Second Brain

Second Brain

An AI-powered knowledge compiler for Obsidian. Drop in scattered notes, get back a structured wiki with bidirectional links, semantic search, and an AI chat that cites your own knowledge.

How It Works

raw/ (your notes)  -->  AI Compile  -->  wiki/ (knowledge base)
   articles               LLM extracts          concepts with [[links]]
   highlights             concepts,             entity pages
   highlights             entities,             source summaries
   highlights             sources               index + mind map

1. Put notes in raw/ — ideally material your mind has already worked through (see Raw folder guide below)
2. Compile — AI extracts concepts, entities, and sources, writes structured wiki pages
3. Browse & Chat — explore your knowledge base or ask questions with cited answers

Incremental compilation: only changed files are re-processed. Subsequent compiles finish in seconds.

Raw folder guide

What to put in raw/: notes that are already yours in a cognitive sense—handwritten or self-authored notes (ideas, paraphrases, reflections), and web clippings only after you have read and absorbed them (e.g. with your own highlights or a line on why the piece matters). raw/ is not meant to be an endless “read later” graveyard.

What “already worked through” means: it does not mean “memorized word for word.” It means you have already paid attention—read (or skimmed with intent), thought about it, and connected it to what you already know or do—so the file is no longer a stranger on disk. Typical signals: you wrote it yourself; or you read someone else’s piece at least once and left a personal trace (highlight, margin note, a one-line takeaway, or “how this relates to project X”). The opposite—saved links you never opened, full clips never read, “might be useful someday” with no concrete use—usually still counts as unprocessed; keep those in read-later or an inbox, and promote into raw/ after they become real input. In one line: information becomes knowledge you helped construct, not just something you filed.

The principle: keep the source layer close to what your brain already holds. The compiler turns raw/ into a linked wiki—a second brain for knowledge you are ready to connect and reuse. If raw/ is mostly unread captures, the wiki can still look busy, but it drifts away from externalized understanding toward automated hoarding—and the whole product goal—building a second brain—starts to skew off course.

Practical habit: park unread links and full-text dumps outside this pipeline (or in a separate inbox). Promote into raw/ once a piece has become real mental input—then compile, so the wiki tracks what you actually think with, not what you merely saved.

Quick Start

Install from Obsidian Community Plugins (Recommended)

1. Open Obsidian Settings → Community Plugins → Browse
2. Search for "Second Brain"
3. Click Install, then Enable

Alternative: Manual Install

Download second-brain.zip from GitHub Releases or Gitee Releases, unzip and open as an Obsidian Vault.

Configure API Key

1. Get an API key from DeepSeek (recommended, ~$0.002/1K tokens)
2. Open plugin settings, enter Provider / Model / API Key
3. Click "Test Connection"

Your API key stays local. Nothing is uploaded.

Compile

• Click the lightning icon in the left sidebar, then "Start Compile"
• Or use the command palette: Cmd/Ctrl+Shift+C
• The first compile processes all files; subsequent runs are incremental

Browse Your Wiki

• Wiki Preview (globe icon) — card index, page viewer, SVG mind map, search
• Wiki Chat (chat icon) — ask questions about your knowledge base, answers cite [[wiki-links]]

Features

All features are free and open source.

Disclosures

• Free and open source: All features are available at no cost (MIT License).
• Network usage: This plugin connects to external LLM APIs (e.g., DeepSeek, OpenAI, Claude) for compilation and chat. API calls are made directly from your device — your notes and API key are never sent to any server other than the LLM provider you configure.
• API key required: You need your own API key from a supported LLM provider. Costs depend on your provider and usage (see Cost Estimate below).

Folder Structure

raw/                        # Your input (immutable)
  01-articles/              # Web clippings, articles
  02-books/                 # Book notes
  03-podcasts/              # Podcast notes
  04-videos/                # Video notes
  05-tweets/                # Tweet threads
  06-flash_notes/           # Flash notes, ideas
    inbox/                  # Staging area (auto-sorted on compile)

wiki/                       # AI-generated output
  concepts/核心概念/         # Core concepts
  concepts/方法框架/         # Methods & frameworks
  concepts/实践经验/         # Practice & experience
  entities/                 # People, companies, tools
  sources/                  # Source summaries
  syntheses/                # Cross-concept analysis
  index.md                  # Auto-generated wiki index
  log.md                    # Compile log + weekly reports

Settings

Cost Estimate

First full compile uses the most tokens. Incremental compiles only process changed files. Typical usage (dozens of notes/month + occasional chat): a $2 DeepSeek balance lasts months.

Notes

• Desktop only (isDesktopOnly: true) — streaming chat requires fetch API
• Wiki cleanup requires typing CONFIRM to prevent accidental deletion

License

MIT

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中文说明

碎片化笔记太多，找不到、连不上、用不起来？Second Brain 是一个 AI 驱动的知识编译器。把散乱的笔记丢进去，它会自动提取概念、实体和知识来源，生成带双向链接、分类索引和语义搜索的结构化 Wiki 知识库。

工作原理

raw/ (你的素材)  -->  AI 编译  -->  wiki/ (知识库)
  文章剪藏              LLM 提取          带 [[双链]] 的概念页
  读书笔记              概念、实体、       实体页面
  播客笔记              知识来源           素材摘要
  闪念笔记                                索引 + 知识图谱

1. 放入素材 -- 把笔记放到 raw/ 目录下；建议以「大脑已经处理过」的内容为主（见下方「素材目录使用指南」）
2. AI 编译 -- LLM 自动提取概念、实体和来源，生成结构化的 Wiki 页面
3. 浏览与对话 -- 浏览知识库，或用 AI 对话功能提问，回答自动引用你的 [[wiki-links]]

支持增量编译：只处理有变化的文件，后续编译几秒完成。

素材目录（raw）使用指南

建议放进 raw/ 的：你自己手写或亲手整理的笔记（想法、转述、复盘），以及已经读过、消化过的网页剪藏（最好带自己的高亮或一两句「这对我意味着什么」）。raw/ 不适合当成无限膨胀的「稍后读」堆场。

什么叫「大脑已经处理过」？ 这里不是指「能背下来、能默写」，而是指你已经用注意力读过、想过，并和自己的经验或任务对上过号——材料不再只是磁盘上的陌生字节。常见情况包括：你自己写下来的内容；或外部文章/视频稿等你至少认真读过一遍，并留下至少一种「个人痕迹」（高亮、批注、用自己的话写两句总结、标明「和我正在做的 X 有什么关系」）。反过来：收藏从未打开、全文剪藏一眼没看、也说不出具体使用场景，多半仍算未处理——更适合先放在稍后读或单独收件箱，升格进 raw/ 应在它真的变成你的输入之后。**一句话：**从「别人的信息」变成「你参与过意义建构的信息」。

核心原则：让 raw 这一层尽量贴近「大脑已经掌握、正在使用的知识」。插件会把 raw/ 编译成带链接的 Wiki，扮演的是第二大脑——用来串联和复用你已经理解的东西。若 raw/ 里多半是未读收藏，输出再漂亮也容易变成囤积自动化，整体目标会从「外显化的理解」悄悄偏成「存了很多但脑里没接上」，建立第二大脑这件事就容易跑偏。

习惯上可以这样分：未读链接、整篇丢进去但还没看的材料，先放在别处或单独收件箱；只有当你真的读进去、变成自己的输入之后，再升格进 raw/ 再编译，这样 Wiki 跟踪的是你在思考时用得上的知识，而不只是你点过保存的文件。

快速开始

从社区插件市场安装（推荐）

1. 打开 Obsidian 设置 → 第三方插件 → 浏览
2. 搜索 "Second Brain"
3. 点击安装，然后启用

手动安装

从 GitHub Releases 或 Gitee 发行版 下载 second-brain.zip，解压后作为 Obsidian Vault 打开。

配置 API Key

1. 在 DeepSeek 开放平台 注册并获取 API Key（推荐，约 0.002 元/千 token）
2. 打开插件设置，填写 Provider / Model / API Key
3. 点击「测试连接」确认可用

API Key 仅保存在本地，不会上传到任何服务器。

编译

• 点击左侧栏的闪电图标，然后点击「开始编译」
• 或使用命令面板快捷键：Cmd/Ctrl+Shift+C
• 首次编译会处理所有文件，后续编译自动增量处理

浏览知识库

• Wiki 浏览器（地球图标）-- 卡片索引、页面阅读器、SVG 知识图谱、搜索
• Wiki 对话（对话图标）-- 针对你的知识库提问，回答自动引用 [[wiki-links]]

功能一览

所有功能免费开源。

披露声明

• 免费开源：所有功能均可免费使用（MIT 许可证）。
• 网络使用：本插件需要连接外部 LLM API（如 DeepSeek、OpenAI、Claude）进行编译和对话。API 请求直接从你的设备发出，笔记和 API Key 不会发送到除你选择的 LLM 提供商之外的任何服务器。
• 需要 API Key：你需要自行获取支持的 LLM 提供商的 API Key。费用取决于你的提供商和用量（见下方费用说明）。

目录结构

raw/                        # 你的输入素材（不可变）
  01-articles/              # 网页剪藏、文章
  02-books/                 # 读书笔记
  03-podcasts/              # 播客笔记
  04-videos/                # 视频笔记
  05-tweets/                # 推文串
  06-flash_notes/           # 闪念笔记、想法
    inbox/                  # 暂存区（编译时自动归类）

wiki/                       # AI 生成的知识库
  concepts/核心概念/         # 核心概念 -- 领域中最基础的观点和立场
  concepts/方法框架/         # 方法框架 -- 用来分析和解决问题的结构化工具
  concepts/实践经验/         # 实践经验 -- 来自真实场景的案例和反思
  entities/                 # 人物、公司、工具、产品
  sources/                  # 素材摘要
  syntheses/                # 跨概念综合分析
  index.md                  # 自动生成的 Wiki 索引
  log.md                    # 编译日志 + 周报

设置项

费用说明

首次全量编译消耗 token 最多，后续增量编译只处理变化文件。日常使用（每月几十条笔记 + 偶尔对话），DeepSeek 充值 10 元可用几个月。

其他说明

• 仅支持桌面端（isDesktopOnly: true）-- 流式对话依赖 fetch API
• 清理 Wiki 需要输入 CONFIRM 确认，防止误删
• 开发者文档（从源码构建、GitHub + Gitee 双托管）请参见 CONTRIBUTING.md

许可证

MIT