calibrated verdicts.

Can I use evidence synthesis to avoid over-counting agent agreement during an outage review?▼

Yes, evidence synthesis deduplicates repeated facts across parallel investigator runs to avoid over-counting agent agreement and generate accurate escalation flags for human review.

How do I run an adversarial disconfirmation pass on incident reproduction results?▼

Run an adversarial disconfirmation pass on incident reproduction results by challenging the reasoning tree with alternative explanations, measuring divergence points, and adjusting confidence scores accordingly.

When should I not use automated evidence adjudication for production outage investigations?▼

Avoid automated evidence adjudication for production outages when investigator branches lack sufficient supporting or disconfirming evidence, as confidence-calibrated verdicts require structured branch inputs to function reliably.