Borrowing it
Nothing to install: this file belongs to peterfei/ai-agent-team. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/peterfei/ai-agent-team/main/.claude/skills/tidymydesktop/SKILL.mdgit clone --depth 1 https://github.com/peterfei/ai-agent-teamWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/peterfei/ai-agent-team/tidymydesktop)<a href="https://agentmods.dev/skills/peterfei/ai-agent-team/tidymydesktop"><img src="https://agentmods.dev/badge/skills/peterfei/ai-agent-team/tidymydesktop/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/peterfei/ai-agent-team/tidymydesktop"><img src="https://agentmods.dev/badge/skills/peterfei/ai-agent-team/tidymydesktop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00046 | $0.02439 |
| Opus 5 | $0.00023 | $0.01220 |
| Sonnet 5 | $0.00009 | $0.00488 |
| Haiku 4.5 | $0.00005 | $0.00244 |
Grade A, and why
tidymydesktop scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 364 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TidyMyDesktop - 智能桌面整理工具
概述
当用户请求整理桌面或目录时,此 skill 会自动:
- 分析目录中的文件和应用程序
- 智能分类并创建文件夹
- 识别和删除软件的旧版本
- 搜索未知软件的用途
- 生成详细的整理报告(Markdown格式)
支持的触发指令
用户可以通过以下方式触发此 skill:
- "帮我整理桌面" - 整理 ~/Desktop
- "帮我整理当前目录" - 整理当前工作目录(需要用户确认)
- 任何关键词 - 首先搜索相关内容
工作流程
步骤 1: 理解用户意图
首先判断用户输入的类型:
// 检查是否是整理指令
if (用户输入包含 "整理桌面") {
目标路径 = ~/Desktop
} else if (用户输入包含 "整理当前目录") {
// 需要用户确认目录路径
await askUserToConfirmPath()
} else {
// 如果是关键词,先搜索相关内容
await searchKeyword(用户输入)
return
}
步骤 2: 扫描和分析目录
使用提供的 Node.js 工具脚本扫描目标目录:
# 扫描目录并生成文件清单
node ~/.claude/skills/tidymydesktop/scripts/scan.js <目标路径>
该脚本会:
- 列出所有文件和应用程序
- 识别文件类型和扩展名
- 检测应用程序版本号
- 生成初始清单
步骤 3: 智能分类和整理
执行整理操作时,遵循以下原则:
3.1 文件分类规则
根据文件类型创建分类文件夹:
-
应用程序 (
Applications/)- 开发工具 (
Development/) - 办公软件 (
Office/) - 设计工具 (
Design/) - 通讯工具 (
Communication/) - 娱乐软件 (
Entertainment/) - 系统工具 (
Utilities/)
- 开发工具 (
-
文档 (
Documents/)- PDF文档 (
PDFs/) - Word文档 (
Word/) - Excel表格 (
Excel/) - 文本文件 (
TextFiles/)
- PDF文档 (
-
图片 (
Images/)- 照片 (
Photos/) - 截图 (
Screenshots/) - 设计稿 (
Designs/)
- 照片 (
-
视频 (
Videos/) -
音频 (
Audio/) -
压缩包 (
Archives/) -
代码项目 (
CodeProjects/) -
未分类 (
Uncategorized/)
3.2 版本去重规则
对于同一软件的多个版本:
// 识别版本号模式
// 例如: "AppName v1.2.3.dmg" 和 "AppName v2.0.0.dmg"
// 保留: 最新版本
// 删除: 旧版本
function identifyVersions(files) {
// 1. 提取版本号
// 2. 比较版本
// 3. 标记要删除的旧版本
}
CRITICAL: 在删除任何文件前,必须:
- 向用户展示将被删除的文件列表
- 等待用户确认
- 获得明确同意后才执行删除操作
3.3 未知软件处理
当遇到不确定用途的软件时:
# 使用 WebSearch 搜索软件信息
# 搜索查询格式: "<软件名称> 是什么软件 用途"
如果搜索后仍不确定:
- 将其放入
未分类/文件夹 - 在报告中标注为"需要人工审核"
步骤 4: 执行整理操作
使用提供的整理脚本:
# 执行整理操作
node ~/.claude/skills/tidymydesktop/scripts/organize.js \
--source <目标路径> \
--plan <整理计划JSON文件> \
--dry-run # 首次运行使用 dry-run 模式
重要安全措施:
- 首次运行使用
--dry-run模式(仅模拟,不实际移动文件) - 向用户展示整理计划
- 获得用户确认后,再执行实际操作
- 所有删除操作都需要用户明确确认
步骤 5: 生成整理报告
What ships with it
22 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .npmignore 14 B
- .test-summary.txt 5.2 KB
- CHANGELOG.md 1.7 KB
- LICENSE 1.1 KB
- package-lock.json 19 KB
- package.json 686 B
- README.md 8.4 KB
- scripts/classify.js 8.6 KB runs code
- scripts/organize.js 13 KB runs code
- scripts/run.bat 849 B runs code
- scripts/run.js 1.0 KB runs code
- scripts/run.sh 893 B runs code
- scripts/scan.js 7.6 KB runs code
- TEST_REPORT.md 15 KB
- test.bat 1.6 KB runs code
- test.sh 1.7 KB runs code
- tidy-classify 158 B
- tidy-classify.bat 184 B runs code
- tidy-organize 158 B
- tidy-organize.bat 184 B runs code
- tidy-scan 154 B
- tidy-scan.bat 180 B runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 364 lines · 46 tokens per session scan A 5f721923eb05
tidymydesktop is a skill published in the GitHub repository peterfei/ai-agent-team (434 stars, last pushed 2mo ago), licensed MIT. It adds 46 tokens to every session and 2,439 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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