Token导航 LogoToken导航TokenDH.com
效率需要联网clawhub未标认证来源可访问clear审计通过

personal-os-framework个人操作系统框架

Agent Skill

personal-os-framework 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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。

总安装

4,324

周安装

182

GitHub Stars

公开资料未说明

下载量

1,514
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:personal-os-framework(个人操作系统框架)
来源仓库:https://github.com/daowuu/personal-os-framework
安装命令:
openclaw skills install personal-os-framework
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install personal-os-framework

简介

个人操作系统框架构建 AI 可理解的第二个大脑,支持决策记录与路由优化。

  • 适用于复杂任务分解与长期目标执行管理。
  • 提供审查生成与自动化工作流编排能力。
  • 安装命令为 openclaw skills install personal-os-framework,需初始化 SOUL.md 等核心文件。
  • 使用前请确认是否依赖特定目录结构与配置文件模板。

SKILL.md

name
personal-os-framework
description
Build a second brain that AI can understand and maintain. This framework provides decision logging with follow-up tracking, periodic review generation, routing rules for information classification, task management with ownership and status, execution tracking for started tasks, decision support monitoring, and memory distillation for converting raw notes into structured knowledge. Use when you want AI to collaborate proactively by reading and updating your personal operating system through ongoing conversation.
metadata
openclaw
prePublishChecks
homepage
https://clawhub.ai

Personal OS Framework

A methodology and toolset for building a second brain that AI can understand and maintain.

The Core Idea

The human does the work. The AI records it. The AI reads the records. The AI understands the human. The AI helps more effectively.

This is not a standalone tool. It requires an AI collaborator that reads, updates, and maintains the system through ongoing conversation.

What This Framework Provides

Decision Log

Record important decisions with rationale and follow-up actions. Every significant judgment gets a permanent record.

Review Operator

Generate daily, weekly, and monthly reviews from project state. Surface stale projects, identify blockers, generate follow-up actions.

Routing Assistant

Classify incoming information by type and destination. Every piece of information has a canonical home.

Task Layer

Define what a task looks like. Track status, ownership, and aging.

Execution Layer

Record when work begins. Identify started tasks that have gone stale.

Decision Support Layer

Monitor decision follow-ups and task health. Proactive monitoring without manual recounting.

Memory Distiller

Convert accumulated raw captures into structured knowledge. Raw notes become permanent knowledge after a 7-day aging period.

Workflow

Capture → Structure → Execute → Reflect

Information enters the system. It gets classified. Work happens. Regular reviews keep everything current.

How It Works

Human does something
    ↓
AI observes or is told
    ↓
AI records in personal-os
    ↓
AI reads personal-os
    ↓
AI understands the human
    ↓
AI provides better help

Key Principles

The AI does not wait for commands. The AI reads the system, understands the human, and acts proactively.

Reviews keep the system alive. Without regular reviews, the system becomes stale.

Decisions are the most valuable content. Log them with context.

Files

Every personal-os has these core files:

  • STATE.md — current project states
  • TODO.md — active tasks
  • DECISIONS.md — decision log
  • PENDING-DECISIONS.md — blocked decisions
  • HEARTBEAT-LOG.md — system activity log

For AI Collaborators

Read the personal-os after each conversation. Update relevant files. The system stays current because the AI keeps it current.

When to Use This Framework

Use when:

  • You want to build a personal OS that AI can understand and maintain
  • You want decisions logged with context
  • You want regular reviews that surface stale projects
  • You want clear routing rules for information
  • You want AI to collaborate proactively

Do not use when:

  • The work is too small to benefit from structure
  • There is no commitment to regular reviews
  • The human is not willing to work with an AI collaborator

Success Metrics

The framework is working when:

  • You can answer "what was the reasoning behind X decision?"
  • Reviews surface real stale items
  • Decisions have follow-up actions that get done
  • The AI understands your context
  • The system stays current without constant maintenance

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

91.94%
按下载量换算1,392

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills