improve

Automates iterative evaluation and refinement of DxEngine diagnostic AI data files and rules.

Updated Mar 11, 2026
One-click install
npx skills add https://github.com/BEC01/dxengine --skill improve-bec01
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: improve
Source: https://github.com/BEC01/dxengine/tree/main/.claude/skills/improve
Command: npx skills add https://github.com/BEC01/dxengine --skill improve-bec01

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

It streamlines the continuous enhancement of the DxEngine diagnostic system by automating evaluation and data correction processes.

Core Features & Use Cases

  • Automated System Evaluation: Runs iterative assessments of the engine’s diagnostic accuracy and performance metrics.
  • Data Fix Proposal: Identifies gaps or weaknesses in likelihood ratios, disease patterns, and rules, suggesting targeted updates.
  • Use Case: For a medical AI developer, it accelerates the process of refining diagnostic rules and likelihood entries to improve real-world accuracy without manual intervention.

Quick Start

Invoke the improve skill to run the perpetual self-improvement loop, analyzing current evaluations and applying recommended fixes automatically.

Frequently Asked Questions about improve

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

FAQPage Schema
How do I automate diagnostic AI tuning for rule-based medical systems?

Automated diagnostic AI tuning evaluates probability data and disease patterns to propose targeted rule adjustments. This iterative refinement process improves diagnostic accuracy without manual intervention.

What is automated self-evaluation for diagnostic reasoning systems?

Automated self-evaluation runs iterative assessments of a diagnostic engine's accuracy and performance metrics. It identifies gaps in likelihood ratios and disease patterns to suggest data corrections.

Can I optimize likelihood ratios and disease patterns without manual intervention?

Yes, automated system optimization identifies weaknesses in likelihood ratios and disease patterns to suggest targeted updates. It modifies only data files and verifies improvements through automatic re-evaluation.

Does automated self-improvement modify source code or only data files?

Automated self-improvement ensures safe operations by modifying only data files. It refines likelihood entries and diagnostic rules while verifying all improvements through automatic re-evaluation.

What is the best way to refine medical diagnosis software quality through automated tuning?

The best way to refine medical diagnosis software quality is through a perpetual self-improvement loop. This analyzes current evaluations and automatically applies recommended fixes to diagnostic rules.

Are there limitations when applying automated tuning to rule-based system optimization?

Automated tuning is limited to modifying data files for rule-based system optimization. It focuses strictly on probability data and disease patterns, ensuring safe operations without altering core engine logic.