Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add malue-ai/dazee-small --skill macos-findergit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote 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/malue-ai/dazee-small/macos-finder)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/macos-finder"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/macos-finder/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/malue-ai/dazee-small/macos-finder"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/macos-finder.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 | $0.00027 | $0.00705 |
| Opus 5 | $0.00014 | $0.00352 |
| Sonnet 5 | $0.00005 | $0.00141 |
| Haiku 4.5 | $0.00003 | $0.00071 |
Grade A, and why
macos-finder 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 9d 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.
What it actually says
macOS Finder 操作
Finder 高级操作:标签管理、Quick Look、文件信息、智能文件夹。
使用场景
- 用户说「给这些文件打个标签」「预览一下这个文件」
- 用户需要查看文件的详细信息(大小、创建时间等)
- 用户需要按条件筛选文件
命令参考
文件标签(macOS Tags)
# 给文件打标签
tag -a "重要" /path/to/file.pdf
# 或者用 xattr
xattr -w com.apple.metadata:_kMDItemUserTags '("重要")' /path/to/file.pdf
# 查看文件标签
mdls -name kMDItemUserTags /path/to/file.pdf
# 按标签搜索文件
mdfind "kMDItemUserTags == '重要'"
# 移除标签
tag -r "重要" /path/to/file.pdf
Quick Look 预览
# 预览文件(按空格关闭)
qlmanage -p /path/to/file.pdf
# 生成缩略图
qlmanage -t /path/to/file.pdf -s 512 -o /tmp/
文件详细信息
# 完整元数据
mdls /path/to/file.pdf
# 常用字段
mdls -name kMDItemDisplayName -name kMDItemFSSize -name kMDItemContentCreationDate -name kMDItemContentModificationDate -name kMDItemKind /path/to/file.pdf
# 人类可读的文件大小
stat -f "大小: %z bytes" /path/to/file.txt
du -sh /path/to/file.txt
# 文件类型
file /path/to/file
磁盘空间
# 磁盘总体使用
df -h /
# 当前目录大小
du -sh .
# 子目录大小排序(前 10)
du -sh */ 2>/dev/null | sort -rh | head -10
最近使用的文件
# 最近修改的 20 个文件
mdfind "kMDItemFSContentChangeDate >= $time.today(-1)" -onlyin ~ | head -20
# 最近打开的文件(通过 Finder recents)
mdfind "kMDItemLastUsedDate >= $time.today(-7)" -onlyin ~/Documents | head -20
文件夹统计
# 统计文件数量和类型
find /path/to/dir -type f | sed 's/.*\.//' | sort | uniq -c | sort -rn
# 统计总文件数
find /path/to/dir -type f | wc -l
输出规范
- 文件大小用人类可读格式(KB/MB/GB)
- 时间用「X 天前」「刚刚」等自然语言
- 标签操作后确认结果
- 磁盘空间展示用简洁表格
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.
- 9d ago First seen · 108 lines · 27 tokens per session scan A ffe5a018e07b
macos-finder is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 27 tokens to every session and 705 once invoked, about $0.0001 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 2026-08-31.
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