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Install in OpenClaw
/install ee-ai-toolkit
Description
电气工程师 AI 工具包。用于 AI in Electrical Engineering、电气工程 AI、prompt engineering、power systems、smart grids、electrical calculations、design automation、data visualizatio...
README (SKILL.md)
EE AI Toolkit
这个技能由本目录的 HTML 课程资料压缩生成，主题是电气工程师如何用 AI、Python 和提示工程处理计算、设计、分析、自动化、优化和职业发展任务。
激活此技能时，优先按问题类型读取最小必要资料：
- 课程结构、资料来源、主题路由：读取
references/course-index.md。 - 快速回答或复习：读取
references/condensed-lessons.md。 - 需要接近原文、练习、示例流程或完整上下文：读取
references/source-digest.md。 - 提示词、提示词改写、提示词模板：读取
references/prompt-library.md。 - Python 示例脚本、脚本编号、脚本用途：读取
references/python-script-catalog.md，再使用assets/python-scripts/中的对应脚本。 - 需要核对原始 HTML：使用
assets/source-html/，或解压assets/source-html.tar.gz。
资料较大时，先用检索脚本定位，再读取相关引用文件：
python3 {baseDir}/scripts/search_ee_ai.py --query "load forecasting"
生成或修改工程答案时，保持以下约束：
- 明确单位、输入假设、公式、计算步骤和验证方法。
- AI 生成的设计、保护、配电、并网、优化和故障分析结果只能作为工程草案或教学示例。
- 对安全关键或合规相关电气工程问题，要求用户用适用标准、仿真工具、现场数据和有资质工程审查进行验证。
- 需要代码时，优先复用或改造
assets/python-scripts/中最接近的脚本，而不是从零编造。 - 回答可以中英文混合，但用户用中文提问时默认用中文回答。
Usage Guidance
This package appears to be an offline course/toolkit that reads and runs local Python examples. Before installing or running code: (1) review any scripts you plan to run (especially those you haven't inspected) for network calls or filesystem writes; (2) run code in a sandbox or isolated environment if you are concerned; (3) ensure required Python libraries (numpy/pandas/scikit‑learn/matplotlib) are installed in a controlled environment; (4) be cautious when extracting assets/source-html.tar.gz—verify its contents first. If you want, I can scan the remaining omitted scripts for network/file I/O patterns or highlight any files that write to disk or call external services.
Capability Analysis
Type: OpenClaw Skill
Name: ee-ai-toolkit
Version: 1.0.0
The ee-ai-toolkit is a comprehensive educational resource and utility bundle for electrical engineers, consisting of 100 Python scripts and extensive documentation. The scripts (e.g., script_001_power_calculator.py, script_041_load_forecasting_linear_regression_practical.py) provide functional examples for engineering calculations, data analysis, and basic machine learning. A dedicated search utility (scripts/search_ee_ai.py) allows the AI agent to efficiently retrieve information from the provided references. No evidence of malicious intent, data exfiltration, or harmful prompt injection was found; all file access and processing logic are strictly aligned with the stated purpose of engineering automation and analysis.
Capability Tags
Capability Assessment
Purpose & Capability
The name/description (EE AI toolkit, 100 Python examples, prompt library, course materials) align with the included files (references/*.md, assets/python-scripts/*) and the single required binary (python3). The requested capabilities are proportional to its stated purpose.
Instruction Scope
SKILL.md instructs the agent to read local course files and to prefer using the included Python example scripts; it provides a small local search utility for locating material. There are no instructions to read unrelated system files, fetch secrets, or transmit data externally. It does note the option to extract assets/source-html.tar.gz if HTML verification is needed.
Install Mechanism
No install spec is present (instruction-only with bundled files), so nothing is downloaded or executed automatically during install. This is the lowest‑risk install model for a skill.
Credentials
The skill declares no required environment variables or credentials. The optional Python libraries (numpy, pandas, matplotlib, scikit‑learn) mentioned in SKILL.md are appropriate for the examples and are not requested as secrets or system credentials.
Persistence & Privilege
always is false and autonomous invocation is enabled (the platform default). The skill does not request persistent elevated privileges or to modify other skills' configs.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install ee-ai-toolkit - After installation, invoke the skill by name or use
/ee-ai-toolkit - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
EE AI Toolkit initial release:
- 提供专为电气工程师设计的 AI 工具包，支持 AI、Python、提示工程在电气工程中的应用。
- 包括电气计算、设计自动化、数据可视化、优化与电气工程 100 个 Python 脚本示例。
- 支持电力系统、智能电网、工程脚本和职业发展领域的常见问题解答与流程指导。
- 按需智能分流：自动读取最相关课程文件、高效检索和引用资料辅助技术问答。
- 回答包含明确计算单位、假设、验证方法，并提示安全与合规注意事项。
- 默认为中文或中英混合作答，以贴合用户习惯。
Metadata
Frequently Asked Questions
What is ee-ai-toolkit?
电气工程师 AI 工具包。用于 AI in Electrical Engineering、电气工程 AI、prompt engineering、power systems、smart grids、electrical calculations、design automation、data visualizatio... It is an AI Agent Skill for Claude Code / OpenClaw, with 91 downloads so far.
How do I install ee-ai-toolkit?
Run "/install ee-ai-toolkit" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is ee-ai-toolkit free?
Yes, ee-ai-toolkit is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does ee-ai-toolkit support?
ee-ai-toolkit is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created ee-ai-toolkit?
It is built and maintained by John Do (@junwugit); the current version is v1.0.0.
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