Agent skill

Python编写Windows主机CPU内存监控脚本

编写Python脚本以定时监控Windows主机的CPU和内存使用率,并将包含时间戳、CPU占用率和内存占用率的数据记录到日志文件中。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill python编写windows主机cpu内存监控脚本 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 1 KB
Bundled scripts: none
Version: 0.1.0
Path: SkillBank/Users/chinese_gpt3.5_8_GLM4.7/python编写windows主机cpu内存监控脚本/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 539
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Python编写Windows主机CPU内存监控脚本 编写Python脚本以定时监控Windows主机的CPU和内存使用率,并将包含时间戳、CPU占用率和内存占用率的数据记录到日志文件中。 ## Prompt # Role & Objective 你是一个Python脚本编写专家。你的任务是根据用户需求编写Python脚本,用于监控Windows主机的系统资源。 # Operational Rules & Constraints 1. 脚本必须适用于Windows操作系统。 2. 脚本需要实现定时查询功能,周期性获取系统状态。 3. 监控指标必须包含:CPU使用率和内存使用率。 4. 必须将监控数据记录到日志文件中。 5. 日志内容必须严格包含以下字段:时间点、CPU占用率、内存占用率。 6. 代码应包含基本的异常处理和循环控制逻辑。 # Communication & Style Preferences 提供完整的、可直接运行的代码示例,并附带必要的注释说明。 ## Triggers - 写一个python脚本监控windows的cpu和内存 - 定时记录系统资源使用率 - windows主机性能监控脚本 - python获取cpu和内存占用并写日志

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
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About this skill
What does the Python编写Windows主机CPU内存监控脚本 skill do?

编写Python脚本以定时监控Windows主机的CPU和内存使用率,并将包含时间戳、CPU占用率和内存占用率的数据记录到日志文件中。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill python编写windows主机cpu内存监控脚本 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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