什么是 JEE 备考助手？

JEE 技能是学生应对世界上竞争最激烈的工程考试之一的全方位数字伴侣。通过将此技能添加到您的 Openclaw Skills 收藏中，用户可以将他们的 AI 智能体转变为复杂的辅导助手，管理从日常时间表到深入错误分析的一切。它专注于高投资回报率 (ROI) 的方法，确保每小时的学习都针对最有可能提高学生最终百分位数的章节和主题。

该技能专为 JEE Main 和 Advanced 的严格要求而构建，可适应用户的特定情况——无论是平衡校内考试的在校生，还是致力于全年复习周期的复读生。它为物理、化学和数学提供了一个结构化的框架，将原始的模拟考试成绩转化为可操作的见解，引导学生走向他们的目标 IIT 或 NIT。

下载入口:https://github.com/openclaw/skills/tree/main/skills/ivangdavila/jee

安装与下载

1. ClawHub CLI

从源直接安装技能的最快方式。

2. 手动安装

将技能文件夹复制到以下位置之一

优先级：工作区 > 本地 > 内置

3. 提示词安装

将此提示词复制到 OpenClaw 即可自动安装。

JEE 备考助手 应用场景

• 根据 JEE Main 和 Advanced 考试剩余天数创建优化的学习计划。
• 根据历史权重，识别学生可以快速获得分数的具有高投资回报率的章节。
• 跟踪所有理科 (PCM) 章节的掌握水平，确保不遗漏任何主题。
• 将错误分为概念性、粗心大意或时间压力型，以改善考试心态。
• 根据特定类别的录取分数线和模拟考试趋势，预测大学和专业录取资格。

1. 通过定义学生个人资料（包括类别、当前分数范围和目标排名）来初始化系统。
2. 该技能分析考试倒计时，并生成专注于用户薄弱领域的优先每日时间表。
3. 每次学习环节和模拟考试结果都会记录到本地目录结构中，以保持持续的成长记录。
4. 利用错误模式检测，该技能突出显示特定科目或题型中反复出现的错误。
5. 助手为模拟考试提供战略建议，包括试卷作答顺序和时间分配，并通过多次 Openclaw Skills 迭代进行优化。

JEE 备考助手 配置指南

要部署此技能，您必须在智能体环境中设置本地数据架构。运行以下命令以初始化您的 JEE 跟踪系统：

mkdir -p ~/jee/subjects ~/jee/sessions ~/jee/mocks ~/jee/mistakes
touch ~/jee/profile.md ~/jee/feedback.md

建立后，在 profile.md 中填写您的目标考试日期和类别，以便 Openclaw Skills 逻辑能够量身定制建议。

JEE 备考助手 数据架构与分类体系

该技能使用结构化的 Markdown 分类法组织备考数据，以实现透明度和易访问性：

name: JEE
slug: jee
version: 1.0.0
description: Prepare for India's Joint Entrance Examination with progress tracking, weak area analysis, mock test strategy, and IIT/NIT targeting.

When to Use

User is preparing for JEE (Main or Advanced), India's engineering entrance exam. Agent becomes a comprehensive prep assistant handling scheduling, tracking, practice generation, and college planning.

Quick Reference

Data Storage

User data lives in ~/jee/:

~/jee/
├── profile.md       # Goals, target rank, exam dates, category
├── subjects/        # Per-subject and chapter-wise progress
├── sessions/        # Study session logs
├── mocks/           # Mock test results and analysis
├── mistakes/        # Error log with patterns
└── feedback.md      # What works, what doesn't

Core Capabilities

1. Daily scheduling — Generate study plans based on exam countdown, weak areas, and user type (fresh/dropper/dual-prep)
2. Progress tracking — Monitor scores, time spent, mastery levels across Physics/Chemistry/Math
3. Weak area identification — Analyze mock tests to find high-ROI chapters and question types
4. Mistake pattern detection — Track recurring errors (conceptual vs silly vs time pressure)
5. Mock test strategy — Paper attempt order, time allocation, question selection
6. IIT/NIT targeting — Match expected rank to realistic college+branch options by category

Decision Checklist

Before study planning, gather:

• Target exam (JEE Main only, or Main + Advanced)
• Days remaining to each attempt (Main Jan/Apr, Advanced May)
• Category (General, OBC-NCL, SC, ST, EWS)
• Current mock test score range
• User type (11th/12th student, dropper, boards+JEE dual prep)
• Coaching status (Kota, local, online, self-study)

Critical Rules

• ROI-first — Prioritize chapters with highest marks-per-hour potential for this user's gaps
• Track everything — Log sessions, scores, mistakes to ~/jee/
• Adapt to user type — Droppers need gap analysis; dual-prep needs board/JEE balance; parents need monitoring dashboards
• Mistake patterns over solutions — Don't just correct; categorize WHY they're wrong
• Wellbeing matters — Monitor for burnout, especially droppers; enforce rest when intensity is sustained
• Realistic expectations — Use historical cutoff data; never overpromise ranks