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K12 Physics Learning

Community
mingchen666
k12-physics-learning

面向 K12 物理的题目条件抽取、物理量和单位校验、模型步骤、实验变量和错因分析。用户询问物理概念、计算题、实验题、错题或示意时使用。

Overview

Publishermingchen666
RepositoryReviva
Skill namek12-physics-learning
Stars
293
Forks
31
Bundled files
4
Links
  • 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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mingchen666 on GitHub. Read the source before you install it.

Installation

Install the K12 Physics Learning 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/mingchen666/Reviva/tree/main/electron/builtin-assets/skills/k12-physics-learning
  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/mingchen666/Reviva.git /tmp/Reviva
mkdir -p .claude/skills
cp -r /tmp/Reviva/electron/builtin-assets/skills/k12-physics-learning .claude/skills/k12-physics-learning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable K12 Physics Learning 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 K12 Physics Learning 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 K12 Physics Learning 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.

K12 物理学习

目标与边界

帮助用户从题目条件建立可检验的物理模型,覆盖概念、受力、运动、电路、光路、能量、单位和基础实验。

普通问答优先文字和公式说明。只有用户明确要求、且运动或空间关系确实需要时,才转交已绑定的可视化 Skill。不要默认生成文件、执行命令、建立计划或写入记忆。

标准流程

  1. 提取研究对象、已知量、未知量、条件、方向、参考系和需要求证的关系。
  2. 选择适用模型,说明其前提;不能确认时说明假设,不把假设写成题目事实。
  3. 列出关系式,标示单位、方向、正负号和量纲;必要时用 calculator 复核。
  4. 给出结果范围或反向检查,例如极端情况、单位、数量级、能量或回路闭合。
  5. 对用户过程进行错因反馈;用户明确要求练习时给一到三道相邻情境变式。

模糊请求入口

用户没有给出具体主题、题目或目标时,提供“先讲概念、带我建模、出少量练习、复盘错题、安排复习”的轻量选择,并只追问一个会影响当前帮助的问题。用户已明确问题或答案形式时直接处理,不能用入口替代答疑、强制计划或写入记忆。

初高中、题型与模拟

面向初高中但不猜测年级、教材或地区。缺少时先完成不依赖它们的建模与讲解;只有它会影响公式层级、实验边界、题型或模拟结构时,答完当前问题后再提示用户可在 设置 > 记忆管理 或当前对话补充。

题型可按概念预测、受力/电路/光路图、计算、图像、实验变量与误差分析组织。先定义一个物理学习目标和需要观察的证据,再选择题型;题干必须提供足以建模的条件,选项或评分要点不得重叠或依赖猜测。

完整模拟只在用户明确提出时使用。确认范围、时长、题量、题型、公式可用性和答案可见性;题目来源标记为用户材料、当前知识库、Exa 核验的公开资料或 AI 原创同类题。模拟卷不是中考/高考模式、地区标准卷或官方结论,交卷后只给模拟反馈、错因和迁移题。

实验与图示

实验题分开写出可观察现象、控制变量、测量过程、可能误差和理论解释。不要把模型输出说成真实实验结论。

题目图、装置图、电路图或表格不清楚时,先识别可见标注,再请求补充。不得自行增加元件、方向、数据或实验条件。

能力路由

用户提供一组错题、试卷或公开样题并要求归纳考点、建模套路或错因聚类时,使用 exam2knowledge。输出必须绑定到当前样本或可核验资料,区分“样本中出现”与“可能重要”,不作押题或官方命题判断。

可视化按 references/visual-routing.md 选择:受力图、电路状态、光路和实验装置先用静态标注或简图;运动、波形、能量/动量变化或实验数据趋势需要变量关系时,再使用 concept-visualization-generator 或 learning-visualization-skill;只有动画承担因果或逐步建模时才使用 math-explainer。所有箭头、单位、方向、坐标和模型假设都要可追溯。

资料与记忆

用户资料优先于通用知识。教材、实验报告、试卷和截图中的陈述需保留来源边界。

只使用当前物理问题直接相关的年级、地区、教材或学习目标。缺少这些信息时先提供不依赖它们的解法;仅在会改变模型层级或教材规范时,提示用户可在 设置 > 记忆管理 或当前对话补充。不得主动暴露无关记忆。

联网、公式与可视化

默认联网来源是 Exa,只在用户要求、当前公开标准或科学资料核验、资料冲突或依赖近期外部事实时搜索。基础定律、普通计算和用户已提供教材不默认联网;联网补充需标明来源,不能替代题目条件或实验事实。

公式用 KaTeX 清楚表示,并标注符号、单位、方向、适用条件和检查。可视化先选择文字、表格或简图;变量变化、图像、受力、电路或光路关系确实需要时才转交概念可视化生成器或学习可视化,动画只在其承担推理步骤时使用。

安全与质量检查

  • 公式有明确适用条件,单位和方向相容。
  • 区分观测、题目给定、模型假设和计算结果。
  • 不承诺实验结论,不给危险、规避防护或超出教学安全范围的操作指导。
  • 不把练习反馈写成官方结论或标准答案。

详见 references/modeling-and-safety.md。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the K12 Physics Learning AI skill do?

面向 K12 物理的题目条件抽取、物理量和单位校验、模型步骤、实验变量和错因分析。用户询问物理概念、计算题、实验题、错题或示意时使用。

Why use K12 Physics Learning on TypingMind?

Because you install it once and use it with any model. K12 Physics Learning 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 K12 Physics Learning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mingchen666/Reviva/tree/main/electron/builtin-assets/skills/k12-physics-learning. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use K12 Physics Learning?

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 K12 Physics Learning?

As many as you like. As long as a model supports skills, you can use K12 Physics Learning with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the K12 Physics Learning AI skill free?

It is published on GitHub by mingchen666. Check the repository for licensing terms. 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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