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tensorpool

作者 Tycho-Svoboda · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
96
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install tensorpool
功能描述
This skill helps users migrate their local machine learning scripts to run on TensorPool GPU clusters using the interactive cluster workflow (tp ssh). Use th...
安全使用建议
This skill appears to do what it says (migrate scripts to TensorPool), but it instructs the agent to automatically edit, install packages, and re-run your code without asking. Before installing or enabling it: (1) require explicit confirmation before any changes, (2) use a disposable environment (virtualenv/conda or container) and back up your code, (3) be prepared to review all pip installs and code edits, (4) do not expose long-lived API keys/SSH keys unnecessarily — prefer temporary credentials or local authenticated sessions, and (5) monitor cluster creation to avoid unexpected cloud costs. If you need stronger guarantees, ask the skill author to remove the 'fix without asking' directive or to add an explicit opt-in prompt before making changes.
功能分析
Type: OpenClaw Skill Name: tensorpool Version: 1.0.0 The skill facilitates migrating ML scripts to TensorPool GPU clusters but contains high-risk instructions that grant the AI agent significant autonomy. Specifically, SKILL.md instructs the agent to 'proactively diagnose and fix' errors by executing commands like 'pip install' and 'mkdir' without asking for user permission. It also involves sensitive operations such as generating SSH keys (ssh-keygen) and accessing the ~/.ssh directory. While these actions are aligned with the stated purpose of cloud migration, the lack of human-in-the-loop confirmation for command execution and the handling of environment variables/SSH keys create a significant attack surface for potential exploitation.
能力评估
Purpose & Capability
The name/description (migrating local ML scripts to TensorPool via tp ssh) matches the instructions: discovering the tp CLI, creating clusters, transferring code, running on GPU, and debugging. There are no unrelated required env vars, binaries, or install steps declared.
Instruction Scope
SKILL.md tells the agent to 'proactively diagnose and fix the code without asking for permission' and to iterate until the script runs, including running pip installs, editing paths, creating directories, changing code (fixing dataloaders, dtypes, etc.), and re-running. That is scope creep from a user-consent perspective: it grants broad discretion to modify local code and environment automatically. The instructions also expect access to local files, SSH keys, and the user's TensorPool account — reasonable for the task but high-impact actions that should require explicit user approval and safe-guards.
Install Mechanism
This is an instruction-only skill with no install spec and no code files; nothing is written to disk by the skill itself. The runtime guidance to run 'pip install tensorpool' or pip install missing packages is expected for this purpose, but note these commands will alter the user's Python environment if executed.
Credentials
The skill declares no required environment variables or credentials. The instructions assume the user has a TensorPool account and local auth (tp CLI configured) and access to SSH keys, which is proportional. However, because the skill may prompt for or use API keys/SSH credentials at runtime, users should be aware the agent will operate using whatever local credentials or secrets they provide or that are present in the environment.
Persistence & Privilege
always is false and there's no install or self-persistence. The skill can be invoked autonomously (platform default), which increases impact if automated changes are allowed, but autonomy alone is not a disqualifier. The primary concern is the instruction to modify user files without explicit consent rather than persistent privileges.
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 tensorpool
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /tensorpool 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
TensorPool Skill v1.0.0 — Initial Release - Enables seamless migration of local ML scripts to TensorPool GPU clusters using the interactive workflow. - Guides users through step-by-step GPU cluster setup, environment preparation, code syncing, and production runs. - Automatically diagnoses and fixes common errors during migration (dependency, path, CUDA, environment issues), iterating until the script runs. - Enforces in-scope fixes while flagging out-of-scope changes for user approval. - Mandates runtime CLI command discovery to ensure compatibility with evolving TensorPool CLI. - Provides best practices for preparing scripts, managing dependencies, and efficient code/data transfer for cloud GPU runs.
元数据
Slug tensorpool
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

tensorpool 是什么?

This skill helps users migrate their local machine learning scripts to run on TensorPool GPU clusters using the interactive cluster workflow (tp ssh). Use th... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 96 次。

如何安装 tensorpool?

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

tensorpool 是免费的吗?

是的,tensorpool 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

tensorpool 支持哪些平台?

tensorpool 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 tensorpool?

由 Tycho-Svoboda(@tycho-svoboda)开发并维护,当前版本 v1.0.0。

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