study

name	study
description	Run a structured AI-assisted study session on a curriculum module or topic. Use when the user wants to learn, review, or work through material — e.g. "/study distributed-systems", "study Paxos with me", or "let's work on the ML module".

Study Session

Run one iteration of the repo's study loop (defined in milestones/roadmap.md) on the topic given in the arguments. If no topic is given, ask which module or concept to work on, listing the modules in curriculum/core/.

Setup

1. If the topic maps to a module, read its file in curriculum/core/ (or curriculum/specializations/) and anchor the session to its learning objectives and mastery checklist.
2. Check research/ for the user's existing notes or error logs on this topic and calibrate difficulty accordingly. Don't re-teach what their notes show they've mastered; target weaknesses.

The loop

Work through these stages, one at a time, conversationally:

1. Explain — teach the concept in three passes: intuition, formalism, implementation. Name the standard misconceptions and edge cases explicitly. Cite where this sits in the module's primary resources so the user can deep-read later.
2. Generate — produce 3–5 exercises at increasing difficulty: at least one conceptual, one quantitative/proof, one open-ended. Keep your rubric hidden.
3. Attempt first — the user solves before you reveal anything. Give hints only when asked, smallest hint first. Never volunteer the answer.
4. Critique — grade their solution against the hidden rubric: correctness (40), depth (25), rigor (20), clarity (15). State the minimum changes needed for full marks.
5. Repair — for anything below full marks, append an entry to the user's error log (suggest research/error-log.md if none exists): topic, mistake, root cause, scheduled re-attempt date (+48h).
6. Transfer — pose one question applying the same concept in a different domain (e.g. a queueing concept applied to GPU scheduling).

Session close

• Summarize: what was covered, scores, gaps logged, what to re-attempt and when.
• Update nothing in curriculum/ — that zone is upstream-owned. All user artifacts go under research/.
• Suggest the natural next step: another loop iteration, /quiz for volume practice, or /oral-exam if the mastery checklist looks close to complete.