reviewing-findings

Confidence scoring validates AWS cost optimization findings by assigning a score that determines action tags like approved, approved_with_review, needs_validation, or filtered. This mechanism ensures only high-quality recommendations pass through to your final report.

A multi-agent review workflow uses four parallel agents to simultaneously evaluate AWS cost optimization findings. This parallel evaluation assesses recommendation accuracy and filters false positives using confidence-based scoring to ensure high-quality outputs.

Confidence scoring validates AWS cost optimization findings by assigning a score that determines action tags like approved, approved_with_review, needs_validation, or filtered. This mechanism ensures only high-quality recommendations pass through to your final report.

The best way to automate false positive filtering for AWS cost findings is using a multi-agent review workflow with confidence scoring. It automatically evaluates accuracy across environments and updates findings.json with review_status and summary metadata.

Reviewing AWS cost findings requires no external dependencies. The workflow operates entirely self-contained using internal scripts to process findings.json, apply confidence scoring, and append review_status metadata.