How Codex Became My Ultimate Computer Assistant

The author demonstrates how OpenAI Codex can serve as a full‑featured computer manager on macOS, automating cache cleaning, software uninstall, startup service control, large‑file detection, browser data cleanup, material organization, and daily inspections through tailored prompts and screenshots.

Old Zhang's AI Learning
Old Zhang's AI Learning
Old Zhang's AI Learning
How Codex Became My Ultimate Computer Assistant

The author, an experienced Codex user, shows how OpenAI Codex can be turned into a versatile computer‑assistant on macOS, handling tasks that traditional PC‑manager software provides.

UV cache cleaning

Manually clearing the uv cache requires remembering the uv command, opening Terminal, checking for running tasks, and verifying space recovery. With Codex a single prompt "clean uv cache" makes it scan directories, calculate cache size, stop waiting commands, invoke uv’s built‑in cleanup, and report the freed space.

Result: before cleanup the uv cache was about 2.7 GB; Codex removed ~2.5 GiB and the cache became 0 B.

帮我清理系统垃圾和开发缓存,重点看 uv、pip、npm、pnpm、conda、Xcode、浏览器缓存和临时目录,先统计大小并列清单,不要直接删除,确认后再清理,清理完告诉我释放了多少空间

Automation can be added by scheduling the prompt.

Core functions a traditional PC manager provides (Codex can do all)

Cleaning and acceleration: system junk, software caches, large files, duplicate files, downloads, browser cache, browsing traces.

Software management: install, upgrade, uninstall, residual removal, bundled components, unwanted software, rarely used apps.

Startup and permissions: boot items, system services, pop‑up ads, context‑menu entries, desktop icons, default apps.

Security fixes: malware removal, vulnerability patches, system updates, network fixes, homepage repairs, ransomware protection.

Tool collection: file recovery, storage awareness, health checks, toolbox.

Software uninstall and residual cleaning

Typical pain points include locating the installation path, dealing with leftover caches, configs, services, right‑click menus, and desktop icons, and risking removal of shared files.

帮我卸载 XXX,并清理卸载残留,先扫描应用本体、启动项、后台服务、缓存、配置文件和关联目录,列出准备删除的清单和风险,不要直接删除,等我确认后再执行,执行后重新搜索残留并给我一份结果报告

Codex returns a detailed report and performs the cleanup after confirmation.

Startup items and background services management

Pain points: slow boot, incomplete visibility of startup items, obscure service names, and risk of disabling essential services.

帮我体检开机启动项、后台服务和登录项,按“建议保留、可以关闭、需要我判断”三类整理,不要直接关闭,先说明每一项可能影响什么

Codex categorizes items and can disable the ones marked as safe.

Large and duplicate file cleaning

Pain points: system reports low space without pinpointing files, large files may be videos, models, installers, logs, caches, and duplicate files are hard to spot.

帮我找出用户目录下占空间最大的文件和疑似重复文件,先按大小排序,标出文件类型、最后修改时间和建议处理方式,不要删除,只生成清单和可执行方案

Codex produces a ranked list with type, modification time, and handling suggestions.

Browser cache, browsing history, and privacy files

Pain points: growing browser caches, dispersed download/history/Cookie data across browsers, risk of breaking login sessions when clearing everything, and desire to keep key sites.

检查 Chrome、Edge、Safari 的缓存、下载记录和站点数据占用,先列出大小和影响范围,不要清 Cookie 和登录态,给我一份“安全清理”和“深度清理”的两档方案

Codex returns two plans – a safe cleanup and a deeper one.

Material and knowledge‑base organization

Pain points: scattered research material across web pages, screenshots, notes, chats, and temporary markdown files; difficulty remembering where a piece of information is stored; time spent organizing before writing.

围绕“openai在传统行业的实践”整理我的本地素材,找出相关笔记、截图和草稿,按文章结构归类,缺口单独列出来,不要移动原文件,只生成素材地图

Codex generates a material map without moving files.

Automated daily inspection

Pain points: many routine checks are forgotten, such as failed tasks, daily reports, new article aggregation, project error scans, and noisy alerts.

帮我设计一个每天早上运行的电脑巡检任务,检查磁盘空间、异常大文件、失败日志、待更新项目和最近报错,只设计方案和输出样例,先不要创建定时任务

The proposed plan can be turned into a scheduled task once validated.

Summary

Codex proves to be a comprehensive computer manager; the demo covers only a fraction of its capabilities. It can handle bundled software removal, pop‑up suppression, download folder organization, lagging process investigation, suspicious file search, system patch removal, network issues, default app and browser settings, and more. Crucially, Codex first gathers evidence, explains risks, and asks for confirmation before performing destructive actions.

One More Thing: External model integration

Codex now supports custom model providers, allowing users to plug in models such as deepseek‑v4‑pro. The author does not test this integration but notes that successful external model support could further extend Codex’s computer‑assistant abilities.

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prompt engineeringsystem automationOpenAI CodexAI-powered PC managementcomputer assistantmacOS maintenance
Old Zhang's AI Learning
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Old Zhang's AI Learning

AI practitioner specializing in large-model evaluation and on-premise deployment, agents, AI programming, Vibe Coding, general AI, and broader tech trends, with daily original technical articles.

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