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在 OpenClaw 中安装
/install mars-clouds-clustering-parallel-processing
功能描述
Parallel processing with joblib for grid search and batch computations. Use when speeding up computationally intensive tasks across multiple CPU cores.
安全使用建议
This is a safe, coherent how-to for using joblib. Before using it: ensure the runtime Python environment has joblib installed and compatible versions of your dependencies; be cautious with n_jobs (using all cores can make the host unresponsive); watch memory usage when sharing large data objects across workers; test with small workloads first. If you run user-provided or untrusted 'expensive_computation' code, run it in a sandboxed environment to avoid executing unsafe code.
功能分析
Type: OpenClaw Skill
Name: mars-clouds-clustering-parallel-processing
Version: 0.1.0
The skill bundle provides standard documentation and code examples for using the joblib library to perform parallel processing in Python. The content in SKILL.md is purely educational, focusing on n_jobs parameters, grid search patterns, and performance tips, with no evidence of malicious intent, data exfiltration, or prompt injection.
能力评估
Purpose & Capability
Name and description claim joblib-based parallel processing; the SKILL.md contains only joblib usage examples and related tips — no unrelated credentials, binaries, or surprising access are requested.
Instruction Scope
Instructions are limited to Python code examples (Parallel, delayed, parameter grid, shared data) and performance advice. They do not reference reading arbitrary host files, environment variables, network endpoints, or other system credentials.
Install Mechanism
There is no install spec (instruction-only), so nothing is downloaded or written to disk by the skill itself — consistent with a code snippet / how-to skill.
Credentials
No environment variables, credentials, or config paths are requested. This is proportional for a library usage guide; the only implicit requirement is that joblib (and any user code like expensive_computation) be available in the runtime Python environment.
Persistence & Privilege
Skill is not forced-always and does not request any persistent agent privileges or modifications to other skills; autonomous invocation is allowed by default but not combined with other risky behaviors here.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install mars-clouds-clustering-parallel-processing - 安装完成后，直接呼叫该 Skill 的名称或使用
/mars-clouds-clustering-parallel-processing触发 - 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
v0.1.0
Bulk publish from all-task-skills-dedup
元数据
常见问题
parallel-processing 是什么？
Parallel processing with joblib for grid search and batch computations. Use when speeding up computationally intensive tasks across multiple CPU cores. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 75 次。
如何安装 parallel-processing？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install mars-clouds-clustering-parallel-processing」即可一键安装，无需额外配置。
parallel-processing 是免费的吗？
是的，parallel-processing 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
parallel-processing 支持哪些平台？
parallel-processing 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 parallel-processing？
由 lnj22（@lnj22）开发并维护，当前版本 v0.1.0。
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