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 agentmods add skills/coracoo/zspace_skill/label-managernpx skills add coracoo/zspace_skill --skill label-managergit clone --depth 1 https://github.com/coracoo/zspace_skillWrote 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/coracoo/zspace_skill/label-manager)<a href="https://agentmods.dev/skills/coracoo/zspace_skill/label-manager"><img src="https://agentmods.dev/badge/skills/coracoo/zspace_skill/label-manager.svg" alt="Measured on agentmods" 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 | $0.00150 | $0.02835 |
| Opus 5 | $0.00075 | $0.01418 |
| Sonnet 5 | $0.00030 | $0.00567 |
| Haiku 4.5 | $0.00015 | $0.00283 |
Grade A, and why
label-manager 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 4d 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 — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Label Manager — NAS 标签全生命周期
概述
NAS 标签的全生命周期管理——两种发现方式,同一入口:
| 发现方式 | 用哪个命令 | 适合 |
|---|---|---|
| 按文件名/扩展名 | label_manager.py scan + find-by-label |
目录递归、批量、精确匹配 |
| 按文件内容(RAG 语义) | 纯 LLM 编排,semantic_search → save_file_label |
自然语言描述、不靠文件名 |
最终都走 save_file_label MCP tool 落盘。
前置:nas-setup skill(验证 NAS 登录)。RAG 场景额外需要 rag-manager(门控)。
MCP tool 依赖
| list_file_labels | 列出所有标签 |
| save_file_label(label_names, paths) | 打标签(覆盖式,会自动创建新标签名) |
| delete_label(label_names) | 删除标签(从所有文件上彻底移除) |
| notebook_updatelabel(id, label) | 笔记标签 |
| label_manager.py 命令(机械活) | 用途 |
|---|---|
list-labels |
同 MCP,但走脚本(批量友好) |
scan --root X --ext Y |
BFS 扫目录找文件(LLM 决策前先用) |
find-by-label --label X |
反向查询带某标签的文件 |
5 个标准场景
场景 1:给单个/多个文件打标签
用户说:"给 /sata14/my/data/docker-compose.yml 打 docker 标签"
步骤:
- 调
save_file_label(label_names="docker", paths="/sata14/my/data/docker-compose.yml") - 返回结果(返回 200 即可)
注意:
paths多个用英文逗号分隔,最多 50 个/次(NAS 限速)- 如果
label_names里有不存在的标签名,NAS 会自动创建
场景 2:批量打标(目录递归 + LLM 决策)
用户说:"把 /sata14/my/data/ 下所有 .yml 文件打 docker 标签"
步骤:
- exec
python skills/label-manager/label_manager.py scan --root /sata14/my/data/ --ext yml --max-depth 5 --output /tmp/scan.json - 读
/tmp/scan.json,得到items数组(含 path/name/labels) - LLM 自己判断哪些真该打(README.yml 不该打),过滤后分批(每批 50 个)
- LLM 调
save_file_label(label_names="docker", paths="path1,path2,...")分批执行
为什么 LLM 决策:不是所有 .yml 都是 docker 配置。LLM 看 path/name 决定。
场景 3:按标签找文件(反向查询)
用户说:"找所有带 docker 标签的文件"
步骤:
- exec
python skills/label-manager/label_manager.py find-by-label --label docker --root /sata14/my/data/ --max-depth 5 --output /tmp/docker.json - 读
/tmp/docker.json,得到matches数组(含 path/name/is_dir/labels) - 格式化返回给用户
已知 gap:
- 受
--max-depth限制,深度外文件找不到 - 用户只能扫
/<pool>/my/<子目录>/,跨池越权 N001411 - 脚本内部走 BFS + 串行,sleep 0.1s/层,100 个目录约 10s
What ships with it
4 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.
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.
- 4d ago First seen · 214 lines · 150 tokens per session scan A df3bbf1464b0
label-manager is a skill published in the GitHub repository coracoo/zspace_skill (19 stars, last pushed 29d ago), licensed MIT. It adds 150 tokens to every session and 2,835 once invoked, about $0.0007 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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