cognito-auditor

To perform QA for AI outputs, you run the auditor mode to systematically review project outputs against expected quality standards. This process identifies recurring patterns and anti-patterns, generating a comprehensive audit report for continuous improvement.

The best way to extract lessons learned from AI project reviews is through systematic pattern identification on past outputs. This Skill accurately identifies actionable lessons from deployment post-mortems to drive continuous improvement of AI processes.

Post-mortem retrospective analysis identifies anti-patterns by systematically reviewing what went wrong and what was missing in AI outputs. This Skill detects recurring failure patterns to ensure high-quality future deployments and process corrections.

You do not need Sinapsis to run AI output quality assurance, as the Skill works standalone for lesson extraction. Sinapsis is an optional dependency used to codify the extracted lessons as instincts for deeper workflow integration.

Yes, you can integrate extracted lessons learned into your workflow by using Sinapsis. This optional integration allows you to codify the lessons identified during post-mortem analysis as actionable instincts for your AI processes.