Self-Improving + Proactive Agent

You can automate AI agent self-improvement by tracking corrections and learning patterns locally. This Skill captures user feedback into structured memory files like corrections.md, applying learned patterns proactively across global, domain, and project namespaces.

Yes, you can apply learned corrections across multiple project namespaces. The Skill organizes memory into global, domain, and project directories, ensuring that captured preferences and lessons are accessible and reused across diverse tasks within those defined workspace boundaries.

Agent memory consolidation does not require network access. The Skill keeps all data locally under the ~/self-improving directory, ensuring that memory.md, corrections.md, and heartbeat-state.md files are updated offline only when corrections are provided.

To set up a self-improving workspace, initialize local memory templates and correction logs under the ~/self-improving directory. Begin capturing explicit corrections during tasks to seed long-term improvements and update the structured memory lifecycle automatically.