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Teacher Biology Homework Generation

Community
hezkvectory
teacher-biology-homework-generation

帮助生物老师生成少而准、可批改、能反映真实掌握情况的分层作业，避免把作业变成题量堆叠。 Workflow: teacher_biology_homework_generation.run.

Overview

Publisherhezkvectory
Repositoryhermes-edu-skills
Skill nameteacher-biology-homework-generation
Stars
127
Forks
58
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by hezkvectory on GitHub. Read the source before you install it.

Installation

Install the Teacher Biology Homework Generation AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hezkvectory/hermes-edu-skills/tree/main/skills/teacher-tools/teacher-biology-homework-generation
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hezkvectory/hermes-edu-skills.git /tmp/hermes-edu-skills
mkdir -p .claude/skills
cp -r /tmp/hermes-edu-skills/skills/teacher-tools/teacher-biology-homework-generation .claude/skills/teacher-biology-homework-generation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Teacher Biology Homework Generation in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Teacher Biology Homework Generation on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Teacher Biology Homework Generation is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

生物作业生成 Skill

帮助生物老师生成少而准、可批改、能反映真实掌握情况的分层作业，避免把作业变成题量堆叠。

这个 Skill 解决什么问题 / Problem

帮助生物老师生成少而准、可批改、能反映真实掌握情况的分层作业，避免把作业变成题量堆叠。

最适合 / Best For

  • 生物课后巩固
  • 生物分层作业
  • 周末短练
  • 针对错题的补偿练习

不适合 / Not For

  • 超纲题海
  • 无法批改或没有答案依据的开放任务
  • 背名词多、解释少，学生不会用证据说明生命现象

使用前请准备 / Inputs

  • 年级和知识点
  • 预计完成时间
  • 基础/提高/挑战比例
  • 班级常见错误
  • 是否需要答案解析

推荐工作流 / Recommended Workflow

  • 先确定作业目标和完成时长。
  • 按概念辨析、图表分析、实验设计和生活应用分层
  • 按基础、提高、挑战设计题目或任务。
  • 给出答案、解析和批改关注点。
  • 标注学生完成后的反馈和加练规则。

输出格式 / Output Format

  • 作业目标
  • 预计时长
  • 基础题
  • 提高题
  • 挑战题
  • 答案解析
  • 批改关注点

质量检查 / Quality Checks

  • 题量必须匹配时长
  • 分层差异要清楚
  • 答案或评价标准可核验
  • 作业目标不能超过本课核心目标

没有平台工具时 / Standalone Fallback

  • 没有题库时，由 Agent 生成原创题并附答案。
  • 没有班级数据时，默认 60/30/10 分层。

示例提示 / Example Prompts

  • 给七年级生物生成 20 分钟分层作业，要有答案和批改关注点。
  • 生物这一课学生错得多，帮我做一份补偿练习。

适用场景 / When To Use

当学习者、家长、老师、学校或教育应用开发者需要处理以下场景时，可以使用这个 Skill。

最适合的场景：

  • 班级作业

适用角色：

  • 老师

调用信号 / Invocation Signals

意图：

  • teacher_biology_homework_generation
  • teacher_tools
  • 班级作业

示例表达：

  • 开始生物作业生成 Skill
  • 帮我做班级作业
  • 根据当前上下文执行生物作业生成 Skill

公开 Skill 契约 / Public Skill Contract

  • Workflow: teacher_biology_homework_generation.run
  • Category: teacher-tools
  • Stages: primary, junior, senior
  • Subjects: 生物
  • Abilities: 作业生成
  • Quality Tier: curated
  • Standalone Support: needs_user_input
  • Public Release: recommended
  • Requires Tools: context.load, entitlement.check, workflow.create, practice.generate_items, practice.grade_answers, organization.query_context, memory.write
  • Requires Data: 年级和学科/课题, 教材版本或单元, 班级基础/错题/课堂观察, 课时或作业时长
  • Export Mode: installable
  • Release Channel: recommended

成熟度备注：

  • 已按精品 Skill 标准补充边界、输入、工作流、输出格式和示例。

参数化使用 / Parameters

这个 Skill 不再把年级、册别、单元、知识点和难度拆成大量独立 Skill。请在调用时通过参数或自然语言补充这些信息。

  • Grades: 一年级, 二年级, 三年级, 四年级, 五年级, 六年级, 七年级, 八年级, 九年级, 高一, 高二, 高三
  • Semesters: 上册, 下册, 上册, 下册, 必修一, 必修二, 选择性必修
  • Scenarios: 班级作业
  • Difficulties: 基础, 标准, 提高
  • Parameterized Dimensions: grade, semester, unit, lesson, knowledgePointCodes, scenario, difficulty

独立 Hermes 使用方式 / Standalone Hermes Usage

这个 Skill 可以通过 Hermes 的 skills.external_dirs 作为外部 Skill 加载。

如果你有自己的工具、记忆、课程数据或 workflow runner，可以把它们与本 Skill 组合使用。如果没有外部工具，也可以直接使用上面的说明来引导对话，生成有用的学习或教学反馈。

Frequently asked questions

What does the Teacher Biology Homework Generation AI skill do?

帮助生物老师生成少而准、可批改、能反映真实掌握情况的分层作业，避免把作业变成题量堆叠。 Workflow: teacher_biology_homework_generation.run.

Why use Teacher Biology Homework Generation on TypingMind?

Because you install it once and use it with any model. Teacher Biology Homework Generation is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Teacher Biology Homework Generation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hezkvectory/hermes-edu-skills/tree/main/skills/teacher-tools/teacher-biology-homework-generation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Teacher Biology Homework Generation?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Teacher Biology Homework Generation?

As many as you like. As long as a model supports skills, you can use Teacher Biology Homework Generation with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Teacher Biology Homework Generation AI skill free?

Yes. It is published on GitHub by hezkvectory under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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