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在 OpenClaw 中安装
/install parallel-tfidf-search-python-parallelization
功能描述
Transform sequential Python code into parallel/concurrent implementations. Use when asked to parallelize Python code, improve code performance through concur...
安全使用建议
This skill appears coherent and low-risk: it only provides guidance and code patterns for parallelizing Python. Before using it, review any transformed code the agent produces (don't let it run changes automatically), ensure you have the necessary Python libraries installed in your environment, and test transformed code on sample inputs—parallel code can consume many CPU/ memory resources and introduce race conditions or serialization/pickle issues. If you plan to let an agent run or apply changes automatically, require explicit approval for execution. If you need the skill to actually run code, prefer running it in an isolated environment (container/VM) and keep backups of original code.
功能分析
Type: OpenClaw Skill
Name: parallel-tfidf-search-python-parallelization
Version: 0.1.0
The skill bundle is a legitimate tool designed to help an AI agent parallelize Python code. It contains standard implementation patterns for multiprocessing, asyncio, and vectorization, along with safety checklists and error-handling strategies. No indicators of malicious intent, data exfiltration, or prompt injection were found in SKILL.md or the reference documentation.
能力评估
Purpose & Capability
The name/description match the SKILL.md and reference document: all recommended tools and patterns (multiprocessing, asyncio, NumPy, Dask, etc.) are relevant to Python parallelization. No unrelated binaries, credentials, or config paths are requested.
Instruction Scope
The runtime instructions are narrowly scoped to analyzing and transforming Python code for concurrency/parallelism. They do not instruct reading arbitrary system files, contacting external endpoints, or exfiltrating data. Examples reference common libraries and typical file operations (e.g., read_csv) which are appropriate for the domain.
Install Mechanism
This is an instruction-only skill with no install spec and no downloads or extracted archives. That minimizes disk-write/remote-code risk.
Credentials
No environment variables, credentials, or config paths are required. The skill mentions a number of third-party Python libraries (aiohttp, numba, dask, cupy, tqdm) but does not request credentials or system-level access; these mentions are proportional to the functionality.
Persistence & Privilege
always:false and no steps that modify other skills or system-wide agent settings. The skill does not request permanent presence or elevated privileges.
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 parallel-tfidf-search-python-parallelization - 安装完成后，直接呼叫该 Skill 的名称或使用
/parallel-tfidf-search-python-parallelization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
python-parallelization 是什么？
Transform sequential Python code into parallel/concurrent implementations. Use when asked to parallelize Python code, improve code performance through concur... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 79 次。
如何安装 python-parallelization？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install parallel-tfidf-search-python-parallelization」即可一键安装，无需额外配置。
python-parallelization 是免费的吗？
是的，python-parallelization 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
python-parallelization 支持哪些平台？
python-parallelization 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 python-parallelization？
由 lnj22（@lnj22）开发并维护，当前版本 v0.1.0。
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