learner

To extract knowledge from conversations into reusable documentation, capture non-trivial patterns discovered during code or debugging discussions and formalize them into structured Expertise and Workflow artifacts for future reuse across the codebase.

The best way to document debugging patterns for project reuse is to classify the learning as Expertise or Workflow, then use a structured Markdown body containing Problem, Solution, Triggers, and Scope sections to capture the discovered knowledge.

To store learned skills in a version-controlled project directory, save the captured knowledge artifacts as Markdown files with YAML frontmatter, including name and description, into a designated project path such as the .omc/skills directory.

Yes, you can classify conversation insights as either Expertise or Workflow artifacts. The extraction process requires categorizing the learned skill to ensure the captured knowledge is properly structured and discoverable for future codebase reuse.

Reusable knowledge artifacts should use a structured Markdown format with YAML frontmatter containing the name and description, alongside a body with Problem, Solution, Triggers, and Scope sections, to enable quick discovery and version-controlled storage.

You need to formalize project-level learning into expertise artifacts when non-trivial patterns are discovered during active conversations or debugging, requiring durable documentation to guide future development work and prevent knowledge loss.