npx skills add https://github.com/theagentledger/agent-skills --skill 'Learning Journal'作者:The Agent Ledger — 为那些消费多于留存的人设计的 AI 原生学习系统。
您的智能体追踪您正在学习的内容,提示您回顾关键概念,并确保知识真正扎根 — 并得到应用。
您每周阅读 30 篇文章。您收听播客。您参加课程。但 3 个月后,您却无法回忆起那本“改变一切”的书籍中的关键见解。大多数人的消费与留存比率非常糟糕。
这项技能将您的 AI 智能体转变为一个学习伙伴,能够随时间推移捕获、组织、回顾和连接知识。
在您的工作区中创建 learning/learning-state.md:
# 学习状态
## 活跃学习轨道
| 轨道 | 类型 | 来源 | 开始日期 | 进度 | 优先级 |
|-------|------|--------|---------|----------|----------|
| [主题] | 书籍 | [书名 作者] | YYYY-MM-DD | 35% | 高 |
| [主题] | 课程 | [课程名称 — 平台] | YYYY-MM-DD | 60% | 中 |
| [主题] | 自主学习 | [描述] | YYYY-MM-DD | 进行中 | 低 |
## 学习目标(本季度)
1. [完成 X] — 截止日期:[日期]
2. [充分理解 Y 以便 Z] — 无截止日期,但有优先级
3. [建立 Z 技能] — 可衡量:[证明标准]
## 回顾计划
- 每日:快速回顾昨天的捕获内容(2 分钟)
- 每周:全面回顾 + 连接到现有知识(15 分钟)
- 每月:对旧材料进行留存检查
创建 learning/captures/ 用于存放单独的学习笔记。每个来源一个文件:
# [来源标题]
**类型:** 书籍 / 文章 / 课程 / 播客 / 视频 / 经验
**作者/创作者:** [姓名]
**捕获日期:** YYYY-MM-DD
**状态:** 阅读中 / 已完成 / 已放弃
**评分:** [1-5] 价值程度
## 关键要点
1. [最重要的见解]
2. [第二重要的见解]
3. [第三重要的见解]
## 难忘的引述
> "[引述]" — [上下文/页码]
## 这如何应用于我的工作
- [对您的项目/业务的具体应用]
- [与您已知内容的联系]
## 它引发的问题
- [您想进一步探索的事情]
## 回顾历史
| 日期 | 回忆分数 | 备注 |
|------|-------------|-------|
| YYYY-MM-DD | 4/5 | 记住了核心论点,细节模糊 |
## 学习
- 当我分享文章、书籍笔记或学习内容时,将其捕获到 `learning/captures/`
- 在每周回顾期间,提示我回顾到期的项目
- 在相关时,将新学习内容连接到现有捕获
- 在 `learning/learning-state.md` 中追踪我的学习目标
- 当我超过 30 天未重新访问高价值捕获时,建议回顾
智能体创建一个捕获文件,提出有针对性的问题以提取关键要点:
智能体使用新条目更新 learning-state.md,并根据当前目标和活跃轨道建议优先级。
智能体检查所有捕获的回顾日期并显示:
智能体在现有捕获中搜索相关概念并显示连接:
## 发现的连接
- **[新捕获]** 与 **[现有捕获]** 相关
- 共享概念:[它们的共同点]
- 矛盾点:[它们的分歧或提供不同视角之处]
- 综合见解:[将两者结合得到的收获]
每周格式:
## 每周学习回顾 — [日期]
### 本周捕获
| 来源 | 类型 | 评分 | 关键见解 |
|--------|------|--------|-------------|
| [标题] | 文章 | 4/5 | [一句话总结] |
### 回顾提示(间隔重复)
1. **[7 天前的捕获]:** 您能回忆起主要论点吗?[是/否 → 更新回忆分数]
2. **[30 天前的捕获]:** 关键要点是什么?[是/否]
3. **[90 天前的捕获]:** 这如何影响了您的思考?[反思]
### 学习轨道进度
| 轨道 | 上周 | 本周 | 备注 |
|-------|-----------|-----------|-------|
| [主题] | 35% | 42% | 阅读了第 8-10 章 |
### 本周应用
- 将 [来自 X 的概念] 应用于 [项目/决策]
- [来自 Y 的概念] 与我关于 [Z] 的假设相矛盾
### 下周重点
- 优先阅读:[需要关注的内容]
- 到期回顾:[N 个项目需要重新访问]
智能体根据捕获内容生成问题以测试留存:
智能体搜索所有关于某个主题的捕获并进行综合:
## 知识摘要:[主题]
### 来源(按时间顺序)
1. [来源 1] — [日期] — 关键点:[...]
2. [来源 2] — [日期] — 关键点:[...]
### 综合理解
[您对该主题的了解,综合所有来源]
### 思维演变
- 最初认为:[较早的捕获]
- 现在认为:[较晚的捕获,更新的观点]
### 空白点
- 仍不清楚:[遗留的问题]
- 应阅读:[建议的后续来源]
该技能使用简单的间隔重复系统:
| 回顾 | 之后 | 目的 |
|---|---|---|
| 第一次 | 1 天 | 立即回忆检查 |
| 第二次 | 7 天 | 短期留存 |
| 第三次 | 30 天 | 中期留存 |
| 第四次 | 90 天 | 长期留存 |
| 持续 | 180 天 | 如果仍然相关则刷新 |
每次回顾更新回忆分数(1-5):
得分为 1-2 的项目将被移到更短的回顾周期。持续得分为 5 的项目可以标记为“已内化”并从活跃回顾中移除。
## 阅读列表
### 正在阅读
| # | 标题 | 作者 | 类型 | 开始日期 | 进度 | 优先级 |
|---|-------|--------|------|---------|----------|----------|
| 1 | [书籍] | [作者] | 书籍 | 3/1 | 45% | 🔴 高 |
| 2 | [课程] | [平台] | 课程 | 2/15 | 80% | 🟡 中 |
### 接下来(已排序)
| # | 标题 | 作者 | 类型 | 原因 | 添加日期 |
|---|-------|--------|------|-----|-------|
| 1 | [书籍] | [作者] | 书籍 | [原因/推荐] | 2/28 |
| 2 | [课程] | [平台] | 课程 | [原因] | 3/1 |
### 已完成(最近 90 天)
| 标题 | 类型 | 评分 | 捕获? | 关键见解 |
|-------|------|--------|----------|-------------|
| [书籍] | 书籍 | 4/5 | ✅ | [一句话总结] |
### 已放弃
| 标题 | 类型 | 放弃原因 | 值得重访? |
|-------|------|--------------|-------------------|
| [书籍] | 书籍 | 对于当前水平太基础 | 否 |
根据您的学习方式调整捕获格式:
为常见来源类型创建捕获模板:
追踪跨学习领域的广度:
## 知识地图
| 领域 | 捕获数 | 最后活跃 | 深度 |
|--------|----------|-------------|-------|
| 商业策略 | 12 | 2 天前 | 深入 |
| 机器学习 | 3 | 45 天前 | 表面 |
| 写作 | 7 | 10 天前 | 中等 |
| 金融 | 15 | 1 天前 | 深入 |
| 技能 | 集成 |
|---|---|
| goal-tracker | 将学习目标作为季度 OKR;将捕获进度作为 KR 更新 |
| research-assistant | 研究发现自动捕获为学习条目 |
| content-calendar | 将高价值捕获转化为内容(教授所学) |
| writing-assistant | 使用捕获作为文章和帖子的素材 |
| decision-log | 在决策时参考相关学习内容 |
| habit-tracker | 将每日阅读/学习作为习惯追踪 |
添加到 HEARTBEAT.md:
## 学习检查
- 是否有任何捕获到期进行间隔重复回顾?
- 距离上次捕获是否超过 7 天?(消费而不捕获 = 浪费)
- 是否有任何学习轨道停滞超过 14 天?
| 问题 | 解决方法 |
|---|---|
| 捕获内容过长 | 最多限制为 3 个关键要点;深度内容放在参考文献中 |
| 从不回顾 | 设置每周回顾提示的 cron;开始时只处理 3 个项目 |
| 活跃轨道过多 | 同时进行上限为 3 个;在开始新的之前完成或暂停 |
| 捕获感觉无用 | 专注于“如何应用”部分 — 如果无法填写,该来源可能没有价值 |
| 阅读列表无限增长 | 每月清理:移除添加超过 60 天且尚未开始的项目 |
| 什么都记不住 | 前 30 天正常;间隔重复需要 2-3 个周期才能生效 |
由 The Agent Ledger 开发的 Agent Skills Collection 的一部分。 在 theagentledger.com 订阅以获取高级指南和新技能。
每周安装次数
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安全审计
ByThe Agent Ledger — AI-native learning system for people who consume more than they retain.
Your agent tracks what you're learning, prompts you to review key concepts, and makes sure knowledge actually sticks — and gets applied.
You read 30 articles a week. You listen to podcasts. You take courses. But 3 months later, you can't recall the key insight from that book that "changed everything." The consumption-to-retention ratio for most people is terrible.
This skill turns your AI agent into a learning partner that captures, organizes, reviews, and connects knowledge over time.
Create learning/learning-state.md in your workspace:
# Learning State
## Active Learning Tracks
| Track | Type | Source | Started | Progress | Priority |
|-------|------|--------|---------|----------|----------|
| [Topic] | Book | [Title by Author] | YYYY-MM-DD | 35% | High |
| [Topic] | Course | [Course name — platform] | YYYY-MM-DD | 60% | Medium |
| [Topic] | Self-directed | [Description] | YYYY-MM-DD | Ongoing | Low |
## Learning Goals (This Quarter)
1. [Finish X] — deadline: [date]
2. [Understand Y well enough to Z] — no deadline, but priority
3. [Build skill in Z] — measurable: [what would prove it]
## Review Schedule
- Daily: Quick review of yesterday's captures (2 min)
- Weekly: Full review + connect to existing knowledge (15 min)
- Monthly: Retention check on older material
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Create learning/captures/ for individual learning notes. One file per source:
# [Source Title]
**Type:** Book / Article / Course / Podcast / Video / Experience
**Author/Creator:** [name]
**Date captured:** YYYY-MM-DD
**Status:** Reading / Completed / Abandoned
**Rating:** [1-5] how valuable
## Key Takeaways
1. [Most important insight]
2. [Second most important]
3. [Third]
## Memorable Quotes
> "[Quote]" — [context/page]
## How This Applies to My Work
- [Specific application to your projects/business]
- [Connection to something you already know]
## Questions It Raised
- [Things you want to explore further]
## Review History
| Date | Recall Score | Notes |
|------|-------------|-------|
| YYYY-MM-DD | 4/5 | Remembered core thesis, fuzzy on details |
## Learning
- When I share an article, book note, or learning, capture it in `learning/captures/`
- During weekly reviews, prompt me on items due for review
- Connect new learnings to existing captures when relevant
- Track my learning goals in `learning/learning-state.md`
- Suggest review when I haven't revisited a high-value capture in 30+ days
Agent creates a capture file, asks targeted questions to extract key takeaways:
Agent updates learning-state.md with new entry, suggests priority based on current goals and active tracks.
Agent checks review dates across captures and surfaces:
Agent searches existing captures for related concepts and shows connections:
## Connections Found
- **[New capture]** relates to **[Existing capture]**
- Shared concept: [what they have in common]
- Tension: [where they disagree or offer different perspectives]
- Combined insight: [what you get from both together]
Weekly format:
## Weekly Learning Review — [Date]
### This Week's Captures
| Source | Type | Rating | Key Insight |
|--------|------|--------|-------------|
| [Title] | Article | 4/5 | [One-liner] |
### Review Prompts (Spaced Repetition)
1. **[Capture from 7 days ago]:** Can you recall the main argument? [Y/N → update recall score]
2. **[Capture from 30 days ago]:** What was the key takeaway? [Y/N]
3. **[Capture from 90 days ago]:** How has this influenced your thinking? [Reflect]
### Learning Track Progress
| Track | Last Week | This Week | Notes |
|-------|-----------|-----------|-------|
| [Topic] | 35% | 42% | Read chapters 8-10 |
### Applications This Week
- Applied [concept from X] to [project/decision]
- [Concept from Y] contradicted my assumption about [Z]
### Next Week Focus
- Priority reading: [what to focus on]
- Review due: [N items need revisiting]
Agent generates questions from a capture to test retention:
Agent searches all captures for a topic and synthesizes:
## Knowledge Summary: [Topic]
### Sources (chronological)
1. [Source 1] — [date] — Key point: [...]
2. [Source 2] — [date] — Key point: [...]
### Synthesized Understanding
[What you know about this topic, combining all sources]
### Evolution of Thinking
- Initially thought: [earlier captures]
- Now believe: [later captures, updated views]
### Gaps
- Still unclear on: [questions that remain]
- Should read: [suggested next sources]
The skill uses a simple spaced repetition system:
| Review | After | Purpose |
|---|---|---|
| First | 1 day | Immediate recall check |
| Second | 7 days | Short-term retention |
| Third | 30 days | Medium-term retention |
| Fourth | 90 days | Long-term retention |
| Ongoing | 180 days | Refresh if still relevant |
Each review updates the recall score (1-5):
Items scoring 1-2 get moved to a shorter review cycle. Items scoring 5 consistently can be marked "internalized" and removed from active review.
## Reading List
### Currently Reading
| # | Title | Author | Type | Started | Progress | Priority |
|---|-------|--------|------|---------|----------|----------|
| 1 | [Book] | [Author] | Book | 3/1 | 45% | 🔴 High |
| 2 | [Course] | [Platform] | Course | 2/15 | 80% | 🟡 Medium |
### Up Next (Prioritized)
| # | Title | Author | Type | Why | Added |
|---|-------|--------|------|-----|-------|
| 1 | [Book] | [Author] | Book | [Reason/recommendation] | 2/28 |
| 2 | [Course] | [Platform] | Course | [Reason] | 3/1 |
### Completed (Last 90 Days)
| Title | Type | Rating | Capture? | Key Insight |
|-------|------|--------|----------|-------------|
| [Book] | Book | 4/5 | ✅ | [One-liner] |
### Abandoned
| Title | Type | Why Abandoned | Worth Revisiting? |
|-------|------|--------------|-------------------|
| [Book] | Book | Too basic for current level | No |
Adapt capture format to how you learn:
Create capture templates for common source types:
Track breadth across learning domains:
## Knowledge Map
| Domain | Captures | Last Active | Depth |
|--------|----------|-------------|-------|
| Business strategy | 12 | 2 days ago | Deep |
| Machine learning | 3 | 45 days ago | Surface |
| Writing | 7 | 10 days ago | Moderate |
| Finance | 15 | 1 day ago | Deep |
| Skill | Integration |
|---|---|
| goal-tracker | Learning goals as quarterly OKRs; capture progress as KR updates |
| research-assistant | Research findings auto-captured as learning entries |
| content-calendar | Turn high-value captures into content (teach what you learn) |
| writing-assistant | Use captures as source material for articles and posts |
| decision-log | Reference relevant learnings when making decisions |
| habit-tracker | Track daily reading/learning as a habit |
Add to HEARTBEAT.md:
## Learning Check
- Any captures due for spaced repetition review?
- Has it been >7 days since last capture? (consumption without capture = waste)
- Any learning tracks stalled for >14 days?
| Issue | Fix |
|---|---|
| Captures too long | Limit to 3 key takeaways max; depth goes in references |
| Never reviewing | Set up cron for weekly review prompt; start with just 3 items |
| Too many active tracks | Cap at 3 simultaneous; finish or pause before starting new ones |
| Captures feel useless | Focus "How This Applies" section — if you can't fill it, the source may not be valuable |
| Reading list growing forever | Monthly prune: remove anything added 60+ days ago that you haven't started |
| Can't recall anything | Normal for first 30 days; spaced repetition needs 2-3 cycles to work |
Part of theAgent Skills Collection by The Agent Ledger. Subscribe attheagentledger.com for the premium guide and new skills.
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