uoa_py_course

Use this skill to give a student FORMATIVE, instructor-voice feedback on a draft (often partial) of the Python-course final assignment — guidance on how to improve, never a grade. Trigger on requests like "give feedback on this assignment draft", "review <student>'s final assignment submission", "feedback on the eClass submission for <student>", "the student submitted an early draft, what should they improve", "feedback on this regression/clustering/classification notebook for the final assignment", or when the user supplies a .zip / folder / .ipynb of a final-assignment draft and asks for feedback rather than a grade. Both the eClass download automation (automation_infrastructure/eclass/download_submissions.py) and emailed drafts land in one unified per-student location, students_work/class_<YY>/<lastname_t>/final_assignment/; the skill locates the student there, reads the already-extracted dated download (or extracts a .zip only if needed). It reads the authoritative specs (final_assignment/submission_requi

Use this skill to draft English-language LinkedIn posts announcing updates to the UoA "Python for Data Science, ML and AI" MSc course. Trigger on requests like "draft the next linkedin post", "write the linkedin post about <theme>", "linkedin post for the course updates", "continue the course post series", "mark post N as published", or "rebuild the linkedin series plan". The series plan (themes, evidence, status) is the file admin_docs/linkedin_posts/series_plan.md — this skill reads it, gathers and VERIFIES evidence from git history and repo files, writes one plain-text post draft per invocation to admin_docs/linkedin_posts/post_NN_<slug>.md, and updates the plan's status column. It never publishes anything (no LinkedIn API — the maintainer copies the text out and posts manually), never invents numbers or features not verifiable in the public repo, and never mentions students, grades, PII, secrets, or gitignored private content. Do NOT use this skill to write feedback or grades (separate skills exist), to e

Use this skill to evaluate one lecture folder in this course repo against the 9-category pedagogical rubric (six internal + three external) and produce a Markdown report with a composite tier and prioritized fixes. Trigger on requests like "evaluate lecture NN", "audit lecture NN", "score lecture NN", "review the lecture material for NN", or when the user supplies a `lectures_*/` folder path and asks for a quality assessment. Do NOT use it to: improve, rewrite, or propose content for a lecture (that work belongs to the future `create-improve-lecture` skill — this skill flags absence only); evaluate non-lecture material such as `README.md`, `CLAUDE.md`, or arbitrary scripts; grade student submissions or final-assignment notebooks (use `final_assignment/grade_feedback.prompt.md` instead). If the lecture number or path doesn't resolve to exactly one folder, ask which folder before proceeding.

Use this skill to produce a structural outline for one lecture in this course repo — a draft `goals_NN.md` plus an internal design doc that pre-conforms to the 9-category rubric used by `uoa-py-course-lecture-eval`. Trigger on requests like "outline lecture NN", "plan a lecture on X", "design lecture NN before writing it", "draft goals_NN.md for X", "plan the refactor of lecture NN", or "scaffold the outline for the regression lecture". Do NOT use it to: generate lecture content (no code, no datasets, no specific industry uses — that work belongs to the future `create-improve-lecture` skill); evaluate an existing lecture (use `uoa-py-course-lecture-eval`); grade student submissions; rewrite `docs/Lectures_outline.md` directly (the skill emits a suggested patch instead). If the lecture number or topic is ambiguous, ask before proceeding.