review
Skill2 starsChanged 8 days agoMITView on GitHub
Spaced-repetition review of topics that are due and past mistakes, quick active-recall questions, reschedules each topic. Use when the user asks to review, revise, repeat or do flashcards.
192 other projects use a version of this.
Adopted by
Most recently taken up by
- microsoft/veronatheir own version, first seen Nov 8, 2026
- microsoft/FluidFrameworktheir own version, first seen Nov 8, 2026
- charliee1w/consolidation-memorytheir own version, first seen Nov 8, 2026
- jisuzzzz/haechitheir own version, first seen Nov 8, 2026
- apokamo/kajitheir own version, first seen Nov 8, 2026
- dirien/yet-another-agent-harnesstheir own version, first seen Nov 8, 2026
Used with
Projects with it also use close-spec, design-with-images and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
dzhngSkillclose-spec
When a spec under specs/<feature>/ is done shipping (a write-spec build, or any planned task that produced a spec), archive it to specs/done/ and rewrite it from a build-plan into a durable rationale — the why, the principles, the invariants — pointing back to the real code for the how. Use when implementation has landed and the plan no longer matches what shipped, or the user says a feature/spec is finished. Pairs with [write-spec](../write-spec/SKILL.md) (the plan this closes) and [review](../review/SKILL.md) (run before closing).
Also in 5 projects that use this
dzhngSkilldesign-with-images
Explore UI and visual design with image generation, then iterate the real implementation against the user-selected concept. Use when brainstorming visual directions, offering mockup variants, or implementing an approved generated design; do not stop at the mockups or the first code approximation.
Also in 5 projects that use this
LambenthanSkilldaily-arxiv
每日从 arXiv 拉取新论文,过滤相关性,auto-ingest 高优先级论文,检测 SOTA 更新
Also in 5 projects that use this
LambenthanSkillexp-eval
实验判决门:Review LLM 独立评判实验结果 → 4 种判决路径 → 自动更新 claims confidence、ideas status、graph edges
Also in 5 projects that use this
- +3 more from dzhng
- +5 more from Lambenthan
Other versions192 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 192
- garrytan/gstack★ 141ksame name
- ansible/ansible★ 71ksame name
- docling-project/docling★ 70ksame name
- traefik/traefik★ 65ksame name
- ClickHouse/ClickHouse★ 51ksame name
- temporalio/temporal★ 24ksame name
- tisfeng/Easydict★ 15ksame name
- juicedata/juicefs★ 15ksame name
- elie222/inbox-zero★ 13ksame name
- gitkraken/vscode-gitlens★ 10ksame name
182 more not listed
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 repository10 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- Example-Subject/CLAUDE.mdCLAUDE.md
- _template/CLAUDE.mdCLAUDE.md
- examSkill
- ingestSkill
- learnSkill
- quizSkill
- setupSkill
- statusSkill
- todaySkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 157 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 16
Ask ONE question at a time — short active recall (define, why, what happens if, calculate, compare).
- Very specific: line 18
Before asking, find the source for the question: for a mistake, use ~/Study/.tools/study search <Subject> "<the misconception in plain …
- Distinctive: line 21
After my answer: ✅/⚠️/❌, the correct answer in 1–3 lines with a source citation.
“Common” is measured: kept by at least 6 in 10 of the 157 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
Spaced-repetition review (default 8 questions)
- Subject from argument;
allor none → gather due rows from every~/Study/*/progress.md, skipping subjects whoseCLAUDE.mdsays- **Reviews:** paused since …. If I name a paused subject, say it is paused and ask whether to resume it (resume = replace that line with- **Reviews:** resumed <today>); don't review it unless I say yes. A prompt like "Review only<topic>in<subject>, 3 questions" means exactly that: that one topic, 3 questions, then step 5 and 6. - Queue: unfixed rows in
mistakes.mdfirst, then topics with Next review ≤ today (most overdue first), then lowest Level. If nothing is due, say so and offer 3 questions on the weakest topics instead. - Ask ONE question at a time — short active recall (define, why, what happens if, calculate, compare).
Vary the format; no MCQ unless the topic is about telling similar things apart.
Before asking, find the source for the question: for a mistake, use
~/Study/.tools/study search <Subject> "<the misconception in plain words>" -k 3(local model, ~2 s) and Grepconverted/for exact terms. Cite what you find in the answer. - After my answer: ✅/⚠️/❌, the correct answer in 1–3 lines with a source citation.
- Reschedule each topic with the ladder 1 → 3 → 7 → 16 → 35 days: ✅ → next step (Level +1, max 5),
⚠️ → same interval again, ❌ → 1 day (Level −1, min 1) and log it in
mistakes.md. A mistake answered ✅ → markFixed? ✅. - Save
progress.md/mistakes.md/ session log, runstudy log … --kind recallonce per topic (Event log rule in~/Study/CLAUDE.md), then show:n reviewed · x correct · next due: ….
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.

