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feat: 拆分 environment-setup 为 Python/Node.js 运行时双核心 + 父级路由
新增双核心 skill(深度集成 DesireCore Hatch/Volta + HTTP API + Socket.IO): - python-runtime v1.0.1:Python 运行时管理 · 四级降级:HTTP API → Hatch CLI 绝对路径 → 系统包管理器 → pyenv · references:hatch-desirecore / pyenv-fallback / virtualenv / troubleshooting · scripts/probe-python.sh:输出 JSON 快照供 Claude 解析决策 - nodejs-runtime v1.0.1:Node.js 运行时管理 · 四级降级:HTTP API → Volta CLI → 系统包管理器/NodeSource → nvm/fnm · references:volta-desirecore / nvm-fallback / package-managers / troubleshooting · scripts/probe-node.sh:输出 JSON 快照(含 volta_tools / package_json_volta 等) environment-setup → dev-environment-setup v2.0.1(重命名 + 重写为 router): - 从 1380 行手册瘦身为 ~150 行索引 - 仅负责容器(Docker/Podman)/ WSL2 / 办公依赖速查 / 系统工具 - references/desirecore-runtime.md 沉淀 Hatch/Volta 路径表 + HTTP API 速查 + Socket.IO 事件契约,作为两个核心 skill 的共享底座 - references/decision-tree.md 定义四级降级决策树 - scripts/probe.sh + probe.ps1 系统级 JSON 探测 三个 SKILL.md 的 L0 改为场景驱动结构(何时使用 / 何时不要用 / 怎么做), 让 AI 凭名字与 L0 即可判断匹配场景。 注册更新: - builtin-skills.json:新增 python-runtime / nodejs-runtime / dev-environment-setup (原 environment-setup 移除),按字母序,共 21 个 skill - manifest.json:totalSkills 19→21,lastUpdated 2026-05-02 下游同步: - docx / pdf / xlsx / pptx 中的环境引用从 environment-setup 拆分为 python-runtime / nodejs-runtime / dev-environment-setup 三向指引 Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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skills/python-runtime/SKILL.md
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skills/python-runtime/SKILL.md
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---
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name: Python 运行时管理
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description: >-
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Use this skill when the user needs to install, upgrade, or troubleshoot
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Python and pip environments. Covers four-tier fallback strategy: (1)
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DesireCore HTTP API for in-app installation, (2) DesireCore built-in Hatch
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CLI for Python version management, (3) system package managers
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(brew/apt/dnf/winget), (4) community pyenv as last resort. Also covers
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virtual environments (venv/pipx/conda), PEP 668 externally-managed errors,
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and import / PATH troubleshooting. Triggers include: "install python", "pip
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not found", "python not found", "PEP 668", "externally-managed", "venv",
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"virtualenv", "pipx", "conda", "miniconda", "pyenv", "hatch", "python
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version", "pip command not found", or any Python-related runtime error.
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使用场景:用户需要 安装 Python、安装 pip、配置虚拟环境、管理多版本、
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解决 PEP 668、import 失败、PATH 问题、SSL 证书错误等。
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version: 1.0.1
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type: procedural
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risk_level: low
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status: enabled
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disable-model-invocation: true
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tags:
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- python
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- pip
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- hatch
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- pyenv
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- venv
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- virtualenv
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- pipx
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- conda
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- environment
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metadata:
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author: desirecore
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updated_at: '2026-05-02'
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market:
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icon: >-
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<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0
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24 24" fill="none"><defs><linearGradient id="py-a" x1="3" y1="3" x2="21"
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y2="21" gradientUnits="userSpaceOnUse"><stop
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stop-color="#306998"/><stop offset="1"
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stop-color="#FFD43B"/></linearGradient></defs><rect x="3" y="3" width="18"
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height="18" rx="3" fill="url(#py-a)" fill-opacity="0.12"
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stroke="url(#py-a)" stroke-width="1.5"/><path d="M9 8.5h4.5a1.5 1.5 0 011.5
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stroke-width="1.4" stroke-linecap="round" fill="none"/><path d="M15
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15.5h-4.5a1.5 1.5 0 01-1.5-1.5v-3a1.5 1.5 0 011.5-1.5H14.5A1.5 1.5 0 0016
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fill="none"/><circle cx="10.5" cy="10" r="0.6" fill="url(#py-a)"/><circle
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cx="13.5" cy="14" r="0.6" fill="url(#py-a)"/></svg>
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short_desc: Python 安装、多版本与虚拟环境(DesireCore Hatch 优先)
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category: development
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maintainer:
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name: DesireCore Official
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verified: true
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channel: latest
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---
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# python-runtime 技能
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## L0:一句话摘要
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**何时使用**:用户需要 安装 Python / 升级 Python / 切换 Python 多版本 / 配置
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pip / 创建虚拟环境(venv / pipx / conda)/ 排查 `python: command not found`、
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`pip: command not found`、PEP 668 "externally-managed"、SSL 证书、import 失败、
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PATH 异常 等 Python 运行时问题,或其他 skill(docx / pdf / xlsx / pptx)报告
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"Python 不可用" 时。
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**怎么做**:优先使用 DesireCore 内置 Hatch,按四级降级(HTTP API → Hatch CLI →
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系统包管理器 brew/apt/dnf/winget → 社区方案 pyenv)执行。
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## L1:概述与使用场景
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### 能力描述
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procedural skill。每次执行 Python 环境操作前,先运行 `scripts/probe-python.sh` 取 JSON 快照,再按 `references/decision-tree`(→ `../dev-environment-setup/references/decision-tree.md`)四级降级选择路径。
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### 使用场景
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- "python not found" / "pip not found"
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- 用户要求安装/升级 Python
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- 用户要求多版本管理(3.10/3.11/3.12 切换)
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- 创建/激活/调试虚拟环境(venv/pipx/conda)
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- "externally-managed-environment"(PEP 668)报错
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- import 失败、PATH 问题、SSL 证书错误
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- 其他 skill(docx/pdf/xlsx/pptx)报告 Python 不可用
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### 核心价值
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- **DesireCore 优先**:Hatch + HTTP API 作为强制 L1/L2,避免污染系统 Python
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- **JSON 决策**:probe 脚本输出结构化数据,Claude 可直接解析
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- **跨平台一致**:macOS / Linux / Windows 统一 4 级降级
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## L2:详细规范
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### 第一步:环境探测(必须)
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```bash
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bash skills/python-runtime/scripts/probe-python.sh > /tmp/py-probe.json
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cat /tmp/py-probe.json | jq .
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```
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输出字段含义见 `../dev-environment-setup/references/probe-snapshot.md`。
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### 第二步:选择执行路径
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按 `../dev-environment-setup/references/decision-tree.md` 判断:
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| 条件 | 路径 |
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|------|------|
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| `desirecore_api` 非空 | **L1** HTTP API |
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| `desirecore_api` 空,`hatch_path` 非空 | **L2** Hatch CLI |
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| 上述都不满足 | **L3** 系统包管理器(brew/apt/dnf/winget) |
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| L1–L3 全部失败或用户明示 | **L4** 社区方案(pyenv) |
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### 第三步:执行(仅展示主路径,详见各 references)
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#### L1:HTTP API(→ `references/hatch-desirecore.md`)
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```bash
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PORT=$(cat ~/.desirecore/agent-service.port)
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BASE="https://127.0.0.1:${PORT}/api/runtime"
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# 列出可装版本
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curl -sk "${BASE}/python/available"
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# 触发安装(异步,订阅 runtime:terminal 看进度)
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curl -sk -X POST "${BASE}/python/install" \
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-H "Content-Type: application/json" \
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-d '{"version":"3.12"}'
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# 安装完成后强制刷新缓存
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curl -sk -X POST "${BASE}/environment/refresh"
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```
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#### L2:Hatch CLI 绝对路径(→ `references/hatch-desirecore.md`)
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```bash
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HATCH=~/.desirecore/runtime/hatch/hatch
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export HATCH_HOME=~/.desirecore/runtime/hatch
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"$HATCH" python install 3.12
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"$HATCH" python show # 列出已安装/可装版本
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# 直接使用 Hatch 安装的 Python
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~/.desirecore/runtime/hatch/local/3.12/python/bin/python3 -m venv .venv
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```
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Windows:`%USERPROFILE%\.desirecore\runtime\hatch\hatch.exe`。
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#### L3:系统包管理器
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| 平台 | 命令 |
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|------|------|
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| macOS | `brew install python3` |
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| Debian/Ubuntu | `sudo apt install python3 python3-pip python3-venv` |
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| Fedora/RHEL | `sudo dnf install python3 python3-pip` |
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| Arch | `sudo pacman -S python python-pip` |
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| Windows | `winget install Python.Python.3` |
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#### L4:pyenv(→ `references/pyenv-fallback.md`)
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仅在用户明示或上述失败时启用。
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### 第四步:虚拟环境
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虚拟环境策略详见 `references/virtualenv.md`:
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- venv(推荐,标准库)
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- pipx(全局 CLI 工具如 black/ruff/markitdown)
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- conda / miniconda(数据科学场景)
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### 第五步:故障排查
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报错时按 `references/troubleshooting.md` 查表:
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- "python: command not found" / "pip: command not found"
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- PEP 668 "externally-managed-environment"
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- SSL/TLS 证书错误
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- import 失败(包名 vs import 名差异)
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- macOS xcrun / Xcode CLI 缺失
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- Windows PowerShell 执行策略阻止脚本
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- 代理环境配置
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## 重要约束
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1. **绝不 `sudo pip install`**:始终用虚拟环境或 `pipx`。
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2. **修改了环境后必须刷新**:L1 调 `POST /api/runtime/environment/refresh`;L2/L3/L4 重新跑 probe。
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3. **跨 skill 协作**:`docx` / `pdf` / `xlsx` / `pptx` 报"Python 不可用"时,进入 L1/L2 安装;办公依赖速查见 `../dev-environment-setup/references/office-deps.md`。
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4. **不污染系统 Python**:项目级别一律使用 venv,全局 CLI 用 pipx。
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## 引用关系
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- 决策树:`../dev-environment-setup/references/decision-tree.md`
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- DesireCore 底座:`../dev-environment-setup/references/desirecore-runtime.md`
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- 探测协议:`../dev-environment-setup/references/probe-snapshot.md`
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- 办公依赖:`../dev-environment-setup/references/office-deps.md`
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- 系统工具:`../dev-environment-setup/references/system-tools.md`
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