Turn a research paper into teaching materials — a lecture outline, the 3-5 results worth presenting (with intuition), a slide skeleton ready for `/create-lecture`, discussion questions, and a problem-set brief. Reads the paper end-to-end and pitches to a stated audience level. Use when user says "turn this paper into a lecture", "teach from this paper", "build slides from this PDF", "make teaching materials from X", "I'm presenting this paper to my class".
npx skills add https://github.com/pedrohcgs/claude-code-my-workflow --skill teach-from-paper
Convert one research paper into a ready-to-build teaching package: a lecture outline, a shortlist of teachable results with the intuition spelled out, a slide skeleton, discussion questions, and an exercise brief. The deliverable is an outline and a brief — not a finished deck; the slide skeleton is shaped to hand straight to /create-lecture, and the exercise brief to /scaffold-exercises.
.tex, .md) and a slot to teach it — a lecture, a reading group, a job-market practice talk./create-lecture to do the drafting.Not for: literature surveys across many papers (use /lit-review); refereeing the paper's correctness (use /review-paper); drafting the actual Beamer slides (use /create-lecture).
$0 — path to the paper.| Format | How to read it |
| --- | --- |
| .tex, .qmd, .md, .txt | Read directly with the Read tool. |
| .pdf | TMP=$(mktemp -t paper).txt && pdftotext "$0" "$TMP" (poppler-utils), then Read/Grep "$TMP". |
If extraction fails or the tool is missing, ask the user for a plain-text version and stop. The full paper goes in the context window (1M) — read it end-to-end before extracting; do not skim the abstract and guess.
Read the paper start to finish. Then resolve the audience level and time budget — from --level / --minutes if given, otherwise ask once. Echo a Pre-Flight Report before extracting:
## Pre-Flight Report
**Paper:** [title, authors, year]
**One-line thesis:** [the paper's central claim in your words]
**Audience level:** undergrad | phd | seminar (drives notation depth + which proofs survive)
**Time budget:** N minutes (~N/2 slides)
**Prerequisites assumed:** [concepts students must already have]
**Running example candidate:** [the paper's application that can thread the lecture]
Get a nod on level + thesis, then proceed. Level governs everything downstream: undergrad keeps intuition and drops proofs; phd keeps the identifying assumptions and one key derivation; seminar foregrounds the contribution-vs-literature framing.
Produce a motivation → setup → key result → method → takeaways arc, then a slide skeleton matching the time budget (~2 min/slide). Each skeleton entry is a title + one-line content note + figure/diagram placeholder — enough for /create-lecture to draft from, no prose. Honor the project's pedagogy invariants in shape: motivation before formalism, a worked example near each definition, a transition slide at each act break.
/scaffold-exercises, which fleshes out problems, data, and answer keys. Skip if --no-exercises.Write to quality_reports/teach_from_paper_[sanitized-title].md:
# Teaching Package: [Paper Title]
**Audience:** [level] · **Budget:** [N min] · **Date:** [YYYY-MM-DD]
## 1. Lecture Outline
Motivation → Setup → Key Result → Method → Takeaways (one line each)
## 2. Results Worth Presenting
### R1 — [name]
- **Statement:** … · **Intuition:** … · **Breaks when:** …
[R2..R5]
## 3. Slide Skeleton (→ /create-lecture)
| # | Title | Content note | Figure/diagram |
## 4. Discussion Questions
1. [comprehension] … 5. [critique] …
## 5. Exercise Brief (→ /scaffold-exercises)
- **E1:** [prompt] — drills [skill] — answer shape: [form]
/create-lecture [Topic]. Exercise brief ready — run /scaffold-exercises."--level — undergrad | phd | seminar. Sets notation depth, which proofs survive, and question difficulty. Asked interactively if omitted.--minutes — target lecture length; the slide count is roughly --minutes/2.--no-exercises — skip Phase 3's exercise brief (keep discussion questions)./create-lecture — consumes the Phase 2 slide skeleton to draft the actual Beamer deck. See .claude/skills/create-lecture/SKILL.md./review-paper — referee the paper's correctness *before* teaching it if you're unsure the result holds. See .claude/skills/review-paper/SKILL.md./lit-review — for situating the paper among many, rather than teaching one deeply. See .claude/skills/lit-review/SKILL.md./scaffold-exercises (a downstream skill that fleshes out problem sets); this skill stops at the brief./create-lecture. The slide skeleton is an outline, not Beamer./scaffold-exercises./review-paper if the result's validity is in doubt.Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.
Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.
Efficient database search tool for bioRxiv preprint server. Use this skill when searching for life sciences preprints by keywords, authors, date ranges, or categories, retrieving paper metadata, downloading PDFs, or conducting literature reviews.
Query and analyze scholarly literature using the OpenAlex database. This skill should be used when searching for academic papers, analyzing research trends, finding works by authors or institutions, tracking citations, discovering open access publications, or conducting bibliometric analysis across 240M+ scholarly works. Use for literature searches, research output analysis, citation analysis, and academic database queries.
Access USPTO APIs for patent/trademark searches, examination history (PEDS), assignments, citations, office actions, TSDR, for IP analysis and prior art searches.
Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.
Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.
Take pedrohcgs/teach-from-paper from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.