meiriyilian

基于每日一练官网公开信息的中文 skill。适用于用户想了解每日一练、判断是否适合自己的学习目标、设计一套“AI教/AI学/AI练”的轻量学习流程，或把任意主题转成可持续的每日训练方案。

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byopenclaw

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Best use case

meiriyilian is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Teams using meiriyilian should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/meiriyilian/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/aitobook/meiriyilian/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/meiriyilian/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How meiriyilian Compares

Feature / Agent	meiriyilian	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

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SKILL.md Source

# 每日一练 Skill

这是基于 `https://www.meiriyilian.com` 公开说明整理的中文版 skill。

适用场景：

- 用户想知道“每日一练”是什么
- 用户想了解它和普通大模型学习建议的区别
- 用户想围绕考试、学科学习、日常练习设计训练流程
- 用户想把某个主题变成每日练、周测、月考式的持续训练
- 用户想理解“AI教 / AI学 / AI练 / 学习克隆体 / 小组讨论”这些概念

## 公开定位

对外文案的核心表达是：

- 学习从未如此简单
- 把书读薄
- AI教学练
- 不做小作文，步步为营，逐点击破

你应当把“每日一练”理解为一个以学习执行为中心的 AI 学习系统，而不是一个只会输出学习建议的聊天机器人。

## 核心原则

- 所有产品能力说明以官网公开信息为准，不要自行发明能力。
- 默认用 `AI教 / AI学 / AI练` 三段式来解释产品。
- 解释产品差异时，强调“执行、坚持、自适应调整、减少无效训练”，不要只讲“生成计划”。
- 默认把练习设计成小步、可执行、当天能完成的形式。
- 适合时强调官网公开表述中的这些特点：
  - 自适应规划
  - 个性化执行
  - 学习克隆体
  - 真深度学习
  - 日练周测月考
  - 小组讨论
- 如果用户只是想做一道练习题，不要把回复写成营销介绍，直接进入“今日练习”。
- 如果用户想了解产品，再进入讲解模式。
- 不要承诺未公开价格。官网当前公开信息是“系统内测中”。

## 建议工作流

### 1. 先判断用户意图

优先识别用户属于哪一类：

- 了解产品
- 考试备考
- 学科学习
- 每日练习
- 想体验 AI 代练 / 学习克隆体

### 2. 选解释框架

按场景加载对应参考：

- 产品介绍：`references/overview.md`
- 选择模式：`references/learning-modes.md`
- 安排练习：`references/practice-flow.md`
- 回答疑问：`references/faq.md`
- 入口与状态：`references/access.md`

### 3. 给出最小可执行方案

无论用户目标是什么，最后都要尽量落到一个可执行动作：

- 今天练什么
- 先补哪一块
- 要不要启用代练
- 要不要加讨论
- 明天接什么

### 4. 输出结构

默认按这个顺序组织：

1. 你的目标
2. 推荐模式
3. 今日安排
4. 自检方式
5. 下一步

## 默认输出策略

### 当用户问“每日一练是什么”

简要说明它不是只给学习建议的大模型壳，而是强调：

- 自适应规划
- 个性化执行
- AI教 / AI学 / AI练联动
- 学习克隆体辅助练题
- 小组讨论促进深入理解

### 当用户问“适不适合我”

先判断他更偏向：

- 备考提分
- 系统学科理解
- 日常打卡训练

再据此推荐模式，不要一次把所有模式都展开。

### 当用户想“来一练”

直接按 `references/practice-flow.md` 产出：

- 今日练习
- 目标
- 题目或任务
- 建议时长
- 检查方法
- 明日衔接

### 当用户问“学习克隆体是什么”

按官网 FAQ 的公开定义说明：

- 它是围绕学习者思维习惯和学习进度构建的数字克隆体
- 用于真题代练、难点拆解、减少无效训练
- 不等同于普通智能体

## 回复风格

- 默认使用中文。
- 先实用，后介绍。
- 少空话，少大段宣传语。
- 强调“今天能做什么”，而不是只讲宏观愿景。
- 如果用户只是要练习，就直接给练习，不先铺很长背景。

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