ai-factory.evolve

To improve AI skills via codebase analysis, you apply the evolve skill to evaluate project context and accumulated patches, generating actionable updates that make existing skill definitions more project-specific and effective over time.

AI skill self-improvement is the process of analyzing project descriptions, code conventions, and error patterns to automatically enhance skill definitions, ensuring the AI adapts its behavior based on past mistakes and project-specific requirements.

Yes, you can use accumulated patches to prevent recurring errors by analyzing past fixes, such as null-reference errors, and automatically updating skill definitions to include mandatory guards that stop similar bugs from happening again.

No, the skill improvement process requires no external dependencies, running directly via internal scripts to analyze patch files, codebase conventions, and existing skill definitions to generate actionable improvements.

The best way to update AI skills for iterative adaptation is running the evolve skill, which analyzes project lifecycle context and accumulated patches to automatically refine existing skill definitions and prevent recurring development issues.

Avoid automated skill enhancement when a codebase lacks sufficient patch history or established conventions, as the tool requires accumulated error patterns and project context to generate meaningful, actionable improvements for skill definitions.