Agent skill

Disk Storage Analyzer

by KKKKhazix in KKKKhazix/khazix-skills

Scans a Mac or Windows PC read-only to find what fills the disk, grades each item by how safe it is to clean and builds an interactive HTML report.

MITAuto-check passedProductivity & Automation

SKILL.md written in Chinese; this summary is our English description.

Install Disk Storage Analyzer

skills CLI
$ npx skills add KKKKhazix/khazix-skills --skill storage-analyzer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install KKKKhazix/khazix-skills storage-analyzer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/KKKKhazix/khazix-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/storage-analyzer .claude/skills/storage-analyzer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
storage-analyzer
GitHub stars
21k
Used in
1 other repo
Token cost
~1.4k tokens
SKILL.md length
300 words
Files
7 (incl. scripts, references, assets)
Skills in repo
6
Repo updated
First seen
Licence
MIT

At a glance

Scans a Mac or Windows PC read-only to find what fills the disk, grades each item by how safe it is to clean and builds an interactive HTML report.

  • Works in 4 steps: 扫描(只读) → 分析与分级 → 生成交互报告 → …
  • The disk is nearly full and you want to know what is taking the space
  • SKILL.md covers 铁律, 执行流程, 依赖与运行前提 and 平台状态, plus 1 more section
  • Runs Python scripts from its folder; calls python3 and brew

What it does

The skill runs a read-only analysis of disk usage on macOS or Windows and detects the system on its own. A scan script lists large folders as JSON, the agent then classifies the findings, and a report builder produces an interactive HTML page with collapsible sections and cleanup commands that can be copied with one click. An optional local server, scripts/server.py, can serve the page so items can be moved to the trash from it.

Each finding lands in one of three tiers: green for safe cleanup such as caches, temporary files and developer caches; yellow for items that need your judgment, such as offline videos, documents and node_modules; and red for items better left alone, with uninstall steps for large apps. The agent never runs delete commands itself and stops to ask first, labels freed-space figures as estimates, and lists folders the scan could not read.

The SKILL.md is written in Chinese and triggers on phrases about a full disk or low storage. It does not apply to questions about RAM or which process uses memory. Reference files describe where data lives on macOS and on Windows.

When your agent uses it

  • The disk is nearly full and you want to know what is taking the space
  • Getting a cleanup plan with risk levels for caches, downloads and app data
  • Producing a shareable HTML report of disk usage on a Mac or Windows PC

Example prompts

  • “My C drive is full. Show me what is using the space and what is safe to delete.”
  • “Analyze my Mac's storage and give me a cleanup report I can open in the browser.”
  • “Which developer caches on this machine can I clear without losing anything?”

Requirements

  • Python 3, to run the scan and report scripts
  • macOS or Windows

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. 扫描(只读)
  2. 分析与分级
  3. 生成交互报告
  4. 对话里给摘要

What it can do on your machine

Read from SKILL.md and the folder at commit 322346d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3
    • brew

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Disk Storage Analyzer loads about 1.4k tokens when it runs, and up to ~2.4k if it reads all its reference files. Until then it costs about 117 tokens; SKILL.md has 300 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~117
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from KKKKhazix/khazix-skills at commit 322346d, republished under its MIT licence (© KKKKhazix). 300 words, ~1,402 tokens.

Download SKILL.mdSave it as .claude/skills/storage-analyzer/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
storage-analyzer
description
macOS / Windows 只读存储分析助手(自动识别系统)。扫描整机磁盘占用,找出 占空间大户,把每一项分成 🟢可自动清理 / 🟡需人工判断 / 🔴谨慎清理 三级并给出 可执行处置方案,生成排版精美、可折叠、命令可一键复制的交互式 HTML 报告,并可 起本地服务在网页上一键删除(移废纸篓/直接删)。扫描全程只读。务必在以下场景 使用:用户说"存储分析""磁盘满了""C盘/硬盘满了""空间不够""清理空间" "清理磁盘""占空间""哪些东西占地方""帮我看看存储""看一下电脑存储/空间" "存储空间""电脑空间不够""内存满了/不够/不足""看下内存/存储"(中文口语里 "内存"常指存储空间)"storage analysis""disk cleanup""清缓存""磁盘清理"; 或用户抱怨电脑没空间、想知道什么东西吃硬盘、想要清理建议时。注意:若用户明确 指运行内存/RAM(如"哪个进程吃内存""内存占用高"想看活动监视器),那是 RAM 不是存储,不属于本 skill。

Storage Analyzer

对 macOS 做一次只读存储分析,产出交互式 HTML 报告。流程:扫描 → 分析分级 → 生成网页 → 打开。

铁律

  • 全程只读。 只能跑扫描/统计/列目录/读元信息(df、du、diskutil、stat、ls)。绝对禁止 rm、mv、rmdir、清空回收站、改权限等任何写操作。
  • 删除命令只展示,不执行。 报告里给出的清理命令是供用户自己在终端确认后运行的。即使用户在对话里说"帮我删",也要先停下确认(命中全局红线:删除文件必须先问),不要直接代跑。
  • 估算标注清楚。 涉及"可释放空间"一律说明是估算值。
  • 路径、命令保留原文不翻译。

执行流程

Step 1 扫描(只读)
bash
python3 scripts/scan.py > /tmp/storage_scan.json

scan.py 自动识别系统(sys.platform):

  • macOS:扫 home、library、caches、containers、group_containers、app_support、applications、downloads、dev_caches,用 du 算大小。
  • Windows:扫 user_profile、appdata_local、appdata_roaming、temp、downloads、program_files(_x86)、dev_caches,用 os.scandir 算大小;system.disks 含所有盘符。

输出 JSON:system(系统/磁盘信息,含 disk_name 主盘名 + disks 全部盘)+ groups(各组子目录大小,已降序、过滤 50MB 以下)。扫描较慢,耐心等。读不到的目录标 denied,需在报告里列出并提示遗漏体量。

Step 2 分析与分级

先看 system.os 判断系统,读对应的数据布局参考:macOS 读 references/macos.md,Windows 读 references/windows.md(讲该系统东西存哪、怎么辨认、归哪一级)。然后读 /tmp/storage_scan.json 做这几件事:

  1. 挑 Top 5 占用大户,判定类型(系统资产/应用本体/应用数据/应用缓存/开发缓存/用户文件/媒体内容/下载内容/虚拟机镜像/回收站/其他)。
  2. 识别"神秘大目录":UUID 命名的 Container、不明的隐藏目录,要追查它属于哪个 App、装的是什么(例如某 97GB 的 UUID Container 实为 Bilibili 离线视频缓存)。必要时 ls/du 深入一层看清楚,但仍只读。
  3. 三级分类 = 清理决策清单,不是全盘点。 只把"存在'要不要动它'这个决策"的项放进三灯;日常在用的正常应用、操作系统本身、海量零碎小文件没有清理决策,不进三灯,它们落在磁盘条的蓝色"系统及其他"里。判定标准:
    • 🟢 可自动清理:纯缓存、临时文件、安装包残留、明确可再生且不影响功能、不丢用户数据(pip/uv/npm/Xcode DerivedData 等开发缓存、浏览器缓存)。
    • 🟡 需人工判断:含用户数据或有判断成本(离线视频、文档、项目代码 node_modules、聊天记录、设计稿)。给内容画像 + 至少 3 句处置路径(应用内清理 / 系统工具 / 文件管理器手动审查,三选最合适)+ 风险提示。所有橙灯项在服务模式下自动有「在访达/资源管理器打开」按钮(跳过去自己审查删);如果该项有一个核实过、删了不破坏 App 的安全子路径(如 B站离线视频的 .Downloads 目录、旧备份目录),给它 trash_paths → 网页出现「移到废纸篓」按钮(橙灯只准移废纸篓、可逆,绝不给"直接删除")。App 托管又无安全子路径的(Chrome/微信)只给打开按钮、不给 trash_paths。按钮下方会自动写明注意事项(打开只查看不删、移废纸篓可逆需清空才释放等);如果某项在文件管理器里是 App 内部格式、不方便手动挑选,给它一个 open_note 字段做客观说明(会显示在注意事项里)。口吻要中性、像产品说明:直接描述"这里是什么结构、为什么不好手动删、想精细操作该去哪",不要写成"我发现/提醒注意/看着像没视频"这种暴露开发者踩坑视角的话。
    • 🔴 谨慎清理(有决策但不建议手删):你可能想动、但建议别手删的具体项——重复安装的应用、想卸载的大应用、运行中应用的核心数据等。给"为什么不建议手删" + indirect_release 写具体卸载步骤(自带卸载器 / 启动台长按 / 右键移废纸篓 / AppCleaner 清残留 / App Store 可重装等,要可照做不是空话)。应用项给 app_paths(真实 .app 绝对路径数组)→ 网页出现「在文件管理器打开(去卸载)」按钮,定位到 App 让用户自己正规卸载。红灯不给删除/卸载按钮(应用在系统目录、可能要管理员密码、可能有自带卸载器和残留,后台代删不稳妥)。纯系统文件、APFS 快照不要单独列红卡(没有清理决策),归蓝色即可;系统层面的释放技巧(重启释 swap、Time Machine 快照策略、可清除空间自动回收)写进 summary.long_term 长期建议。

每个 🟢 项要给:预估释放空间、清理前需关闭的进程、可一键复制的清理命令(用移到废纸篓或 App 自身清理入口的安全方式,谨慎用 rm;如用 rm 必须是明确的缓存子目录)。

大小字段写干净:size / size_estimate 用"约 14 GB""合计约 8.6 GB"即可——"约"已表示估算,不要再加"(估算)",重复且不专业(模板也会自动去掉这种冗余括号)。可再生属性已由分级标题和按钮说明覆盖,别塞进大小字段。

Step 3 生成交互报告

把分析结果写成 analysis JSON(schema 见 scripts/build_report.py 顶部注释)。

🟢 项必须带 trash_paths(具体可删的绝对路径数组,区别于人类可读的 path 展示字段)——这是网页删除按钮的前提,漏了按钮就不出现。

默认用一键删除模式(server.py)打开报告,因为这个 skill 的核心价值就是网页上能直接清理:

bash
python3 scripts/server.py /tmp/storage_analysis.json   # 自动开浏览器,Ctrl+C 停

server.py 起在 127.0.0.1 + 随机端口 + 随机 token。🟢 项给「移到废纸篓」(可逆) +「直接删除」(立即释放、不可逆);🟡 项给「在访达打开」+(有安全子路径时)「移到废纸篓」。安全模型——三套白名单,权限从严到宽:rm 只允许绿灯 trash_paths;trash 允许绿灯+橙灯 trash_paths(橙灯永远不能 rm);open(在文件管理器打开,非破坏性)允许上述全部 + 橙灯真实 path。所有请求 realpath 校验 + 必须在 $HOME 内 + token + Host 校验,每次点击浏览器先 confirm。osascript/SHFileOperationW 入废纸篓,macOS 首次弹访达自动化授权点允许即可。

仅当用户明确只想要一份可分享/留存的只读文件时,才用静态模式(无删除按钮,因为 file:// 打开的页面碰不到文件系统):

bash
python3 scripts/build_report.py /tmp/storage_analysis.json ~/Desktop/storage-report.html && open ~/Desktop/storage-report.html

排障:网页上没有删除/移废纸篓按钮 = 要么开的是静态报告(改用 server.py),要么 🟢 项漏了 trash_paths(补上重启服务)。

报告阅读流(固定顺序):磁盘总览卡片(容量 + 进度条 + 三色容量 pills + 系统信息,纯数据)→ 占用排行 Top5 → 执行建议 → 🟢🟡🔴 三级可折叠卡片(命令一键复制)→ 长期优化建议。即"现状 → 诊断 → 处方 → 操作 → 预防"。

注意 summary.overview 要写成一句话洞察(直接说最大占用是什么、能释放多少),不要重复总/已用/可用数字——那些已在卡片大数字里显示。overview 渲染在"执行建议"小节开头作引子(普通文字),紧接着是 summary.priority 优先级清单。

磁盘进度条把"已用"拆成分段:绿(可自动清)+橙(需手动)+红(已识别的不建议动项)+蓝(系统及其他,自动取 已用−绿−橙−红 的余量),余下为可用(灰底)。summary.tier_stats 的 green / yellow / red 三个值都要以可解析的 GB 数字开头(如 "约 27.8 GB"),脚本从中取数算分段;蓝色段和"系统及其他"pill 由模板自动算余量。

pills 只渲染解析出的纯数字(如"约 5.5 GB"),不显示数据里的附注,所以 tier_stats 三个值写干净的数字即可,别加"仅已识别项/系统未计"这类道歉式说明——系统文件本来就归在蓝色段,红色只放你能量化的 🔴 项(重复应用、可卸载大应用等),量不准的系统文件/快照自然落到蓝色。

Step 4 对话里给摘要

报告生成后,在对话里用一段话给结论先行的摘要:总可释放估算、最该先清的 2-3 项、风险最高的一项。细节让用户看网页。

依赖与运行前提

  • 全部脚本是 Python 3 标准库,零第三方依赖(不用 pip install)。
  • macOS 自带 python3、du、diskutil、osascript,开箱即用。
  • Windows 默认没装 Python——需先装 Python 3,且命令多为 python 或 py -3(不是 python3)。本 skill 命令示例写的是 python3,在 Windows 上自动改用 python / py -3。
  • 本 skill 是 agent 驱动:扫描出数据后由 agent(Claude)做分级分析,不是双击即用的独立 App。

平台状态

  • macOS:完整实现并实测(扫描 / 报告 / 一键删除全验证过)。
  • Windows:代码已写(scan.py 的 scan_windows、server.py 的 _trash_windows 走 SHFileOperationW),但未在真实 Windows 上实测。首次在 Windows 跑要核对:目标目录路径、os.scandir 大小、回收站删除是否正常。多盘符已支持(主盘分段条 + 其他盘列表)。

长期优化建议素材(写进报告 summary.long_term)

  • 定期清理:brew cleanup、Xcode DerivedData、浏览器缓存
  • 可视化工具:DaisyDisk、GrandPerspective、OmniDiskSweeper
  • 大文件归档到外置盘 / iCloud / NAS;macOS「系统设置 > 通用 > 储存空间」的优化选项

© KKKKhazix, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references, assets) in storage-analyzer of KKKKhazix/khazix-skills.

  • SKILL.md
  • assets/report_template.html
  • references/macos.md
  • references/windows.md
  • scripts/build_report.py
  • scripts/scan.py
  • scripts/server.py

Open the folder on GitHubat commit 322346d

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in KKKKhazix/khazix-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Fantastical Calendartwhsi/skills259—~688Automated safety check: PassNone

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Works with

Questions about Disk Storage Analyzer

What does Disk Storage Analyzer do?

Scans a Mac or Windows PC read-only to find what fills the disk, grades each item by how safe it is to clean and builds an interactive HTML report. The skill runs a read-only analysis of disk usage on macOS or Windows and detects the system on its own. A scan script lists large folders as JSON, the agent then classifies the findings, and a report builder produces an interactive HTML page with collapsible sections and cleanup commands that can be copied with one click.

When should I use Disk Storage Analyzer?

Disk Storage Analyzer fits situations like: the disk is nearly full and you want to know what is taking the space; getting a cleanup plan with risk levels for caches, downloads and app data; producing a shareable HTML report of disk usage on a Mac or Windows PC.

How do I install Disk Storage Analyzer in Claude Code?

Run `npx skills add KKKKhazix/khazix-skills --skill storage-analyzer -a claude-code`. Or copy the skill folder (storage-analyzer in KKKKhazix/khazix-skills) into .claude/skills/storage-analyzer in your project. Claude Code loads it when a task matches its description.

How do I install Disk Storage Analyzer in Codex?

Run `npx skills add KKKKhazix/khazix-skills --skill storage-analyzer -a codex`. Or copy the skill folder (storage-analyzer in KKKKhazix/khazix-skills) into .agents/skills/storage-analyzer in your project. Codex loads it when a task matches its description.

Can I use Disk Storage Analyzer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add KKKKhazix/khazix-skills --skill storage-analyzer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/storage-analyzer, .gemini/skills/storage-analyzer, .github/skills/storage-analyzer and .opencode/skills/storage-analyzer in your project.

What does Disk Storage Analyzer need to run?

Going by SKILL.md and its folder, Disk Storage Analyzer needs Python for the scripts in its folder and the command-line tools its instructions call (python3 and brew). Our summary lists: Python 3, to run the scan and report scripts; macOS or Windows.

Does Disk Storage Analyzer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Disk Storage Analyzer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Disk Storage Analyzer use?

Disk Storage Analyzer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Disk Storage Analyzer use?

About 1.4k tokens (SKILL.md is roughly 5.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 983 tokens, read only when the agent opens those files.

What are the alternatives to Disk Storage Analyzer?

Skills that share tags, products or a category with Disk Storage Analyzer: Rename Pdfs (realspqrk/autorename-pdf, 122 stars), Setup (marketcalls/vectorbt-backtesting-skills, 208 stars), Mole Mac Cleanup CLI Safety (tw93/Mole, 70k stars) and Jev Desktop Computer Use (kerpopule/hermes-jev-skills, 1.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Disk Storage Analyzer?

KKKKhazix (a GitHub user) maintains it in KKKKhazix/khazix-skills, which has 21,265 GitHub stars. The repository holds 6 skills in this directory. The repository was last updated on October 1, 2026.

Source: KKKKhazix/khazix-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.