Token导航 LogoToken导航

Agent Skill · 研究检索

second-brain(第二大脑)

second-brain 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

second-brain 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 68,884。

总安装 222周安装 9GitHub Stars 公开资料未说明下载 70核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:second-brain(第二大脑)
来源仓库:https://github.com/leegonzales/aiskills
仓库路径:skills/second-brain
安装命令:
npx skills add leegonzales/aiskills --skill "second-brain"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add leegonzales/aiskills --skill "second-brain"

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

扩展第二大脑知识库,支持长期记忆与联想检索。适用于个人知识管理系统与创意激发场景。使用 GitHub 安装,命令见原始 README。需定期同步与清理以确保信息时效性。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

second-brain 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/second-brain

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add leegonzales/aiskills --skill "second-brain";命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

second-brain 怎么安装?

在终端执行 npx skills add leegonzales/aiskills --skill "second-brain"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

second-brain 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

second-brain 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

second-brain 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

second-brain 用的人多吗?

公开数据是累计安装 222 次,近一周安装 9 次,下载 70 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

second-brain 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
second-brain

第二大脑 · 本页

222—需要联网MIT未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
second-brain
description
Personal intelligence system for capturing thoughts, managing knowledge, and surfacing insights. Use when user wants to capture an idea, task, or note during conversation; query their knowledge base; check their inbox; review digests; or update task status. Triggers include "remember this," "add a task," "what did I say about," "show my inbox," or "mark complete.
license
MIT

Second Brain Skill

Conversational interface to the Second Brain personal knowledge management system. Capture thoughts naturally during Claude Code sessions, query your knowledge graph, and manage your inbox.

Core Philosophy

Capture at the point of thinking, not after.

This skill enables seamless capture during work sessions without breaking flow:

  • Capture thoughts as they emerge
  • Query past decisions and notes
  • Surface today's priorities
  • Track what needs review

The system remembers so you don't have to.


Core Capabilities

1. Capture

Capture thoughts, tasks, ideas, and references directly from conversation.

Usage patterns:

  • "Remember that the API rate limit is 1000 req/min"
  • "Add a task to review the PR from Sarah"
  • "Note: decided to use Supabase for sync"
  • "Capture this idea: what if we..."

Classification: The system uses AI to classify captures into types:

  • task: Actionable item with completion state
  • idea: Non-actionable insight worth remembering
  • reference: Information for later retrieval
  • meeting: Time-bound event with notes
  • goal: Outcome you're working toward
  • project: Collection of related work
  • value: Core principle that guides decisions
  • person: Relationship context

Confidence threshold:

  • High confidence (≥0.6): Auto-classified
  • Low confidence (<0.6): Sent to needs_review

2. Query

Search and explore your knowledge graph.

Usage patterns:

  • "What did I say about authentication?"
  • "What projects support the 'shipping velocity' goal?"
  • "Show me tasks related to the SecondBrain project"
  • "Who did I meet with about the budget?"

Query types:

  • Semantic search: Find by meaning, not just keywords
  • Graph traversal: Follow relationships (supports, blocks, contains)
  • Filter by type: "Show me all ideas from this week"
  • Filter by domain: "What work tasks are due?"

3. Inbox

Review and triage pending captures.

Usage patterns:

  • "Show my inbox"
  • "What's waiting for review?"
  • "How many pending captures?"

Inbox states:

  • pending: Awaiting AI classification
  • needs_review: Low confidence, needs human decision
  • processing: Currently being classified

4. Digest

Get actionable summaries of what matters.

Usage patterns:

  • "What should I focus on today?"
  • "Show me today's digest"
  • "What's overdue?"

Digest includes:

  • Due tasks (today and overdue)
  • High priority items
  • Today's meetings
  • Items needing review
  • Recent insights

Constraints:

  • Daily digest: <150 words
  • Weekly review: <250 words

5. Actions

Update status and manage nodes.

Usage patterns:

  • "Mark the PR review task done"
  • "Complete task abc123"
  • "Archive the old project"
  • "Set priority to high for..."

Supported actions:

  • Complete/reopen tasks
  • Update priority (0-4)
  • Change status (active, completed, archived)
  • Add domain tag (work, personal, both)

Workflow Integration

During Work Sessions

When user mentions something capture-worthy during natural conversation:

  1. Recognize capture intent:

- Direct: "Remember this...", "Add a task..." - Implicit: "I should...", "Don't forget...", "Note to self..."

  1. Capture with context:

- Include relevant context from current conversation - Tag with source: "cli" (Claude Code session) - Add any mentioned relationships

  1. Confirm capture:

- Brief confirmation with ID - Mention if needs_review due to low confidence

Quick Actions

For common actions, provide shortcuts:

/sb capture "thought or idea"     # Capture immediately
/sb inbox                         # Show pending items
/sb digest                        # Today's actionable summary
/sb query "search term"           # Search knowledge base
/sb done <id>                     # Mark task complete

Meeting Transcript Processing

Use case: Paste meeting transcripts to automatically extract and capture structured content.

Workflow

  1. User pastes transcript:
   "Here's the transcript from today's standup:
   [transcript content]"
  1. System processes and extracts:

- Meeting summary → MEETING node - Action items → TASK nodes - Decisions made → REFERENCE nodes - People mentioned → PERSON links - Follow-up meetings → MEETING nodes - Key insights → IDEA nodes

  1. Confirmation and review:
   Processed standup transcript:

   📅 Created: "Daily Standup - Jan 15" (meeting)

   ✅ Extracted 4 tasks:
   - "Review PR #1234" → assigned to you (high)
   - "Update API docs" → assigned to Sarah
   - "Schedule design review" → due Friday
   - "Fix login bug" → blocked by infrastructure

   📝 Captured 2 decisions:
   - "Using Postgres instead of MongoDB"
   - "Sprint ends Friday, demo at 2pm"

   👥 Linked 3 people:
   - Sarah (mentioned 5x)
   - Mike (mentioned 2x)
   - John (new person, created)

   💡 1 insight flagged:
   - "Team velocity improves when standups are <15 min"

Extraction Patterns

Action items (→ TASK):

  • "TODO: ...", "Action: ...", "Need to..."
  • "Sarah will...", "I'll...", "We should..."
  • "@mentions with action verbs"

Decisions (→ REFERENCE):

  • "Decided: ...", "Agreed: ..."
  • "We're going with...", "The plan is..."
  • "Final decision: ..."

Follow-ups (→ MEETING):

  • "Let's meet again...", "Schedule a follow-up..."
  • "Next week we'll discuss..."
  • Explicit dates/times mentioned

People (→ PERSON links):

  • Names mentioned in context
  • @mentions
  • "talked to...", "asked..."

Insights (→ IDEA):

  • Observations about patterns
  • Hypotheses mentioned
  • "I noticed...", "Interesting that..."

Post-Processing

After extraction:

  1. Create meeting node with summary
  2. Create task nodes with assignments and due dates
  3. Link people (create if new)
  4. Store decisions as references
  5. Write to Obsidian with wikilinks

Configuration

# ~/.config/secondbrain/daemons.yml
transcript_processing:
  auto_assign_unassigned: true  # Assign to self
  default_task_priority: 2
  flag_low_confidence: true     # Mark uncertain extractions
  link_to_meeting: true         # Connect all items to meeting node

Graph Model

Node Types

TypeDescriptionExample
valueCore principle"Family comes first"
goalOutcome to achieve"Run a marathon by December"
projectRelated work collection"Kitchen renovation"
taskActionable item"Call dentist to schedule"
personRelationship context"Sarah - VP Engineering"
meetingTime-bound event"1:1 with Sarah - Jan 15"
ideaNon-actionable insight"What if AI for onboarding?"
referenceInfo for retrieval"API rate limit: 1000/min"

Edge Types

RelationMeaningExample
supportsProvides evidence forproject → goal
blocksPrevents progress ontask → task
containsHierarchical parentproject → task
derived_fromExtracted fromgoal → value
assigned_toAssigned to persontask → person
mentioned_inReferenced in contextperson → meeting
related_toGeneral relationshipidea → reference
child_ofSubtask/childtask → task

Implementation

CLI Integration

This skill wraps the sb CLI commands:

sb capture "content"      # Capture a thought
sb inbox                  # List pending captures
sb process                # Classify pending captures
sb digest                 # Generate daily digest
sb list [type]            # List nodes
sb show <id>              # Show node details
sb status                 # System health check

Database

  • Local SQLite at ~/.local/share/secondbrain/secondbrain.db
  • Obsidian vault for markdown output
  • Graph model: nodes + typed edges

Configuration

# ~/.config/secondbrain/config.yml
node_id: "home"
vault_path: "/path/to/vault"
classification:
  model: "claude-sonnet-4-20250514"
  confidence_threshold: 0.6

Context Awareness

Use Session Context

When capturing, leverage current conversation context:

  • File being discussed: Link to related codebase notes
  • Error being debugged: Capture as reference with solution
  • Decision being made: Note with rationale
  • Meeting notes mentioned: Parse for action items

Domain Detection

Infer domain from context:

  • In work project directory → domain: work
  • Personal topics mentioned → domain: personal
  • Both contexts mixed → domain: both

Example Interactions

Capture During Work

User: "The deadline for the API migration is March 15th"
Assistant: [Captures as task with due date]
Captured: API migration deadline - Due March 15th (ID: abc123)

Query Knowledge

User: "What did we decide about authentication?"
Assistant: [Searches knowledge graph]
Found 3 related items:
- [reference] "Use JWT with refresh tokens" (Jan 5)
- [task] "Implement OAuth flow" (in_progress)
- [meeting] "Auth design review with Sarah" (Jan 3)

Morning Digest

User: "What should I focus on today?"
Assistant: [Generates digest]

📋 Today's Focus (Wed, Jan 15):
- [OVERDUE] Review PR from Sarah (due Jan 14)
- [HIGH] Prepare API migration plan
- [DUE TODAY] Call dentist to reschedule

📅 Meetings:
- 10:00 1:1 with Mike

⚠️ Needs Review: 2 items in inbox

Anti-Patterns

Don't:

  • Capture every single thing mentioned (be selective)
  • Force classification when context is unclear
  • Interrupt flow for minor captures
  • Create duplicate entries for same concept
  • Over-classify simple notes

Do:

  • Capture when user expresses intent or importance
  • Ask for clarification if capture intent is ambiguous
  • Batch confirmations when capturing multiple items
  • Link to existing nodes when relationships are clear
  • Respect user's domain boundaries

Integration Points

With beads issue tracker:

  • Cross-reference tasks with beads issues
  • Import epic/task relationships

With Obsidian vault:

  • Generated markdown syncs via Obsidian Sync
  • Wikilinks enable navigation
  • Daily notes include digest

With SiliconDoppelgangerActual:

  • Deep queries via agent conversation
  • Complex graph traversals
  • Multi-step reasoning about priorities

Success Metrics

Skill succeeds when:

  • Captures happen naturally without flow interruption
  • User finds past information quickly
  • Daily digests surface actionable items
  • Inbox stays manageable (<10 items needing review)
  • Classification accuracy >85%

User feels:

  • Confident nothing important is lost
  • Informed about what matters today
  • In control of their knowledge system

平台分布

Claude Code

30.46%
按下载量换算21

windsurf

24.96%
按下载量换算17

OpenCode

17.29%
按下载量换算12

Codex

12.68%
按下载量换算9

Antigravity

8.93%
按下载量换算6

Gemini CLI

3.57%
按下载量换算2

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills