效率应用PRODUCTIVITY· COST

learn-workbuddy

adongwanai/learn-workbuddy

从 0 复刻 WorkBuddy-style 桌面 AI 助手 Harness：24 章 Python 教程，覆盖 Agent Loop、工具调用、记忆系统、Sidecar、沙盒审计、DeepSeek/OpenAI 评测轨迹

根据公开文档整理，未运行实测；费用以项目官网为准。Based on public documentation, without runtime testing. Check the project site for pricing.

适用平台Platforms: claude-code
已识别的要求Documented requirements: API key · Local runtime
许可LICENSE: MIT

打开仓库Open repository

能力CAPABILITIES

它能帮你做成什么What it helps you do

上手GET STARTED

怎么装How to install

GIT-CLONE

git clone https://github.com/adongwanai/learn-workbuddy

选择与你的环境对应的方式。命令来自项目文档，未运行实测。Choose the option for your environment. Commands come from project documentation and have not been run-tested.

打开项目文档Open project documentation ↗

使用限制LIMITATIONS

限制与风险Limits and risk

以下要求与风险来自文档静态检查，未执行项目代码；扫描没有命中，不代表使用安全。Risk here is evidence, not an alarm. These findings come from static scanning of the docs; we never execute a project’s code.

限制LIMITS

需检查Needs review

01需要 API KeyREQUIRES API KEY: 是Yes
02需要本地环境NEEDS LOCAL RUNTIME: 是Yes
03需要 DockerNEEDS DOCKER: 未在文档中发现Not found in the docs
04难度DIFFICULTY: 需要开发经验Needs development work

项目动态PROJECT ACTIVITY

它现在处在什么位置Where it stands right now

首次发现FIRST SEEN

03 OCT 202603 OCT 2026

增长GROWTH

+3.5%+3.5%

403 → 417 stars · 8 个快照403 → 417 stars · 8 snapshots

状态STATUS

持续活跃Active

PROVENANCE · 这些结论的依据是什么Where these conclusions come from

来源 URLSource URL: https://github.com/adongwanai/learn-workbuddy
原始数据哈希Raw data hash: c9f1347660489a27a8a6c482c15d9ca3
解析时间Parsed at: 2026-10-10T23:40:50.646Z
最后一次验证Last verified: 2026-10-10T22:10:48.059Z
增长测量时间Growth measured: —
发现查询Discovery queries: focus:token:repo:topic-context-engineering
分类来源Category source: rules
焦点Focus: token (6)

完整解析证据 JSONFull parse evidence JSON

{
  "agents": [
    {
      "agent": "claude-code",
      "evidence": "readme: …维度 | learn-workbuddy | learn-claude-code | 直接看 WorkBuddy | |---|---|--…"
    }
  ],
  "apiKey": "env.example .env # 编辑 .env，只填 DEEPSEEK_API_KEY 即可开始 python3 examples/mini_workbuddy_de",
  "docker": null,
  "taxonomy": {
    "scores": {
      "design": 1,
      "ai-tools": 0,
      "dev-tools": 1,
      "indie-web": 0,
      "skill-agent": 0,
      "productivity": 4
    },
    "primary": "productivity",
    "secondary": "cost"
  },
  "localRuntime": "用户数据。 允许的材料： - 公开可观察的产品行为 - 本地运行时目录的结构性观察，已脱敏 - 通用协议和开源生态知识，例如 HTTP、JSON",
  "skillMdTotal": 2,
  "skillMdErrors": [],
  "treeTruncated": false,
  "categoryScores": {
    "data": 0,
    "agent": 0,
    "media": 0,
    "design": 2,
    "browser": 0,
    "devtool": 1,
    "security": 1,
    "marketing": 0,
    "productivity": 0
  },
  "classification": [
    {
      "signal": "1 SKILL.md with name + description",
      "weight": 0.95
    },
    {
      "signal": "skills/ directory with 2 markdown files",
      "weight": 0.75
    },
    {
      "signal": "README describes a Claude / Agent Skill",
      "weight": 0.7
    },
    {
      "signal": "description mentions AI",
      "weight": 0.2
    }
  ],
  "scannedSources": [
    "readme",
    "skills/excel-workbook/SKILL.md",
    "skills/git-commit/SKILL.md"
  ],
  "skillMdFetched": 2
}