omc-learner

To extract reusable skills from conversation logs, you can use a tool to identify non-obvious problem-solving techniques and convert them into Codex-compatible skill files for future reuse.

Capturing non-generic knowledge from conversations requires careful curation to filter out standard documentation, ensuring only specific, non-obvious project insights are codified into Codex skills.

Yes, extracted conversation lessons can be stored at both project-level and user-level scopes, allowing you to vary the reusability of codified skills across different environments.

To ensure conversation analysis avoids generic documentation, the extraction process applies quality control to verify that each captured lesson contains unique, non-obvious value specific to your project.

Yes, omc-learner works for codifying non-standard coding techniques by processing conversation transcripts and transforming specific problem-solving lessons into reusable Codex skills.

You should not use automated skill extraction when conversations contain only standard troubleshooting steps or generic solutions, as the process requires non-obvious, unique insights to generate valuable Codex skills.