universal-exam-cram-coach

You know him. Night before the exam, hair a mess, eyes wide open, hasn't read a single page of the course. This skill is for him — it doesn't pour in more "knowledge" that it isn't sure about; it teaches only what's actually in your materials, and says "not in the materials" for everything else.

30-second start — clone the repo, then say one line to your agent:

git clone https://github.com/ZeKaiNie/universal-examprep-skill .claude/skills/universal-exam-cram-coach
# In Claude Code / Cursor, say: "use this skill to set up my exam-prep space", then drop in your materials

---

Before / after

With the skill — every claim carries its source, so you can check it:

[#vis_q1] In the figure, which set relation does the shaded region show? The intersection of A and B. Question: hw02.pdf p.3 | Answer: hw02_sol.pdf | 🟢 from your materials

Closed-book / plain agent — sounds just as confident, but you can't tell if it's true:

The shaded region is the union. _{(It's actually the intersection; no source label, nothing to check against — this is where hallucination happens.)}

The difference isn't tone. It's whether each claim lands back in your materials.

---

Numbers

The skill's value is grounding: connecting what's in your materials but not in the model's head — accurately, and never fabricated. Two real measurements (judge: Sonnet):

① In your materials, not in the model — the skill goes from 11% up to 100%. Details mined from course transcripts (the professor's examples, obscure studies, exact numbers) that world knowledge can't answer; closed-book collapses, hand the materials back and it returns:

materials-specific: closed-book vs with the skill

Course · Model	Closed-book	Raw files + generic agent	With the skill
PSYC 110 · Opus 4.8	11%	98%	100%
PSYC 110 · Sonnet 4.6	13%	100%	100%
PSYC 110 · Haiku 4.5	11%	98%	100%
6.006 · Haiku 4.5	45%	89%	91%

② Not in the materials at all — the skill says "not covered" 100% of the time. On out-of-scope probes, with the skill (and raw files) all three models, both courses, abstain honestly 100%; closed-book only 60%–90% (it fabricates a plausible answer). This is the most direct anti-hallucination measure.

out-of-scope probes: honest abstention rate

The skill matches a "raw files agent" on accuracy but costs less — it pulls only the compressed relevant chapters instead of re-scanning the whole file pile each question:

Cost per question (same accuracy, less spend)

Cost / question	Closed-book	Raw files agent	With the skill
PSYC 110	$0.033	$0.117	$0.102
6.006	$0.034	$0.066	$0.063

Full method, three-arm design, judge calibration, cost, limitations → test report.

---

How it works

A ladder of "don't make it up unless you have to":

1. Quiz only from the materials — questions come from a quiz_bank.json, never improvised.
2. Forced source labels — every claim tagged 🟢 from your materials / 🟡 AI-supplemented, may differ from your teacher / ⚠️ AI-generated answer, never passed off as the textbook.
3. If it's not in the materials, say so — abstains honestly on uncovered questions instead of fabricating (100% out-of-scope abstention, measured).
4. Draw-it questions run the algorithm first — for binary trees / graph traversal, it runs the real algorithm in the background to get the topology, then renders — no imagining.
5. Figure-dependent questions won't be served without the figure — no unanswerable question handed to the student.
6. Chapter-sliced knowledge base, loaded on demand — sliced by chapter, loaded by progress, so long chats don't blow up the context. Context −90%.

---

Study modes · time budget · preferences

The skill adapts how deep it teaches, how fast, and whether it asks you questions — all kept in study_state.json, persistent across chats.

3 study modes (how it teaches):

Mode	For
Teach from scratch	Haven't studied at all — walk every chapter from zero, 7-step walkthrough per key question
Start mid-course, shore up weak spots	Know some — start from a chapter you name, target the weak parts
Fill the gaps	Mostly covered — just quiz to find blind spots, mistakes first

4 time budgets (how fast):

Budget	Behavior
≤ 1 day	All-out sprint — never asks you anything, silently infers defaults (teach-from-scratch), goes straight in
1–3 days	Hits the essentials, compresses the rest
3–7 days	Normal pace, asks which chapters you're solid on
> 7 days	Relaxed — for chapters you say you know, it quizzes to verify rather than taking your word

Preferences (remembers your habits): whether walkthroughs append the "common mistakes" / "3-minute recap" closing blocks, reply language (Chinese / English / bilingual), and per-chapter mastery windows (window-add / window-set-status) — all persisted, changed by a single line anytime. See docs/language-policy.md and docs/skill-architecture.md.

---

Install

Claude Code

Recommended — the runtime bundle (a ~230 KB zip with just the skill, none of the dev weight):

Download universal-exam-cram-coach.zip from the latest release and unzip it into .claude/skills/universal-exam-cram-coach/ (project-local or global ~/.claude/skills/).

No dependencies to install up front — the core is pure stdlib. If your materials include PDFs, the agent runs the bundled dependency preflight (scripts/check_deps.py) at setup and offers the exact one-line install before starting, so nothing fails mid-build.

Or clone the repo (developer path — brings benchmark/tests along, ~3.4 MB):

git clone https://github.com/ZeKaiNie/universal-examprep-skill .claude/skills/universal-exam-cram-coach

Codex / Cursor / Windsurf / Antigravity

Clone the repo; have the agent read AGENTS.md (a one-screen fallback contract) or load skills/. These tools write files and run scripts directly.

Web (ChatGPT / DeepSeek / Gemini)

Can't write local files — use the drop-in prompt instead: copy prompts/web_prompt.en.md and send it, then paste your materials.

Full load matrix (per-agent support, entry files) in docs/agent-portability.md. The trigger entry is SKILL.md (a language-neutral router); locales/en/SKILL.md is the full English manual it dispatches to (derived rendering of locales/zh/SKILL.md).

---

Sub-skills

The monolith is split into 9 single-purpose sub-skills the agent loads on demand:

Sub-skill	What it does
exam-cram	Orchestrator — runs the 4-step workflow + study-mode routing
exam-ingest	Builds the workspace from your materials (knowledge base + quiz bank + progress)
exam-tutor	Lazy per-chapter teaching (7-step walkthroughs, draw-it-runs-algorithm-first)
exam-quiz	Draws & grades from the bank (6 question types: MC / short / draw / fill / T-F / code)
exam-review	Mistakes and concept-confusion review
exam-cheatsheet	Pre-exam cheat sheet
exam-audit	Read-only workspace health check
exam-help	One-screen quick reference (workflow / modes / file conventions)
confusion-tracker	Logs concept questions as you go into a pre-exam blind-spot list

All nine live under skills/ (e.g. skills/confusion-tracker/SKILL.md), loaded on demand.

---

Development

Zero-cost structured checks you can run often (no API spend):

python -m unittest discover -s tests -v          # unit tests (pure stdlib, in CI)
python scripts/validate_workspace.py path/to/ws  # validate a built exam-prep workspace

The real paid benchmark is expensive (tens of dollars / hours per matrix), run manually only — see benchmark/docs/running-real-runs.md and the tiering in benchmark/docs/test_tiers.md. Workspace file format: docs/file-format.md.

---

FAQ

No Python installed? Fine. When the agent finds no Python it silently switches to "manual write mode", creating the knowledge-base tree itself — no difference to you.

Only photos / scanned PDFs / a recording? First transcribe with any free web multimodal AI ("extract the highlights and questions as plain text, keep the star/underline markers"), paste into a .txt, then have the agent build the workspace; the rest is plain-text and smooth. Recordings: transcribe first, then feed.

Stuck on one quiz question? Just say "this is too hard / I want to skip" — it files the item to your mistake log, lets you through, and revisits it at the end.

How is this different from just dropping a folder at an AI? Similar accuracy, but the skill is cheaper (only the relevant chapters per question, not the whole pile) and helps weaker models more. See the report.

---

License

MIT. PRs for more subjects' templates or scripts welcome. Good luck on the cram. 🎓

[

](https://www.star-history.com/?repos=ZeKaiNie%2Funiversal-examprep-skill&type=date&legend=top-left)