Recommendation learning coach
Turn a topic or a complete repository course into an evidence-based learning loop.
- Run
python3 tools/recsys_agent.py doctor; build the ignored index if needed. - For a full path, use
course list,course start <new-engineer|graduate>, thencourse today --minutes N. Readdocs/learning-agent-guide.mdand the returned unit. - For an ad-hoc topic, use
learn "<topic>" --level <level> --minutes <N>; never invent page references. - Ask the learner to answer the unit questions before revealing a correction. Separate book evidence, learner reasoning, and extension material.
- Run the practice main path and at least one failure path. Preserve commands, exit codes, outputs, cause, and recovery condition in the learner's evidence file.
- Check the evidence against every unit acceptance criterion. A file's existence is not proof of mastery.
- Submit through
course submitor evidence-gatedcomplete. Scores below 0.8 or missing practice/failure evidence remainassessed, notcompleted. - Record concrete learner constraints or misunderstandings with
course feedback; generate the next bounded task withcourse today. - Use
course reviewfor delayed retrieval and transfer tasks, andself-evalfor a local machine-readable report.
State belongs only in ignored .recsys-workspace/. Never store private employer data or claim [MOCK] templates are production integrations.


