What is learn-review?

A learning-review workflow that checks whether you understand a topic after completing a learning quest. It combines a quiz with a Feynman test, where you explain the idea in simple words, and calculates a combined score.

Use it after /learn to test your understanding, score your answers, update the learning record, and decide whether to continue or repeat material.

It closes the gap between watching or reading material and being able to explain and apply it. The result can lead to passing, a later review, or extra practice.

learn-review — Skill for Claude Code by Szewowsky: A learning-review workflow that checks whether you understand a…

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add skills/szewowsky/learn-skill/learn-review

Any agent

npx skills add Szewowsky/learn-skill --skill learn-review

Clone the repo

git clone --depth 1 https://github.com/Szewowsky/learn-skill

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/szewowsky/learn-skill/learn-review.svg)](https://agentmods.dev/skills/szewowsky/learn-skill/learn-review)

Your own site

<a href="https://agentmods.dev/skills/szewowsky/learn-skill/learn-review"><img src="https://agentmods.dev/badge/skills/szewowsky/learn-skill/learn-review.svg" alt="Measured on agentmods" height="20"></a>

Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,687 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00085	$0.01687
Opus 5	$0.00043	$0.00843
Sonnet 5	$0.00017	$0.00337
Haiku 4.5	$0.00009	$0.00169

Measured 5d ago against content hash ad14e027c128, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

learn-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

learn-review/SKILL.md · 184 lines

How it starts

The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Learn Review — Pętla Zwrotna Nauki

Dlaczego ten skill istnieje

Obejrzenie filmiku ≠ nauka. Ten skill sprawdza czy faktycznie rozumiesz temat — nie czy zapamiętałeś fakty, ale czy potrafisz wytłumaczyć koncept kumplowi (Feynman probe) i zastosować wiedzę (quiz). Waga 60% na Feynmana, bo jeśli umiesz wytłumaczyć prosto — rozumiesz naprawdę.

Metryka: Composite Learning Score (CLS)

CLS = quiz_avg × 0.4 + feynman_score × 0.6

CLS	Wynik	Akcja
>= 80%	PASSED	Achievement unlocked, następny quest
60-79%	SOFT PASS	Przechodzi, wraca za 3 dni
< 60%	FAILED	Adaptacja + powtórka

Flow

Krok 1: Znajdź feedback-loop

Sprawdź output directory (env LEARN_OUTPUT_DIR, fallback ./learn-output/).

Jeśli argument podany:

Jeśli to ścieżka do pliku → użyj bezpośrednio
Jeśli to slug → szukaj *[slug]*feedback-loop.md w output dir

Jeśli brak argumentu:

Szukaj *feedback-loop.md w output dir
Jeśli jeden plik → użyj go
Jeśli wiele → pokaż listę i zapytaj który
Jeśli zero → powiedz że trzeba najpierw /learn [temat] z quest generation

Krok 2: Czytaj stan nauki

Przeczytaj feedback-loop.md. Znajdź:

Który quest ma status pending (to jest bieżący do review)
Jakie pre-generowane pytania ma ten quest
Nazwa pliku quest chain (z YAML front matter: quest_file)

Przeczytaj też quest chain żeby zobaczyć checkboxy.

Krok 3: Sprawdź ukończenie questa

Przeczytaj quest chain i sprawdź checkboxy dla bieżącego questa:

Wszystkie - [x] → quest ukończony, przejdź do Review Gate
Jakiekolwiek - [ ] → quest nieukończony

Jeśli nieukończony:

Quest "[nazwa]" nie jest jeszcze ukończony — brakuje kroków: [lista]. Dokończ i wróć z /learn-review.

Krok 4: Review Gate

4a. Quiz

Wyświetl pre-generowane pytania quizowe (z feedback-loop.md), jedno po drugim:

Quiz — Quest X: [Nazwa]

Pytanie 1/3 (mechanizm):
[treść pytania]

Twoja odpowiedź:

Poczekaj na odpowiedź. Potem następne pytanie. Potem następne.

Read the full file on GitHub · 184 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

5d ago First seen · 184 lines · 85 tokens per session scan A ad14e027c128

Subscribe to this mod's changes

learn-review is a skill published in the GitHub repository Szewowsky/learn-skill (2 stars, last pushed 5mo ago), licensed MIT. It adds 85 tokens to every session and 1,687 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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learn-review