What makes calculus-intelligent-grading notable?

972 downloads. Trust evidence available

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calculus-intelligent-grading

高数多解法智能批改：计算题+证明题双模式，MathJax SVG，分步卡片，符号面板，手写模拟。省级培训专用 Skill: calculus-intelligent-grading Owner: daigxok Summary: 高数多解法智能批改：计算题+证明题双模式，MathJax SVG，分步卡片，符号面板，手写模拟。省级培训专用 Tags: latest:1.1.0 Version history: v1.1.0 | 2026-07-30T15:04:05.410Z | auto - Major redesign: Skill now supports dual-mode grading for both computational and proof-based calculus problems, emphasizing independent assessment of mathematical correctness rather than strict reference answer matching. - Intr

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

972

Updated

Oct 11, 2026

Version

1.1.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 972 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

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 972 downloadsadoption · observed Oct 11, 2026
Latest release: 1.1.0release · observed Jul 30, 2026
Handshake status: UNKNOWNsecurity

What changed

Newest first. Only changes that point at a source are listed.

Release 1.1.0release
- Major redesign: Skill now supports dual-mode grading for both computational and proof-based calculus problems, emphasizing independent assessment of mathematical correctness rather than strict reference answer matching. - Introduced multi-method recognition: Alternative correct solutions are identified and fairly graded, rewarding innovative but valid approaches. - Enhanced step-wise answering: LaTeX input with a symbol panel, keyboard shortcuts, and step-specific card system for both types of problems. - Visual features: Uses MathJax SVG rendering (not KaTeX), with handwriting simulation effects for more natural math input and review. - AI grading engine now utilizes structured prompts for in-depth analysis, logic evaluation, and method identification using DeepSeek API. - Focused on ease-of-use for training scenarios, supporting quick demonstration, symbol recommendations, and distinction between calculation and proof logic.
Observed Jul 30, 2026 · source

Install and run

Setup complexity: low.

clawhub skill install s1780ks0559aj0a6r3aabws5e983sfvy:calculus-intelligent-grading

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
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-daigxok-calculus-intelligent-grading/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

18,096 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: "calculus-intelligent-grading"
description: "高数多解法智能批改：计算题+证明题双模式，MathJax SVG，分步卡片，符号面板，手写模拟。省级培训专用"
---

# 高等数学多解法智能批改 Skill

## 概述

面向高等数学主观题的智能批改系统，支持**计算题**和**证明题**双模式。基于 MathJax SVG 渲染，提供符号面板、分步作答卡片、多解法评判和手写模拟。适用于省级大学数学 OpenClaw 培训场景。

## 核心设计理念

### 多解法评判原则

数学题允许多种正确解法。批改策略的核心是**独立评判数学正确性**，而非与单一标准答案比对。

- 计算题：参考答案只是其中一种解法，AI 独立判断计算正确性
- 证明题：常见证法仅供参考，AI 独立判断逻辑正确性
- 创新方法且逻辑正确 → 应得高分，不因「不常见」扣分

### 双模式批改

| 维度 | 🧮 计算题模式 | 📐 证明题模式 |
|:---|:---|:---|
| 评判重点 | 步骤计算正确性 | 逻辑完整性 + 定理使用 |
| 步骤类型 | 计算步骤 | 已知/假设/定理/推导/结论 |
| 错误分类 | concept / calculation / notation | 逻辑跳跃 / 循环论证 / 前提错误 |
| 输出 | 分步得分 + 方法识别 | 分步得分 + 逻辑结构分析 |
| 配色 | 紫色系 | 青色系 |

## 功能清单

### 1. 多模态输入
- LaTeX 文本输入（主输入方式）
- 数学符号面板（10 组，可搜索、可收藏）
- 智能符号推荐（根据题型/模式自动高亮相关符号组）
- 快捷键支持：`/`→分式、`^`→上标、`_`→下标、`Tab`→切换步骤

### 2. 分步作答系统
- 每步独立卡片：输入框 + 实时 MathJax 预览 + 语法状态灯
- 计算题：简洁步骤卡片
- 证明题：每步可选类型标签（已知/假设/定理/推导/结论）
- 动态增删步骤，自动重新编号

### 3. MathJax SVG 渲染
- 使用 MathJax 3 `tex-svg` 输出，而非 KaTeX
- 实时预览：250ms 防抖，`tex2svg` 验证语法后克隆到预览区
- 题目/订正渲染：`typesetPromise` 异步渲染
- 异步加载不阻塞 UI

### 4. 手写模拟
- MathJax SVG + `feTurbulence` 粗糙滤镜模拟笔触抖动
- 逐语义单元（`g[data-mjx-texclass]`）渐显动画
- 米色纸质背景

### 5. AI 批改引擎
- 调用 DeepSeek API 进行分步评判
- 计算题 Prompt：强调多解法、独立评判
- 证明题 Prompt：强调逻辑完整性、定理使用
- 返回结构化 JSON：分步得分 + 方法识别 + 错误类型 + 逻辑分析

## 批改 Prompt 模板

### 计算题
```
你是高等数学批改专家。请独立评判以下解答的数学正确性。

【题目】{latex}
【一种参考答案】{answer}
【常见解法】{methods}
【学生解答步骤】{steps}

⚠️ 核心原则：
1. 数学题允许多种解法，参考答案只是其中之一
2. 评判标准是数学正确性，不是是否与参考答案一致
3. 学生用不同方法得出正确结果 → 应得满分
4. 结果正确但中间步骤有瑕疵 → 适当扣分
5. 注意区分"计算错误"和"方法错误"

返回JSON：overall_score, approach, is_alternative_method, step_results, summary
```

### 证明题
```
你是高等数学证明题批改专家。请独立评判以下证明解答的数学正确性。

【证明题】{latex}
【可用定理】{theorems}
【常见证法参考】{methods}
【学生证明过程】{steps}

⚠️ 核心原则：数学证明允许多种路径。常见证法仅供参考，不要因为学生用了不同方法就扣分。只根据逻辑正确性评分。

返回JSON：overall_score, approach, is_valid_approach, step_results, logic_analysis, summary
```

## 使用方式

### 在培训中演示

1. 打开 `grading-demo/index.html`（单文件，无需服务器）
2. 选择一道计算题或证明题
3. 展示分步作答 + 符号面板
4. 提交批改，展示 AI 如何识别不同解法
5. 打开手写模拟，展示 MathJax SVG 渲染效果

### 培训要点

1. **多解法评判**：重点演示同一道题用不同方法作答，AI 都能正确识别和评分
2. **证明题逻辑分析**：选一道证明题，故意制造逻辑跳跃，看 AI 如何检测
3. **符号面板 + 快捷键**：降低学生 LaTeX 输入门槛
4. **MathJax vs KaTeX**：MathJax SVG 输出在手写模拟上的优势

## 技术栈

- **渲染引擎**：MathJax 3 (`tex-svg`)，CDN 加载
- **AI 接口**：DeepSeek Chat API
- **前端**：纯 HTML/CSS/JS，无框架，单文件部署
- **存储**：localStorage（收藏符号持久化）

## 适用场景

- 大学数学课程作业批改
- 考研数学辅导班练习批改
- 数学竞赛培训
- OpenClaw 教学培训演示

## 扩展方向

- 接入更多 AI 模型（通义千问、文心一言等）
- 批量批改模式
- 学情统计面板
- 错题本自动归类
- 板书/手写照片 OCR 输入

_meta.json

{
  "ownerId": "kn78tmpsm3jqmdzjc8fa5dzdcn83s0kp",
  "slug": "calculus-intelligent-grading",
  "version": "1.1.0",
  "publishedAt": 1785423845410
}

skill-card.md

## Description:

Supports demonstration of intelligent grading for higher-mathematics calculation and proof problems, including multi-method assessment, step-by-step scoring, MathJax SVG rendering, and handwriting-style review.

This skill is for demonstration purposes and not for production usage.

## Publisher:

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

### License/Terms of Use:

MIT-0

## Use Case:

Educators, training facilitators, and agent developers use this skill to demonstrate AI-assisted grading workflows for calculus exercises. It is aimed at training scenarios where agents evaluate mathematical correctness across alternative valid solution paths rather than strict answer matching.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Student answers, reference answers, and solution steps may be sent to DeepSeek during grading workflows.

Mitigation: Confirm data-sharing approval before use with real coursework, avoid student identifiers where possible, and document consent and data-retention requirements.

Risk: The referenced grading demo HTML is not included in this package.

Mitigation: Verify required demo assets are available before using the skill in a training session.

## Reference(s):


## Skill Output:

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

**Output Format:** [Markdown guidance with structured JSON response examples and implementation notes]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Outputs may describe DeepSeek API grading prompts, MathJax SVG rendering behavior, step-level scores, method identification, error categories, and logic analysis.]

## Skill Version(s):

1.1.0 (source: server release evidence)

## 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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