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lesson-visuals

@jiawenlv⭐ 0 stars

Design multimedia lesson presentation from a teaching brief, including illustrations, architecture diagrams, interactive models, code animations, and video within continuous articles.

Choose how to use this skill

You do not need every option. Choose the path your AI client supports. The stable page stays the same; versioned files are immutable.

1. Native installer

This listing has no registered native installer command. Use the complete package or source fallback below, depending on what your client supports.

Do not guess an installer command or replace an existing version without reviewing the diff.

2. Complete package recommended

Download the ZIP when available. It includes SKILL.md plus the references, security notes and version metadata.

No complete ProSkills package is published for this listing yet.

3. Prompt-only

Copy the prompt above when the agent can read the stable page or when you want to adopt the workflow without installing a skill.

Need only the instruction file?

Download SKILL.md only if your client requires a single file. The complete ZIP is safer for a full installation because it preserves the references and release context.

No path installs or executes anything by itself. Your agent still needs access to the project files. Before updating, compare the installed version and review the diff.

—/10

// RATINGS

⭐GitHub Stars
⭐ 0 on GitHubGitHub ↗

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// README

Agent Skills

面向 OpenAI Codex 和 Pi coding agent 的开源技能集合,覆盖学习项目初始化、教学展示、图解动画与技能复盘。采用 MIT License。

Skills for learning, visual explanations, and workflow improvement. Install with Codex's skill installer, Pi's package manager, or the local installer below. Instructions are mostly English; the teaching template is Chinese and can be adapted to your language.

技能目录

技能用途
teach初始化独立学习项目,生成项目教学说明、目标、计划和续学笔记;后续教学使用项目自己的说明
lesson-visuals为课文选择合适的文字、图解与交互,纯文字也是有效结果
excalidraw可编辑架构图、关系图及本地 SVG/PNG 导出
svg-animation精确 SVG、分步推导与交互模拟
manim-video按需制作数学动画视频
skill-retrospective根据真实使用证据改进指定技能,保留可复用决策

安装到 Codex

在 Codex 中发送以下内容即可安装单个技能(需要内置 skill-installer):

$skill-installer 从 https://github.com/jiawenlv/skills 安装 skills/teach,保留其 assets 和 agents 目录。

将 skills/teach 换成上表中的技能路径即可。需要全部技能时:

$skill-installer 从 https://github.com/jiawenlv/skills 安装 skills/ 下的全部六个技能,包含各自的资源文件,并保留目录名称。

安装后用 $teach 初始化学习项目,或用 $excalidraw 等名称调用。未出现在技能列表时,重启 Codex。不同安装方式不要重复安装同名技能。

安装到 Pi agent

已安装 Pi 的用户,在终端运行:

pi install git:github.com/jiawenlv/skills

在 Pi 中执行 /reload,然后调用:

/skill:teach 帮我初始化一个学习项目
/skill:excalidraw 画出这个系统的组件关系

只为当前项目安装可加 --local。更新和卸载:

pi update --extensions
pi remove git:github.com/jiawenlv/skills

pi update --extensions 会更新已配置的包。此仓库的根 package.json 只声明技能资源,没有安装钩子和运行时依赖。Pi 的安装命令不会安装可选绘图工具。

本地安装:Codex / Pi 共用

适合希望自己维护、修改或按需选择技能的用户。需要 Git 和 uv;以下命令适用于 macOS / Linux(Windows 可用 WSL)。

git clone https://github.com/jiawenlv/skills.git
cd skills
# 先预览;不会写入安装目录
uv run --no-project python scripts/install.py
# 安装全部技能到 ~/.agents/skills/
uv run --no-project python scripts/install.py --apply

安装单个或多个技能:

uv run --no-project python scripts/install.py --skill teach --skill skill-retrospective --apply

脚本会一并链接所选技能引用的其他仓库技能,避免相对引用断开。使用 --target ~/.pi/agent/skills 可指定 Pi 的独立目录,或指定项目的 .agents/skills 目录。默认目录可被 Codex 和当前 Pi 共同发现。

安装使用软链接,请保留克隆目录。更新时在克隆目录执行 git pull --ff-only,再让 agent 重新加载;若更新新增技能,重新运行安装脚本。重复执行不会改变已正确安装的链接。

已有同名技能时脚本会停止,不会覆盖。检查冲突内容后,只有确实需要替换才添加 --replace teach(可重复指定);旧内容移到目标目录旁的 skill-migration-backups/,脚本会输出备份路径。卸载时只删除对应软链接,例如 unlink ~/.agents/skills/teach,不要删除真实技能目录;恢复旧版本可将备份移回原安装位置。

使用条件与边界

  • teach 保留显式调用策略:Codex 使用 $teach,Pi 使用 /skill:teach。普通答疑和续学遵循生成的项目说明,不会重复初始化。
  • 技能是工作流说明,不自带模型、浏览器、图片生成服务或网站阅读器。某些流程需要文件读写、资料查询或独立子 agent;缺少能力时应说明未完成的验证。
  • 文字教学无需绘图依赖。Excalidraw 的可选工具需要 Node.js >= 22.12,按 工具说明 安装依赖与 Chromium。Manim 按技能中的官方指南用 uv 单独设置环境。
  • 课程、学习记录、私有路径、凭据和生成素材放在使用技能的项目中,不放在本仓库。安装技能不授权发布学习记录。

安装依据:OpenAI 官方技能文档、Pi Packages、Pi Skills。

贡献与来源

欢迎通过 Issues 提交问题,或通过 Pull Request 改进技能。提交时说明使用场景、实际问题和验证方式;保留技能调用策略,不加入私人学习记录或密钥。Python 脚本使用 uv 运行。

uv run --no-project python -m unittest discover -s tests -v
npm ci --prefix skills/excalidraw/tools --ignore-scripts
node --test skills/excalidraw/tools/render-excalidraw.test.mjs

教学技能从作者的 personal-studio 教学工作流整理;研究和公开技能参考保留在 研究依据。本仓库未打包那些第三方技能。Excalidraw 渲染器通过 npm 使用官方依赖,版本由其 lockfile 固定;第三方依赖仍适用各自许可证。本仓库原创文件使用 MIT。

// HOW IT'S BUILT

// FILES

2 files shipped with this skill. Inline text is the catalog copy. The upstream link is the source repository.

  • skills/lesson-visuals/SKILL.md8.8 KBee68727c4e32upstream ↗
    ---
    name: lesson-visuals
    description: Design multimedia lesson presentation from a teaching brief, including illustrations, architecture diagrams, interactive models, code animations, and video within continuous articles.
    ---
    
    # Visual lesson authoring
    
    Text alone is a valid final presentation. Select media only when it contributes to the learner's understanding, observation, or practice beyond what clear prose and examples already provide. The result of presentation design may be to create no visual assets. Do not optimize for variety, novelty, tool coverage, or visible production effort, and do not require different formats across lessons. Feedback, retries, and capability milestones can be expressed entirely in words.
    
    Own presentation, not curriculum or learner diagnosis. Read the delivery project’s local teaching instructions (normally TEACHING.md) when present. Start from its public-safe teaching brief: target capability, system position, reasoning path, worked example, practice prompt, and intended observation. If only a narrow visual is requested, infer enough of this context without requiring a full brief. Return missing premises or contradictory subject claims to content design before production; preserve its success criteria.
    
    The teaching agent follows the project contract to orchestrate a presentation pass for each complete lesson; the learner does not need to invoke this skill separately. Use the brief and working draft to produce one canonical Markdown or MDX lesson plus assets at the selected delivery location. Do not require a second maintained full-text Markdown source for an MDX page. Content changes return to the teaching agent for correctness checks and are applied to the same lesson and affected media. A text-only decision completes this pass without media production. Do not copy learner records or private paths into public artifacts, or add private-file imports to the website build. Before delivery, provide the actual lesson, media, and verification results for the independent review required by the project contract; do not launch a duplicate review for each visual asset.
    
    Identify what the learner should see, compare, predict, or manipulate, then choose the representation. For each substantive media element, decide its learning job, where it belongs in the reasoning, the action or observation, feedback or reveal behavior, and an accessible fallback. Keep this plan compact; it need not become a separate file. Do not default to dense textbook prose with decorative images, or turn every paragraph into a slide or card.
    
    Keep the explanation coherent across prose and media. Preserve the premises, indispensable reasoning, and an accessible way to recover the result; do not duplicate every visible step verbatim in prose. Place media beside the explanation it supports and signal which feature the reader should attend to.
    
    Resolve the delivery project from workspace/course instructions. Read its media and lesson contract for paths, supported components, theme tokens, and validation; never derive its location from this skill's installation. Use continuous articles, with Markdown or MDX according to the existing reader. Do not assume a reader or a particular component library already exists. No obligatory slides, full-screen presentation shell, or generated per-page slide files apply.
    
    Choose the representation from the learning task, the essential information, and the reader's context. Consider what the reader needs to compare, follow, predict, or explore, together with prior knowledge, device constraints, accessibility, and explicit preferences. Aim for a clear, accurate explanation with no unnecessary reading, memory, or operating burden.
    
    Prose, tables, static diagrams, animation, video, and interaction are complementary options. Static views can support direct comparison; animation can reveal continuity or timing; interaction can help test predictions and explore conditions. These are selection cues, not a fixed hierarchy. Select layout, pacing, and controls for the actual content; do not prescribe a universal orientation, frame count, or component. Remove complexity when it adds no understanding, while preserving necessary reasoning and the mechanism being taught.
    
    ## Presentation decisions
    
    - **Orientation:** for a large system, make major responsibilities and connections visible, highlight the current part, and distinguish intentionally opaque parts from explained ones. Return to the same conceptual frame as understanding grows; avoid a crowded map of every implementation detail.
    - **Motivation and comparison:** show the concrete problem or the observable difference between plausible approaches. Generated illustrations can make a situation or analogy tangible; label an analogy's limits and verify subject-specific details.
    - **Mechanism:** use a trace, linked states, or a code-driven animation where change, timing, or flow is the learning object. Expose the relevant state and assumptions. Let the reader step, pause, or replay at useful boundaries; preserve a stable view for comparison.
    - **Exploration:** use a small interactive model when changing an input, connection, parameter, or assumption helps test an explanation. Invite a prediction, expose the result, explain the discrepancy, and permit retry. Interactions are occasional tools, not a quota or decoration.
    - **Feedback and reward:** make consequences understandable and progress concrete. Show a criterion-specific explanation and a meaningful next challenge when applicable. Keep hints and solutions distinguishable from an independent attempt. Do not introduce streak penalties, mandatory competition, or points that impersonate mastery.
    
    Content design determines what response would count as evidence. The UI must not treat replaying an animation or opening a page as understanding. Unless an actual collection path exists and is authorized, keep page interactions local and invite the learner to bring their answer or observation back to the coach. Never claim to save assessment results, update private learning records, or personalize from uncollected data.
    
    ## Production and review
    
    After choosing the form, select an appropriate tool:
    
    - Relationships, architecture, and informal structural diagrams: [excalidraw](../excalidraw/SKILL.md).
    - Precise geometry, circuits, state traces, adjustable parameters, and short transformations: [svg-animation](../svg-animation/SKILL.md).
    - Complex continuous mathematical animation intended as a video: [manim-video](../manim-video/SKILL.md), only when its extra render cost adds value.
    - Illustrative scenes or analogies: use the available `imagegen` skill and image-generation tool. Read that skill when selected; use Agnes/MiniMax only when requested. Preserve the resulting local file. Explain a missing capability and use SVG/Excalidraw where suitable, without inventing generated output. Formulas, exact labels, and circuit wiring should be authored as verifiable text/vector content.
    
    Reuse the delivery project's supported components; add a course-specific interactive component when its state model requires it. Prefer semantic SVG colors and responsive view boxes. Preserve editable sources with the course or its designated authoring directory, and place final assets in the configured delivery location. Do not impose a website-specific component API on other readers.
    
    Before delivery, check that the chosen form supports the learning task, makes the essential information observable, and works in the reader's context. Consider whether a simpler alternative preserves those benefits; remove redundant elements and unexplained controls. Before rendering, polish Chinese captions, labels, subtitles, and teaching controls: check connections and pronoun references, use natural precise wording, remove repetition without losing premises or boundaries, then recheck technical meaning. Follow additional language conventions in the project contract. Global teach is an initializer and is not required during presentation. After embedding the media, complete the same final review of the whole lesson and check that the visible media text still matches the prose.
    
    Check subject-matter claims and modeled behavior against an appropriate primary source. Inspect the rendered result for Chinese text, clipped labels, arrow directions, legend consistency, and mobile readability. Exercise controls, pause/replay, reset, answer reveals, and boundary states; check keyboard operation, text alternatives, theme changes, and reduced motion. Do not make color, motion, hover, or fast reaction the sole way to access essential meaning. A reduced-motion or static fallback must preserve the relevant relationships and results, not merely stop on an uninformative first frame. If production fails, keep a correct static figure and written explanation, and report which asset was not verified. Generated material is never evidence of mastery.
    
  • README.mdupstream ↗

    Contents are not inlined in the catalog. Open the upstream file.

Plain-text copy, no login: /skill-bundles/jiawenlv-skills-skills-lesson-visuals.md

// REPO STATS

0 stars