Classroom Lesson Pack

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.

Security Scan

The skill's code, instructions, and requirements are coherent with a local lesson-plan generator/auditor that expects python3 and local files; it does not require external credentials or network access and contains no obvious exfiltration or malicious behavior.

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.

Assessment

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.

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 <输入文件> --output <输出文件>
6. 如当前环境不能执行脚本，仍要基于 {baseDir}/resources/template.md 与 {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。