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MLOps Prototyping CN

作者 Guohongbin · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
624
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0
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当前安装
1
版本数
在 OpenClaw 中安装
/install mlops-prototyping-cn
功能描述
Structured Jupyter notebook prototyping with pipeline integrity
安全使用建议
This skill appears coherent and low-risk: it runs a local script that reads a notebook file and prints checks. Before installing/running: (1) ensure python3 is available on the machine, (2) review scripts/check-notebook.sh yourself if you want to confirm behavior, (3) run it on non-sensitive copies of notebooks until you are comfortable with its heuristic false positives (its 'magic number' and import-detection heuristics are simplistic), and (4) be aware the wrapper prints a final 'Notebook check complete' message even when the internal check failed, so rely on the script's exit code rather than that message for CI gating.
功能分析
Type: OpenClaw Skill Name: mlops-prototyping-cn Version: 1.0.0 The `scripts/check-notebook.sh` file contains a critical shell injection vulnerability. The `$NOTEBOOK` variable is directly interpolated into a heredoc passed to `python3`, allowing arbitrary command execution if an attacker can control the input to this script (e.g., `NOTEBOOK="foo.ipynb$(id)"`). Additionally, it allows arbitrary file reading via path traversal if the target is a regular file. While this is a severe vulnerability, there is no evidence of intentional malicious behavior such as data exfiltration, persistence, or backdoors; the script's stated purpose is to check notebook structure.
能力评估
Purpose & Capability
Name/description match the included assets: SKILL.md documents a notebook-check workflow and the repo includes a small script (scripts/check-notebook.sh) that implements the check. No unrelated credentials, services, or installers are requested.
Instruction Scope
Runtime instructions only run a local shell script that opens the provided .ipynb and inspects cells. The script does not call external endpoints or read other filesystem paths, but it relies on python3 (not declared in metadata). The heuristics are simplistic (e.g., treating any digit in code as a 'magic number' unless RANDOM_STATE appears), and the outer shell prints a success message unconditionally after the Python block which may be misleading. No data exfiltration or broad system access is performed.
Install Mechanism
No install spec; instruction-only plus a small shipped script. Nothing is downloaded or extracted from remote URLs.
Credentials
No environment variables, credentials, or config paths are requested. The script only needs a local notebook file and a python3 runtime.
Persistence & Privilege
Skill does not request persistent/always-on presence, does not modify other skills or system settings, and contains no agents or background components.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install mlops-prototyping-cn
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /mlops-prototyping-cn 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Claude→OpenClaw conversion - Notebook structure checking
元数据
Slug mlops-prototyping-cn
版本 1.0.0
许可证
累计安装 0
当前安装数 0
历史版本数 1
常见问题

MLOps Prototyping CN 是什么?

Structured Jupyter notebook prototyping with pipeline integrity. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 624 次。

如何安装 MLOps Prototyping CN?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install mlops-prototyping-cn」即可一键安装,无需额外配置。

MLOps Prototyping CN 是免费的吗?

是的,MLOps Prototyping CN 完全免费(开源免费),可自由下载、安装和使用。

MLOps Prototyping CN 支持哪些平台?

MLOps Prototyping CN 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 MLOps Prototyping CN?

由 Guohongbin(@guohongbin-git)开发并维护,当前版本 v1.0.0。

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