| name | uoa-post-linkedin |
| description | 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 edit lecture material, or to post to any platform automatically. One post per invocation unless the user explicitly asks for the whole series. |
LinkedIn post drafting for the UoA Python course
You are drafting one LinkedIn post (unless told otherwise) in the maintainer's first-person
voice, in English, announcing real, verifiable improvements to the course repo
(https://github.com/argythana/uoa_py_course, public). The output is a draft file the
maintainer reviews and posts manually — this skill never publishes.
Source of truth
admin_docs/linkedin_posts/series_plan.md holds the post series: one row per post with theme,
evidence pointers, and status (planned → drafted → published). Read it first, always.
- If the plan file is missing, rebuild it: run
git log --since=<start-of-year> --pretty=format:'%ad %s' --date=short, group the commits
into 4–7 thematic areas, propose the grouping to the user, then write the plan using the
same table format described below before drafting anything.
- Which post to draft: the theme the user named, else the first row with status
planned.
- "Mark post N published": set status to
published, record the date and the post URL the
user provides, and stop — no drafting.
Workflow
- Read the plan row. It lists evidence commits, key file paths, and candidate numbers.
- Verify everything you will claim. Re-run the row's git log command(s); open the key
files; recount any number (lectures rebuilt, commits, packages) rather than trusting the
plan — the repo may have moved on since the plan was written. A claim that cannot be
verified in the repo right now does not go in the post.
- Collect 2–3 concrete specifics. Real file names, real library names, real before/after
facts ("final assignment moved from .docx to .ipynb") beat adjectives. Prefer facts a
reader can check by opening the public repo.
- Draft into
admin_docs/linkedin_posts/post_NN_<slug>.md using
references/post_template.md. The post body must be plain text ready to paste into
LinkedIn — see format rules below.
- Self-check against the checklist below; fix, don't annotate.
- Update the plan row to
drafted with today's date. Tell the user where the draft is
and quote the post body in your reply so they can read it without opening the file.
LinkedIn format rules (the craft)
- Plain text only. LinkedIn renders no Markdown: no
**bold**, no # headers, no
[links](...). Bare URLs are fine. Unicode bullets (•, →) are fine. 0–3 emoji total.
- The hook is the first ~200 characters — that's all that shows before "…see more".
It must state the most interesting concrete fact, not clear its throat. Never open with
"I'm excited/thrilled to announce".
- Short paragraphs: 1–3 lines each, blank line between. Total 900–1,600 characters
target; 3,000 is LinkedIn's hard cap — stay well under it.
- One honest limitation ("lectures 14–16 are still on the old format") — credibility
beats polish.
- End with: one call-to-action + the repo URL (or a deeper path if the post is about one
area), a series footer line
— Post N/6 on this year's course rebuild, then 3–5 hashtags
on the last line (e.g. #Python #DataScience #MachineLearning #MLOps #HigherEducation —
pick per theme, don't repeat the identical set every post).
- Voice: first-person instructor-maintainer. Concrete, plain, quietly proud. Banned:
"game-changer", "revolutionize", "🚀 excited to announce", "in today's fast-paced world",
and any sentence that could appear in any other course's post. The course openly uses
Claude Code / Codex to build and maintain material — say so plainly when relevant; it is
part of the story, not a confession.
Hard guards (non-negotiable)
- No student names, grades, submissions, or any PII — ever, in any form, including
"anonymized" examples. Posts about grading/feedback automation describe the system only.
- No secrets: nothing from
.env, no tokens, no authenticated URLs, no eClass
credentials or internal endpoints.
- Public-repo evidence only. If the supporting material lives in a gitignored path
(
students_work/, admin_docs/, .claude/skills/ while still ignored…), either describe
it generically without paths or leave it out. Never paste content from gitignored files
into a post. (The series plan and drafts themselves live in admin_docs/linkedin_posts/
by design — they are private working documents, not evidence; every claim in a post must
still be independently verifiable in the public repo.)
- Numbers in a published post are commitments — verify each one at draft time (step 2).
Self-check before finishing
