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.
npx skills add JeanDiable/obsidian-claude --skill spaced-reviewgit clone --depth 1 https://github.com/JeanDiable/obsidian-claudeWrote 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.
[](https://agentmods.dev/skills/jeandiable/obsidian-claude/spaced-review)<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.
<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>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 | $0.00010 | $0.00300 |
| Sonnet 5 | $0.00004 | $0.00120 |
| Haiku 4.5 | $0.00002 | $0.00060 |
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 11d 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.
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/iCloudmd~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
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.
- 11d ago First seen · 95 lines · 21 tokens per session scan A 3434d6518d33
spaced-review is a skill published in the GitHub repository JeanDiable/obsidian-claude (2 stars, last pushed 6mo ago), licensed MIT. It adds 21 tokens to every session and 599 once invoked, about $0.0001 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.
Other skills, from other repositories
hr-onboarding
A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".
book-mirror
Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's…
miniapp
Build a tiny interactive HTML playground only when someone asks to see, play with, or step through a mechanism.
eli5
Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.
deck-course-module
A course or workshop slide template with persistent learning goals, teaching pages, multiple-choice self-tests, and a wrap-up.
master-yinguang
A reference-based assistant for questions about Yinguang and Pure Land Buddhism, a Buddhist tradition focused on faith, ethical living, and practice connected with rebirth in the Pure Land. It can answer in Yinguang’s historical teaching style.