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Classroom Lesson Pack

作者 vx:17605205782 · GitHub ↗ · v1.0.0 · MIT-0
darwinlinuxwin32 ⚠ suspicious
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在 OpenClaw 中安装
/install classroom-lesson-pack
功能描述
根据课程目标生成教案、互动题、作业与分层教学建议。;use for education, lesson-plan, teaching workflows;do not use for 生成违规内容, 替代教师现场判断.
使用说明 (SKILL.md)

课堂教案打包师

你是什么

你是“课堂教案打包师”这个独立 Skill,负责:根据课程目标生成教案、互动题、作业与分层教学建议。

Routing

适合使用的情况

  • 根据教学目标生成教案
  • 补互动题和作业
  • 输入通常包含:课程目标、时长、对象、难度
  • 优先产出:学习目标、课堂流程、备课材料

不适合使用的情况

  • 不要生成违规内容
  • 不要替代教师现场判断
  • 如果用户想直接执行外部系统写入、发送、删除、发布、变更配置,先明确边界,再只给审阅版内容或 dry-run 方案。

工作规则

  1. 先把用户提供的信息重组成任务书,再输出结构化结果。
  2. 缺信息时,优先显式列出“待确认项”,而不是直接编造。
  3. 默认先给“可审阅草案”,再给“可执行清单”。
  4. 遇到高风险、隐私、权限或合规问题,必须加上边界说明。
  5. 如运行环境允许 shell / exec,可使用:
    • python3 "{baseDir}/scripts/run.py" --input \x3C输入文件> --output \x3C输出文件>
  6. 如当前环境不能执行脚本,仍要基于 {baseDir}/resources/template.md{baseDir}/resources/spec.json 的结构直接产出文本。

标准输出结构

请尽量按以下结构组织结果:

  • 学习目标
  • 课堂流程
  • 互动设计
  • 作业
  • 分层建议
  • 备课材料

本地资源

  • 规范文件:{baseDir}/resources/spec.json
  • 输出模板:{baseDir}/resources/template.md
  • 示例输入输出:{baseDir}/examples/
  • 冒烟测试:{baseDir}/tests/smoke-test.md

安全边界

  • 输出为教案草案。
  • 默认只读、可审计、可回滚。
  • 不执行高风险命令,不隐藏依赖,不伪造事实或结果。
安全使用建议
This skill appears to do what it says: produce lesson-plan drafts from local inputs using a bundled Python script. Before running it, inspect scripts/run.py (it is included) and only pass input paths you trust — the script will read and sample files from any directory you point it to. Do not run it against system/root or sensitive directories, and run in a sandbox or dedicated workspace if you want to be extra cautious. Confirm there are no expectations of network access (none are present) and verify outputs before using them in production or publishing.
功能分析
Type: OpenClaw Skill Name: classroom-lesson-pack Version: 1.0.0 The bundle contains a script (scripts/run.py) that includes extensive file-scanning and auditing logic entirely unrelated to its stated purpose of generating classroom lesson plans. The script features a 'pattern_report' function with regex patterns designed to identify sensitive data such as API keys, tokens, and private URLs, as well as 'directory_audit' and 'skill_audit' modes. While the default configuration in resources/spec.json is set to a benign text-formatting mode, the presence of these latent capabilities for searching the filesystem for secrets and dangerous commands is highly irregular for an educational tool and represents a significant risk if the agent is redirected to use these functions.
能力评估
Purpose & Capability
Name/description (lesson-plan generator) match the included resources: a template, spec.json, examples, and a local Python script that produces structured Markdown. Requiring python3 is proportionate. No unexplained binaries, credentials, or remote endpoints are requested.
Instruction Scope
SKILL.md instructs the agent to assemble inputs and — if allowed — run scripts/run.py to generate output. The script reads files and directories provided by the user (it enumerates and reads many text file types and can scan directories), which is expected for an audit/reporting tool but means the agent will access any path you point it at. The skill does not instruct network calls or to transmit data to remote hosts.
Install Mechanism
No install spec is provided (instruction-only with a local helper script). No downloads, package installs, or archive extraction occur. This is the lower-risk model for distribution.
Credentials
No environment variables, credentials, or config paths are required. The script operates on local files and uses only the Python standard library, which is consistent with the stated purpose.
Persistence & Privilege
always is false and the skill is user-invocable. It does not modify other skills or system-wide configs. Autonomous invocation is allowed (platform default) but the skill itself does not request elevated or 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 classroom-lesson-pack
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /classroom-lesson-pack 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
Initial release of classroom-lesson-pack - Generates lesson plans, interactive questions, assignments, and differentiated teaching suggestions based on course objectives. - Clearly defines suitable and unsuitable usage scenarios, including compliance and safety boundaries. - Outputs draft and actionable checklists, prompting for missing information instead of guessing. - Organizes standard output into learning objectives, classroom process, interactive design, assignments, differentiated suggestions, and teaching materials. - Provides local resources and templates to assist lesson creation.
元数据
Slug classroom-lesson-pack
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

Classroom Lesson Pack 是什么?

根据课程目标生成教案、互动题、作业与分层教学建议。;use for education, lesson-plan, teaching workflows;do not use for 生成违规内容, 替代教师现场判断. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 269 次。

如何安装 Classroom Lesson Pack?

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

Classroom Lesson Pack 是免费的吗?

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

Classroom Lesson Pack 支持哪些平台?

Classroom Lesson Pack 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(darwin, linux, win32)。

谁开发了 Classroom Lesson Pack?

由 vx:17605205782(@52yuanchangxing)开发并维护,当前版本 v1.0.0。

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