exam-prep
Skill3 starsChanged 19 days agoMITView on GitHub
Turns a whole course (lecture PDFs, exercise sheets, past exams, transcripts) into a prioritised Anki deck in stages - a blueprint the user approves, card writing, pictures and approval in the chat. Runs only when the user starts it with /anki:exam-prep; for cards from one source or a few topics, use create-cards.
9 other projects use a version of this.
Adopted by
Most recently taken up by
- Noam-Marom/academic-studentstheir own version, first seen Nov 8, 2026
- PeanutGT/NutsSkillstheir own version, first seen Nov 1, 2026
- liknenS/language-learning-skillstheir own version, first seen Oct 25, 2026
- MichaelPrutkow/anki-for-claudeword for word, first seen Oct 17, 2026
- Slava-code/college-kbtheir own version, first seen Oct 15, 2026
- Aysuda-j/claude-skillstheir own version, first seen Sep 24, 2026
Other versions9 projects use a version of this.
Word for word · 1
- MichaelPrutkow/anki-for-claude★ 3100% same
Edited · 0
None found.
Wrote their own version · 8
- IssacW228/student-llm-wiki★ 173same name
- Noam-Marom/academic-students★ 7same name
- Candlest/exam-prep-skill★ 4same name
- PeanutGT/NutsSkills★ 3same name
- Runtime-3rr0r/canvas-scanner★ 2same name
- Aysuda-j/claude-skills★ 1same name
- liknenS/language-learning-skills★ 0same name
- Slava-code/college-kb★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository4 other files it gives its agents.
- check-setupSkill
- create-cardsSkill
- improve-cardsSkill
- visualsSkill
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 5 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 15
Intake: Ask once for whatever is missing: target deck, the sources, exam date, a rough card budget, language.
“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Exam preparation
This is the most expensive way to make cards, and it runs on the user's usage limits. Spend effort where the exam puts its points, and start agents only for courses too big to handle yourself.
Work in a run folder anki-run/<date>/ in the current project. Every step reads and writes files there; keep only short summaries in the conversation.
If overview and the other anki tools are not among your tools, call get_device_info (search for it if it is not loaded) and search for the anki tools again. In the Claude app, a chat reaches the tools on the user's computer reliably only if the user added a folder to it before sending the first message. If the tools are still missing, ask the user to start a new chat, add a folder with the Add folder button (for example the folder with their study material) and send the request again. Only if that does not help either, follow the check-setup skill.
- Intake. Ask once for whatever is missing: target deck, the sources, exam date, a rough card budget, language.
Plan the cost. Count the sources and their pages, then pick a mode:
- Small course (up to about 5 sources or 150 pages): no agents. Do every step yourself, one source or one topic at a time.
- Large course: agents, never more than these: 3
anki:source-analyst, 3anki:card-writer, 1anki:visual-designer, 1anki:card-auditor.
Tell the user in one sentence which mode you chose and how many agents it starts, and go on only once they agree. If they want it cheaper, cut the sources down to the past exams and the lectures those exams cover.
- Sources. Read the past exams first: they set the priorities. Write one inventory per source,
inventory/<source-name>.md, in the format of${CLAUDE_PLUGIN_ROOT}/agents/source-analyst.md. In a large course, split the sources into at most three groups of similar size and start oneanki:source-analystper group, never one per source. - Blueprint. Merge the inventories into
blueprint.md, one row per topic:topic | priority (from past exams) | card types | picture needed | est. cards | already in deck. Markpicture neededfor every topic the exams or lectures show as a drawing. Check existing cards withsearch_notes. Show the blueprint as a short table and wait for the user's approval: this is the cheapest moment to change direction. - Cards. Follow the
create-cardsrules, one draft per topic cluster, titled with its topics. In a large course, give the clusters to at most threeanki:card-writeragents, each with the deck, the note type, its blueprint rows and the inventory files; each reports its draft ids. Picture needs go intovisual-requests.md:<draft id> #<card number> | what to draw | source page or figure id. - Pictures. Make every picture in
visual-requests.mdand for everypicture neededrow, following thevisualsskill: yourself, or in a large course with oneanki:visual-designer. - Audit. In a large course, start one
anki:card-auditorwith the draft ids; it writesaudit.md. Otherwise go through thecreate-cardschecklist yourself. Fix the real problems withdraft_editand ignore false alarms. - Approval. Go through the drafts with the user one at a time: show the cards with
draft_show, word for word, apply changes withdraft_edit, and add the approved cards withdraft_commit. If the user studies on a phone, finish withsync.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

