What is spaced-review?

A study workflow that selects random saved clippings from an Obsidian vault and turns their key ideas into questions and answers for spaced repetition, a method of reviewing information at intervals.

Use it to review saved material with questions about concepts, applications, tradeoffs, and connections, with answers linked to the original notes.

It helps reveal what you understand and what you have forgotten instead of relying on rereading notes.

spaced-review — Skill for Claude Code by JeanDiable/obsidian-claude

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.

Any agent

npx skills add JeanDiable/obsidian-claude --skill spaced-review

Clone the repo

git clone --depth 1 https://github.com/JeanDiable/obsidian-claude

Made for: Claude Code.

Or install obsidian-claude, the plugin that ships this one along with the rest of its 19 skills.

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/jeandiable/obsidian-claude/spaced-review/github.svg)](https://agentmods.dev/skills/jeandiable/obsidian-claude/spaced-review)

Your own site

<a href="https://agentmods.dev/skills/jeandiable/obsidian-claude/spaced-review"><img src="https://agentmods.dev/badge/skills/jeandiable/obsidian-claude/spaced-review/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/jeandiable/obsidian-claude/spaced-review"><img src="https://agentmods.dev/badge/skills/jeandiable/obsidian-claude/spaced-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 599 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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	$0.00021	$0.00599
Opus 5.5	$0.00008	$0.00240
Sonnet 5.5	$0.00004	$0.00120
Haiku 4.5	$0.00002	$0.00060

Measured 2mo ago against content hash 3434d6518d33, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

spaced-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 2mo 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.

skills/spaced-review/SKILL.md · 95 lines

How it starts

The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review

Generate Q&A pairs from random categorized clippings for spaced repetition review.

Vault Path

~~/Library/Mobile Documents/iCloud~~md~obsidian/Documents/My_note

Input

Optional: /review N where N is the number of clippings to review (default: 5)

Workflow

Step 1: Select Random Clippings

List all .md files in 50_Clippings/ subfolders (only categorized ones, not root)
Randomly select N files
Read each selected file

Step 2: Generate Q&A

For each selected clipping:

Analyze the content and identify 2-4 key knowledge points
Generate questions that test understanding (not just recall):
- Conceptual: "Why does X work this way?"
- Application: "How would you apply X in scenario Y?"
- Analysis: "What are the tradeoffs between X and Y?"
- Synthesis: "How does X relate to Y?"
Generate detailed answers with:
- Direct answer to the question
- Key knowledge points summarized
- Links to source material and related wiki entries

Step 3: Create Output Files

Questions file: 50_Clippings/Review_Questions_YYYY-MM-DD.md

---
title: "Review Questions YYYY-MM-DD"
created: YYYY-MM-DD
modified: YYYY-MM-DD
tags: [review, spaced-repetition]
description: "Review questions generated from N random clippings"
---

# Review Questions — YYYY-MM-DD

## From: [[ClippingTitle1]]
1. Question 1?
2. Question 2?

## From: [[ClippingTitle2]]
1. Question 3?
2. Question 4?

...

Answers file: 50_Clippings/Review_Answers_YYYY-MM-DD.md

---
title: "Review Answers YYYY-MM-DD"
created: YYYY-MM-DD
modified: YYYY-MM-DD
tags: [review, spaced-repetition]
description: "Answers and knowledge summaries for review questions"
---

# Review Answers — YYYY-MM-DD

## From: [[ClippingTitle1]]
### Q1: Question 1?
**Answer**: ...
**Key Points**:
- Point 1
- Point 2
**Related**: [[WikiEntry1]], [[WikiEntry2]]

### Q2: Question 2?
...

Important Rules

Questions should test UNDERSTANDING, not just memorization
Answers should include enough context to be a learning resource
Always link to source clippings and relevant wiki entries
Vary question types across conceptual, application, analysis, synthesis
Match language to the clipping content language

Read the full file on GitHub · 95 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.

2mo ago First seen · 95 lines · 21 tokens per session scan A 3434d6518d33

Subscribe to this mod's changes

spaced-review is a skill published in the GitHub repository JeanDiable/obsidian-claude (2 stars, last pushed 8mo ago), licensed MIT. It adds 21 tokens to every session and 599 once invoked, about $0.0001 per session on Opus 5.5. 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.

Learning and teaching

spaced-review next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
spaced-reviewJeanDiable/obsidian-claude	Skill	2	8mo ago	MIT	A	21	Claude Code
hr-onboardingnexu-io/open-design	Skill	106k	today	Apache-2.0	A	62	Claude Code, Codex
book-mirrorgarrytan/gbrain	Skill	32k	today	MIT	A	138	Claude Code
exam-forecastanthropics/claude-for-legal	Skill	9.9k	today	Apache-2.0	A	73	Claude Code
lean-formalizewanshuiyin/Auto-claude-code-research-in-sleep	Skill	19k	yesterday	MIT	A	81	Claude Code
eli5companion-inc/feynman	Skill	10k	6d ago	MIT	A	63	Claude Code, Codex
deck-course-modulenexu-io/html-anything	Skill	9.4k	today	Apache-2.0	A	25	Claude Code, Codex