self-improving-agent

To capture AI interaction errors for continuous learning, log command failures, user feedback, and discovered workarounds into categorized Markdown files within a .learnings/ directory. This structured logging prevents recurring mistakes by preserving historical corrections.

The best way to log command failures and document workarounds is to automatically record unexpected behaviors and their solutions. This workflow optimization identifies and documents better approaches to recurring tasks, preventing future occurrences of the same error.

Knowledge capture from AI interactions works by recording factual corrections, new insights, and feature requests into structured Markdown files. This enables continuous improvement by feeding discovered shortcuts and better approaches back into the AI's knowledge base.

Yes, you can promote captured learnings into permanent documentation like AGENTS.md, SOUL.md, or TOOLS.md. This facilitates elevating valuable error corrections and workflow optimizations from temporary logs into authoritative reference files.

No dependencies are required to start logging AI errors and new insights. The skill operates independently using scripts and references to capture factual corrections and command failures into categorized Markdown files.

You should not use a self-correcting agent for error logging when dealing with transient, non-recurring issues or highly sensitive data. It is designed for identifying and documenting better approaches to recurring tasks and persistent command failures.