second-brain

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Second Brain for AI Agents

为AI Agents打造的第二大脑

Second Brain turns

~/.memory/

into a persistent, hierarchical knowledge store that works across projects and tools. Unlike project-level context files (CLAUDE.md, .cursorrules), Second Brain holds personal, cross-project knowledge - your preferences, learnings, workflows, and domain expertise. It is designed for AI agents: tag-indexed for fast relevance matching, wiki-linked for graph traversal, and capped at 100 lines per file for context-window efficiency.

Second Brain 将

~/.memory/

转化为一个可跨项目和工具使用的持久化、分层式知识存储库。与项目级上下文文件（如CLAUDE.md、.cursorrules）不同，Second Brain存储的是个人跨项目知识——你的偏好、学习成果、工作流和领域专业知识。它专为AI Agents设计：通过标签索引实现快速相关性匹配，支持wiki链接用于图谱遍历，且每个文件限制在100行以内以提升上下文窗口效率。

When to use this skill

何时使用此技能

Trigger this skill when the user:

Starts a new conversation (auto-load relevant memories based on context)
Says "remember this", "save this for later", or "update my memory"
Asks "what do you know about X" or "what are my preferences for Y"
Completes a complex or multi-step task (auto-propose saving learnings)
Needs to set up ~/.memory for the first time (onboarding)
Wants to search, organize, or clean up their memories
Asks about their past learnings, workflows, or preferences

Do NOT trigger this skill for:

Project-specific context (that belongs in CLAUDE.md or similar project files)
Storing sensitive data like passwords, API keys, or tokens

当用户出现以下行为时触发此技能：

开启新对话（基于上下文自动加载相关记忆）
说出“记住这个”“稍后保存这个”或“更新我的记忆”
询问“你知道关于X的什么内容”或“我对Y的偏好是什么”
完成复杂或多步骤任务后（自动提议保存学到的内容）
首次需要设置~/.memory/（新用户引导）
想要搜索、整理或清理他们的记忆
询问过往的学习内容、工作流或偏好

请勿在以下场景触发此技能：

项目特定上下文（应存储在CLAUDE.md或类似项目文件中）
存储敏感数据如密码、API密钥或令牌

Key principles

核心原则

Ask before saving - Never write to ~/.memory without user consent. After complex tasks, propose what to remember and let the user approve before writing. The user owns their memory.
Relevance over completeness - At conversation start, read
```
index.yaml
```
, match tags against the current context, and load only the top 3-5 matching files. Never load all memory files - most won't be relevant and they waste context.
100-line ceiling - Each memory topic file stays under 100 lines (including frontmatter). When a file grows beyond this, split it into sub-files in a subdirectory. This keeps individual loads cheap and forces concise writing.
Cross-project, not project-specific - ~/.memory stores personal knowledge, preferences, and universal learnings. Project-specific rules, configs, and context belong in project-level files like CLAUDE.md.
Tags + wiki-links for navigation - Every memory file has YAML frontmatter with tags for index lookup. Cross-references use
```
[[path/to/file.md]]
```
wiki-links. The root
```
index.yaml
```
maps tags to files for fast retrieval.

保存前询问 - 未经用户同意，绝不要写入~/.memory/。完成复杂任务后，提议要保存的内容，获得用户批准后再写入。用户拥有他们的记忆控制权。
相关性优先于完整性 - 对话开始时，读取
```
index.yaml
```
，将标签与当前上下文匹配，仅加载排名前3-5的匹配文件。绝不要加载所有记忆文件——大多数文件不相关，会浪费上下文窗口。
100行上限 - 每个记忆主题文件（包括前置元数据）不得超过100行。当文件超出此限制时，将其拆分为子目录中的子文件。这样可以降低单个文件的加载成本，同时促使内容保持简洁。
跨项目而非项目特定 - ~/.memory/存储个人知识、偏好和通用学习成果。项目特定规则、配置和上下文应存储在CLAUDE.md等项目级文件中。
标签+wiki链接用于导航 - 每个记忆文件都包含带标签的YAML前置元数据，用于索引查找。交叉引用使用
```
[[path/to/file.md]]
```
格式的wiki链接。根目录下的
```
index.yaml
```
将标签映射到文件，实现快速检索。

Core concepts

核心概念

Directory structure - ~/.memory/ uses a hierarchical layout:

index.yaml

at root as the master registry,

profile.md

for user identity from onboarding, and category directories (e.g.,

coding/

marketing/

) each containing an

index.md

overview and topic-specific

.md

files.

Memory file format - Each

.md

file has YAML frontmatter with

tags

created

updated

, and

links

(wiki-links to related files), followed by a concise markdown body. This is a knowledge dump, not documentation - keep entries terse and scannable.

index.yaml - The master lookup table. Maps tags to file paths, tracks categories, records line counts and last-updated timestamps per file. Always read this first to determine what to load.

Relevance matching - Extract keywords from the current context (working directory, file types, tools, user's stated topic). Score each file's tags against these keywords (exact match = 3 points, partial = 1). Load the top 3-5 scoring files. If nothing scores above threshold, load only

profile.md

Memory lifecycle (CRUSP) - Create (onboarding or post-task save), Read (auto-load or explicit query), Update (append or revise existing entries), Split (when file exceeds 100 lines), Prune (remove stale/outdated entries).

目录结构 - ~/.memory/采用分层布局：根目录下的

index.yaml

作为主注册表，

profile.md

存储新用户引导时收集的用户身份信息，分类目录（如

coding/

、

marketing/

）中各包含一个

index.md

概述文件和主题特定的

.md

文件。

记忆文件格式 - 每个

.md

文件都包含带有

tags

、

created

、

updated

和

links

（指向相关文件的wiki链接）的YAML前置元数据，后面是简洁的Markdown正文。这是知识 Dump，而非正式文档——内容应简洁、易于扫描。

index.yaml - 主查找表。将标签映射到文件路径，跟踪分类，记录每个文件的行数和最后更新时间戳。始终先读取此文件以确定要加载的内容。

相关性匹配 - 从当前上下文（工作目录、文件类型、使用的工具、用户明确提及的主题）中提取关键词。将每个文件的标签与这些关键词匹配打分（完全匹配=3分，部分匹配=1分）。加载排名前3-5的高分文件。如果没有文件超过阈值，则仅加载

profile.md

。

记忆生命周期（CRUSP） - 创建（新用户引导或任务后保存）、读取（自动加载或显式查询）、更新（追加或修订现有条目）、拆分（文件超出100行时）、清理（移除过期/过时条目）。

Common tasks

常见任务

First-run onboarding

首次运行引导

Detect first run by checking if

~/.memory/

exists and contains

index.yaml

. If missing, run a structured interview with 7 questions covering work domains, tools, communication style, active projects, workflows, learning goals, and golden rules. Use answers to bootstrap the directory structure: create

index.yaml

profile.md

, category directories with

index.md

files, and initial topic files.

See

references/onboarding.md

for the full question set, bootstrapping templates, and a worked example.

通过检查

~/.memory/

是否存在且包含

index.yaml

来判断是否为首次运行。如果缺失，进行包含7个问题的结构化访谈，涵盖工作领域、使用工具、沟通风格、活跃项目、工作流、学习目标和黄金规则。根据回答初始化目录结构：创建

index.yaml

、

profile.md

、带

index.md

文件的分类目录，以及初始主题文件。

查看

references/onboarding.md

获取完整问题集、初始化模板和示例。

Auto-load relevant memories at conversation start

对话启动时自动加载相关记忆

Read
```
~/.memory/index.yaml
```
Extract keywords from current context: project name, file extensions being edited, tools/frameworks mentioned, user's explicit topic
Match keywords against the
```
tags
```
map in index.yaml
Score matches: exact tag hit = 3 points, substring match = 1 point
Load the top 3-5 scoring files (read their content into context)
If no files score above threshold, load only
```
profile.md
```
as baseline
Briefly note which memories were loaded so the user knows what context is active

读取
```
~/.memory/index.yaml
```
从当前上下文提取关键词：项目名称、正在编辑的文件扩展名、提及的工具/框架、用户明确的主题
将关键词与index.yaml中的
```
tags
```
映射进行匹配
匹配打分：完全匹配标签=3分，子串匹配=1分
加载排名前3-5的高分文件（将内容读入上下文）
如果没有文件超过阈值，仅加载
```
profile.md
```
作为基线
简要告知用户加载了哪些记忆，让用户了解当前激活的上下文

User-initiated save ("remember this")

用户发起的保存（“记住这个”）

When the user says "remember this" or similar:

Identify what to remember from the conversation
Determine the right category - check existing categories in index.yaml first; if ambiguous, ask the user
Check if a relevant topic file already exists in that category
If yes: append the new knowledge to the existing file (check 100-line limit)
If no: create a new file with proper YAML frontmatter (tags, timestamps, links)
Update
```
index.yaml
```
with new tags and file metadata
Scan existing files for related tags and add
```
[[wiki-links]]
```
if appropriate

当用户说“记住这个”或类似表述时：

从对话中确定要保存的内容
确定合适的分类——先检查index.yaml中的现有分类；如果不明确，询问用户
检查该分类中是否已存在相关主题文件
如果存在：将新知识追加到现有文件中（检查100行限制）
如果不存在：创建带有正确YAML前置元数据（标签、时间戳、链接）的新文件
更新
```
index.yaml
```
中的新标签和文件元数据
扫描现有文件查找相关标签，如有需要添加
```
[[wiki-links]]
```

Auto-propose learnings after complex task

复杂任务后自动提议保存学习内容

After completing a multi-step or complex task, identify learnable patterns:

New tool configurations or setup steps discovered
Debugging techniques that worked
Workflow preferences revealed during the task
Domain knowledge gained

Present the proposed memories to the user in a concise summary. Include which file each would be saved to. Only write on explicit user approval. Never save silently.

完成多步骤或复杂任务后，识别可学习的模式：

发现的新工具配置或设置步骤
有效的调试技巧
任务过程中展现的工作流偏好
获得的领域知识

以简洁摘要的形式向用户展示提议保存的内容，包括每个内容将保存到哪个文件。仅在获得用户明确批准后再写入，绝不要静默保存。

Search memories ("what do you know about X")

搜索记忆（“你知道关于X的什么内容”）

Search
```
index.yaml
```
tags for matches against the query
If tag matches found: read those files and present relevant excerpts
If no tag match: do a content search across all memory files as fallback
Present results with source file paths so user can verify or update
Offer to update, correct, or prune any found memories

在
```
index.yaml
```
的标签中搜索与查询匹配的内容
如果找到匹配标签：读取这些文件并展示相关摘录
如果没有标签匹配：作为备选方案，在所有记忆文件中进行内容搜索
展示结果时附带源文件路径，方便用户验证或更新
提供更新、修正或清理找到的记忆的选项

Split an oversized memory file

拆分过大的记忆文件

When a file exceeds 100 lines:

Propose a split to the user - identify 2-4 natural sub-topics
Create a subdirectory named after the original file (without extension)
Move each sub-topic into its own file within the subdirectory
Replace the original file with an
```
index.md
```
linking to the sub-files
Update all
```
[[wiki-links]]
```
across ~/.memory that pointed to the old file
Update
```
index.yaml
```
with the new file paths and tags

See

references/maintenance.md

for the detailed splitting protocol.

当文件超过100行时：

向用户提议拆分——确定2-4个自然的子主题
创建以原文件名（不含扩展名）命名的子目录
将每个子主题移动到子目录中的独立文件
用指向子文件的
```
index.md
```
替换原文件
更新~/.memory/中所有指向原文件的
```
[[wiki-links]]
```
更新
```
index.yaml
```
中的新文件路径和标签

查看

references/maintenance.md

获取详细的拆分流程。

Handle conflicting or outdated memories

处理冲突或过时的记忆

When new information contradicts an existing memory:

Flag the conflict - show the existing memory and the new information
Ask the user which version is correct
Update the file with the correct version; set a new
```
updated
```
timestamp
Optionally add a
```
supersedes
```
note in frontmatter to track the change
If the old memory was cross-referenced, check if linked files need updates

当新信息与现有记忆冲突时：

标记冲突——展示现有记忆和新信息
询问用户哪个版本正确
用正确版本更新文件；设置新的
```
updated
```
时间戳
可选择在前置元数据中添加
```
supersedes
```
注释以跟踪变更
如果旧记忆被交叉引用，检查相关文件是否需要更新

Anti-patterns / common mistakes

反模式/常见错误

Mistake	Why it's wrong	What to do instead
Storing passwords, API keys, or tokens	Memory files are plaintext, readable by any tool	Use env vars, keychains, or secret managers
Duplicating project-specific context	~/.memory and CLAUDE.md serve different purposes	Project rules in CLAUDE.md; personal knowledge in ~/.memory
Loading all memory files at start	Wastes context window; most files won't be relevant	Load only tag-matched files; max 3-5 per conversation
Saving without user approval	User may not want everything remembered	Always propose and get explicit approval first
Saving obvious or generic knowledge	"Python is interpreted" wastes space	Only store personal preferences, specific learnings, non-obvious patterns
Letting files grow past 100 lines	Large files defeat the purpose of selective loading	Split into sub-topic files in a subdirectory
Ignoring timestamps	Stale memories can mislead future sessions	Always set `updated` timestamp; periodically review old entries

错误行为	错误原因	正确做法
存储密码、API密钥或令牌	记忆文件是明文，任何工具都可读取	使用环境变量、密钥链或密钥管理器
重复存储项目特定上下文	~/.memory/和CLAUDE.md的用途不同	项目规则存储在CLAUDE.md中；个人知识存储在~/.memory/中
对话启动时加载所有记忆文件	浪费上下文窗口；大多数文件不相关	仅加载标签匹配的文件；每次对话最多加载3-5个
未经用户同意保存内容	用户可能不想记住所有内容	始终先提议并获得明确批准
保存明显或通用知识	“Python是解释型语言”这类内容浪费空间	仅存储个人偏好、特定学习成果、非显而易见的模式
允许文件超过100行	大文件违背了选择性加载的初衷	拆分为子目录中的子主题文件
忽略时间戳	过时的记忆可能误导未来会话	始终设置 `updated` 时间戳；定期检查旧条目

References

参考资料

For detailed specs and workflows, read the relevant file from

references/

```
references/onboarding.md
```
- Full onboarding interview questions, bootstrapping templates, and worked example. Load when setting up ~/.memory for a new user.
```
references/memory-format.md
```
- index.yaml schema, memory file format spec, wiki-link resolution, and profile.md template. Load when creating or updating files.
```
references/maintenance.md
```
- File splitting protocol, pruning strategy, relevance matching algorithm details, and index rebuild procedure. Load for memory cleanup tasks.

Only load a references file if the current task requires it.

如需详细规范和工作流，请查看

references/

中的相关文件：

```
references/onboarding.md
```
- 完整的新用户引导访谈问题、初始化模板和示例。为新用户设置~/.memory/时加载此文件。
```
references/memory-format.md
```
- index.yaml schema、记忆文件格式规范、wiki链接解析和profile.md模板。创建或更新文件时加载此文件。
```
references/maintenance.md
```
- 文件拆分流程、清理策略、相关性匹配算法细节和索引重建步骤。进行记忆清理任务时加载此文件。

仅在当前任务需要时加载参考文件。