Xpersona
A

AI Learning Tutor

CLAWHUB · Unverified

AI学习私教 - 搭知识库、规划路径、出题练习、批改讲解、总结输出。学练查写闭环，从零学成高手。支持任意学科：专业、考证、编程、论文等。 Skill: AI Learning Tutor Owner: smseow001 Summary: AI学习私教 - 搭知识库、规划路径、出题练习、批改讲解、总结输出。学练查写闭环，从零学成高手。支持任意学科：专业、考证、编程、论文等。 Tags: ai:1.0.0, education:1.0.0, knowledge-base:1.0.0, latest:1.0.0, learning:1.0.0, study:1.0.0, tutor:1.0.0 Version history: v1.0.0 | 2026-04-17T05:47:56.434Z | auto ai-learn-tutor 1.0.0 — 首发版本 - 集成知识库搭建、学习路径规划、自动出题与批改、错题整理、知识点总结等功能，覆盖学习全流程闭环。 - 支持多学科、多需求：专业课程、编程、论文、考证、语言等多领域自定义学习。 - 突出连贯体系、进度可视化、

62
Rank
84
Safety
995
Downloads

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 995 downloads reported by the source. Last updated 10/11/2026.

Avoid when

  • Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Install and run

Setup complexity: low.

clawhub skill install s17a72fh5mgpvvs3dm2ax0yq8984pnqc:ai-learn-tutor
  1. Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
  2. Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-smseow001-ai-learn-tutor/snapshot"

Run-check

$0.02 USD

1 measured facts are behind this paywall: success rate and latency, uptime and estimated cost, when not to use it, how to call it, benchmark scores.

Agents pay $0.02 in USDC. A card payment is $0.50, the smallest a card allows.

Documentation

CLAWHUB

4,871 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: ai-learn-tutor
version: 1.0.0
description: AI学习私教 - 搭知识库、规划路径、出题练习、批改讲解、总结输出。学练查写闭环，从零学成高手。支持任意学科：专业、考证、编程、论文等。
keywords: [AI学习私教,learnTutor,AI学习助手,学习效率,AI Agent,智能学习,学习闭环,搭建知识库,学习路径,练习测试,整理输出,学练查写]
---

# AI学习私教 LearnTutor

把**学、练、查、写**串成一个闭环，从零学成高手。

---

## 核心功能

### 1. 搭知识库
- 上传论文、文档、资料
- 自动构建专属知识库
- 向量检索 + RAG 召回

### 2. 规划学习路径
- 根据基础与目标
- 自动生成个性化学习路线
- 阶段里程碑设定

### 3. 练习测试
- 自动出题（选择题/简答题/计算题）
- 练习 → 批改 → 讲解
- 错题本自动整理

### 4. 整理输出
- 知识点自动总结
- 框架结构梳理
- 笔记生成 + 复习卡片

---

## 学习闭环流程

```
📚 资料输入 → 🧠 知识库构建 → 🗺️ 路径规划
       ↑                              ↓
       ← 📝 整理输出 ← 🎯 薄弱点强化
              ↑
         📖 学习 & 练习
              ↓
         ✅ 掌握 & 输出
```

---

## 使用方式

当用户说：
```
我想要学习机器学习
帮我制定学习计划
出几道题考考我
总结一下这个知识点
我不懂这个概念，解释一下
学习进度追踪
```

---

## 支持学科

- 🎓 **专业课程**：数学、物理、统计、金融工程
- 💻 **编程开发**：Python、机器学习、深度学习
- 📄 **论文研究**：文献阅读、论文复现
- 📝 **考证备考**：CFA、FRM、AI证书
- 🌍 **语言学习**：英语、中文、其他外语

---

## 教学原则

1. **连贯式教学**：不零散问答，有系统性
2. **循序渐进**：从基础到进阶
3. **讲练结合**：学完立刻练
4. **错题讲解**：错了就详细解释
5. **进度可视化**：知道自己学了多少

---

## 示例对话

**用户**：我想学习深度学习，从零开始

**AI私教**：
```
🎯 目标确认：从零掌握深度学习基础
📊 当前水平：假设零基础

🗺️ 个性化学习路径（共6周）：

Week 1-2: 数学基础
  → 线性代数回顾（矩阵运算、特征值）
  → 微积分基础（梯度、链式法则）
  → 练习题 + 批改

Week 3: Python + NumPy
  → 实战编程入门
  → 100道练习题

Week 4: 机器学习基础
  → 监督学习、无监督学习概念
  → 回归与分类

Week 5: 神经网络入门
  → Perceptron → MLP → 反向传播
  → 用NumPy实现

Week 6: 深度学习框架
  → PyTorch 入门
  → CNN / RNN 基础概念

📦 交付物：
- 每章练习题 + 答案
- 代码仓库
- 知识点笔记
```

---

## 知识点总结模板

```markdown
# [主题] 知识点总结

## 核心概念
- 概念1：
- 概念2：

## 关键公式
公式1：xxx
公式2：xxx

## 应用场景
- 场景1：
- 场景2：

## 常见误区
- 误区1：
- 误区2：

## 练习题
1. xxx
2. xxx
```

---

## 学习进度追踪

| 阶段 | 内容 | 状态 | 掌握度 |
|------|------|------|--------|
| Week 1 | 数学基础 | ✅ | 85% |
| Week 2 | Python | 🔄 | 60% |
| Week 3 | ML基础 | ⏳ | 0% |

---

## 核心优势

| 传统学习 | AI私教 |
|---------|--------|
| 零散问答 | 连贯体系 |
| 被动吸收 | 主动练习 |
| 无人批改 | 自动批改 |
| 不知道差距 | 进度可视化 |
| 资料难找 | 知识库自动构建 |

---

*让学习更高效，让知识更扎实*

_meta.json

{
  "ownerId": "kn7expjc3a3skyesxdg25d55n184p52s",
  "slug": "ai-learn-tutor",
  "version": "1.0.0",
  "publishedAt": 1776404876434
}

skill-card.md

## Description:

AI Learning Tutor helps learners build study knowledge bases, plan learning paths, generate practice questions, review answers, explain mistakes, and summarize knowledge across subjects such as coursework, certification prep, programming, research papers, and languages.

This skill is ready for commercial/non-commercial use.

## Publisher:

[smseow001](https://clawhub.ai/user/smseow001)

### License/Terms of Use:

MIT-0

## Use Case:

External learners use this skill as a general AI study tutor for turning materials and goals into structured learning plans, practice exercises, answer review, mistake explanations, notes, and progress summaries.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Broad study-related trigger phrases may activate the tutor during ordinary learning prompts.

Mitigation: Review whether the skill should handle the current prompt before relying on its study plan, exercise, or summary output.

Risk: Learners may upload sensitive documents when building a study knowledge base.

Mitigation: Avoid uploading sensitive materials unless the execution environment and document handling practices are trusted.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/smseow001/skills/ai-learn-tutor)
- [ClawHub publisher profile](https://clawhub.ai/user/smseow001)

## Skill Output:

**Output Type(s):** [Text, Markdown, Code, Guidance]

**Output Format:** [Markdown and conversational text with study plans, exercises, explanations, summaries, notes, progress tables, and occasional code examples]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [No executable files, persistence, credential handling, or hidden behavior were found in the release evidence.]

## Skill Version(s):

1.0.0 (source: SKILL.md frontmatter and ClawHub release metadata)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

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