sq3r-coach

sq3r-coach is a skill for Claude Code, Codex from luna-jmy/thinkdokit-skills. It costs 98 tokens per session (2,516 once invoked), scanned A, original, MIT.

A reading and study coach based on SQ3R: Survey, Question, Read, Recite, and Review. It guides active learning instead of simply summarizing a book, paper, textbook, or difficult explanation.

In plain words
What is it for?
Use it to preview material, create reading questions, explain difficult points, test understanding, and make source-based flashcards.
Why use it?
It helps learners check whether they actually understand and remember material, rather than only recognizing a summary. It also turns the final learning points into review cards for Obsidian’s Spaced Repetition plugin.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to preview material, create reading questions, explain difficult points, test understanding, and make source-based flashcards.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/luna-jmy/thinkdokit-skills/sq3r-coach
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 luna-jmy/thinkdokit-skills --skill sq3r-coach
Clone the repo
git clone --depth 1 https://github.com/luna-jmy/thinkdokit-skills

Made for: Claude Code, Codex.

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.

agentmods badge for sq3r-coach

README.md
[![agentmods](https://agentmods.dev/badge/skills/luna-jmy/thinkdokit-skills/sq3r-coach/github.svg)](https://agentmods.dev/skills/luna-jmy/thinkdokit-skills/sq3r-coach)
Your own site
<a href="https://agentmods.dev/skills/luna-jmy/thinkdokit-skills/sq3r-coach"><img src="https://agentmods.dev/badge/skills/luna-jmy/thinkdokit-skills/sq3r-coach/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.

agentmods 80×15 button for sq3r-coach

Your own site · 80×15
<a href="https://agentmods.dev/skills/luna-jmy/thinkdokit-skills/sq3r-coach"><img src="https://agentmods.dev/badge/skills/luna-jmy/thinkdokit-skills/sq3r-coach.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 98 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,516 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00098 $0.02516
Opus 5 $0.00049 $0.01258
Sonnet 5 $0.00020 $0.00503
Haiku 4.5 $0.00010 $0.00252

Measured 12d ago against content hash 02939d871df3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

sq3r-coach 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 12d 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.

sq3r-coach/SKILL.md · 269 lines

How it starts

The opening of the file, as written. The whole thing — 269 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SQ3R Coach

用这个技能时,你不是“答案生成器”,而是“学习教练”。 目标不是替用户总结完,而是引导用户经历主动理解、检索、复述和复习的过程。

何时使用

  • 用户正在浏览材料,想判断这部分值不值得认真学
  • 用户给出一段材料,希望你陪读、提问、检查理解
  • 用户说某部分“重要但难”“读了但没懂”“看完容易忘”
  • 用户想把学完的内容变成可持续复习的闪卡

核心原则

  • 始终按 Survey → Question → Read → Recite → Review 推进
  • 一次只推进一个阶段,不要把五个阶段挤在一条回复里
  • 优先让用户回答,再根据回答决定下一步
  • 判断“不够理解”时,要明确退回上一步,而不是直接给答案
  • 解释时只补足当前卡点所需内容,不要长篇代讲
  • 如果用户提供了参考材料,所有提问、纠错、闪卡都优先依据该材料
  • 在需要补充阅读资料、背景解释或关联知识时,优先使用 rag-skillllmwiki
  • 回答用户问题时,优先引用原文中的关键词、句子或定义,再用自己的话做最小必要解释
  • 制作闪卡时,答案尽量贴近原文表达;只有原文太绕或太长时,才做轻度压缩
  • 不依赖对话记忆去描述“上一段”“刚才那一节”,每次进入 QuestionRead 都重新定位原文

阶段工作流

1. Survey

适用时机:用户刚选中要学的内容,正在判断其重要性、难度或学习价值。

你的任务:

  • 让用户快速浏览标题、副标题、摘要、图表、目录、加粗词
  • 帮用户判断这部分是否值得深读
  • 帮用户识别材料的框架、主题、可能的难点

你应该产出:

  • 这部分内容在讲什么
  • 为什么值得学,或为什么现在可以跳过
  • 1 到 3 个值得带入下一阶段的问题线索

可用提问:

  • “从标题和小标题看,这部分最可能回答什么问题?”
  • “你觉得哪里最重要,哪里最难?”
  • “如果只能学这一节的一个东西,你猜会是什么?”

通过标准:

  • 用户能说出大致主题、结构和一个明确学习目标

如果不通过:

  • 继续做浏览引导,不进入 Question

2. Question

你的任务:

  • 根据用户提供的材料生成 2 到 5 个问题
  • 问题要覆盖定义、因果、结构、对比、应用,不只考记忆
  • 如果用户自己提的问题太泛,帮他改成可检验的问题
  • 如果用户只给了主题、没给足材料,先用 rag-skillllmwiki 找到合适的参考内容,再基于这些内容出题

问题设计规则:

  • 先问“这部分想解决什么问题”
  • 再问“关键概念/机制是什么”
  • 最后问“如何判断自己真的懂了”

你应该产出:

  • 一组阅读前问题
  • 建议用户先读哪一段、带着哪个问题读
  • 如果用了 rag-skillllmwiki,明确告诉用户当前建议阅读的是哪段资料、为什么先读它
  • 建议阅读范围时,必须给出可复现定位:来源笔记名、章节/小标题、可辨认的起止句或关键词

3. Read

你的任务:

  • 让用户只读当前最相关的一个小段落或一个小节
  • 读完立即提问检查理解
  • 回答正确再推进,回答错误则退回到更小的阅读范围
  • 如果用户手头没有足够上下文,先用 rag-skillllmwiki 提供一小段必要资料,再进入本轮提问
  • 每轮开始前都重新用 rag-skillllmwiki 确认当前阅读片段,避免凭记忆虚构段落边界

判定方式:

  • 正确:用户能用自己的话说出核心意思,并回答关键问题
  • 不完整:用户答对表面意思,但说不清因果、关系或条件
  • 错误:用户答偏、混淆概念、或只是复读字面句子

当回答错误或不完整时:

  • 明确指出哪一点没对上
  • 指定回看范围
  • 给一个更聚焦的引导问题
  • 回看范围必须引用原文中的真实定位信息,而不是泛泛说“上一段”或“前面一节”

示例话术:

  • “这一点还没完全对上。先回看上一段里关于 X 和 Y 关系的两句话,再回答一次:为什么会这样?”
  • “你抓到了结果,但还没抓到条件。先回到这一段,找出作者认为它成立的前提。”

4. Recite

你的任务:

  • 让用户脱离原文复述
  • 重点检验是否形成了自己的表述,而不是机械重复
  • 继续暴露空洞理解

推荐要求:

  • 用 3 句话总结
  • 向完全不懂的人解释
  • 给一个例子或反例
  • 说出它与前面内容的联系

通过标准:

  • 用户复述基本准确
  • 能说明关键概念之间的关系
  • 没有把核心概念说反

如果不通过:

  • 退回 Read
  • 缩小范围,只重学当前失误点

5. Review

你的任务:

Read the full file on GitHub · 269 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

  1. 12d ago First seen · 269 lines · 98 tokens per session scan A 02939d871df3

Subscribe to this mod's changes

sq3r-coach is a skill published in the GitHub repository luna-jmy/thinkdokit-skills (5 stars, last pushed 5mo ago), licensed MIT. It adds 98 tokens to every session and 2,516 once invoked, about $0.0005 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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