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University

该技能把学习全过程交给智能体管理:按目标生成等同于学位的课程体系与前置知识,安排学习日历,处理用户上传的 PDF、幻灯片和录音,生成练习与模拟考试并批改讲解,用间隔重复安排复习,并在 ~/university/ 目录下维护课程、进度与闪卡数据。支持自学、在读学生、转行、认证备考和家教五种模式。

ivangdavila
ivangdavila
热度 83.77
最近更新 2026-05-11 16:52:13
分类:知识依赖:读写文件 / 内部调用大模型应用场景:教学辅导 / 测验 / 笔记整理 / 日程安排 ...

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add university
Metadata
name
University
slug
university
version
1.0.0
description
Replace or complement traditional university with AI-powered degree programs, adaptive learning, exam preparation, and progress tracking.
metadata
{"clawdbot":{"emoji":"🎓","requires":{"bins":[]},"os":["linux","darwin","win32"]}}

When to Use

User wants to: learn a complete degree/career autodidactically, support their current university studies, prepare for certifications/exams, change careers with structured upskilling, or help someone else study. Agent manages the entire learning lifecycle.

Quick Reference

Area File
Degree/career setup degrees.md
Content generation content.md
Assessment & exams assessment.md
Planning & calendar planning.md
Progress tracking tracking.md
Study formats formats.md
Learning preferences feedback.md

Workspace Structure

All learning data lives in ~/university/:

~/university/
├── degrees/              # One folder per degree/career/certification
│   ├── index.md          # Active degrees list with status
│   └── [degree-name]/    # Per-degree folder
│       ├── curriculum.md # Full curriculum with modules
│       ├── progress.md   # Module completion, mastery levels
│       ├── calendar.md   # Exam dates, deadlines, milestones
│       └── modules/      # Study materials by module
├── resources/            # Uploaded PDFs, slides, recordings
├── exams/               # Test history, practice exams
├── flashcards/          # Spaced repetition card sets
└── config.md            # Study preferences, schedule, goals

Core Operations

New degree/career: User says what they want to learn → Generate complete curriculum equivalent to university degree → Map prerequisites → Estimate total time → Create study calendar → Store in degrees/[name]/.

Daily study: Check calendar and progress → Generate today's session (reading + exercises + review) → Adapt to available time → Track completion.

Content processing: User uploads PDF/audio/video → Extract key concepts → Generate summary → Create flashcards → Add to relevant module.

Assessment: Generate practice tests from studied material → Simulate real exam conditions → Correct with explanations → Update mastery tracking → Schedule review for weak areas.

Progress review: Show completion %, mastery by topic, time invested → Predict readiness for exams → Alert if falling behind → Suggest plan adjustments.

Critical Rules

  • Never generate exam answers without teaching first — explain WHY
  • Track what user knows vs doesn't know — don't assume mastery
  • Adapt difficulty progressively — start where user actually is
  • Spaced repetition is mandatory — schedule reviews automatically
  • Distinguish "studied" from "mastered" — require verification
  • Support multiple degrees simultaneously — keep them organized
  • Learn user's optimal study patterns — times, formats, duration

User Modes

Mode Focus Trigger
Autodidact Full degree replacement "I want to learn medicine/law/engineering"
Student Complement existing university "Help me with my classes/exams"
Career Change Upskilling with portfolio "I want to transition to data science"
Exam Prep Certifications, bar exams, etc. "Help me pass AWS/PMP/MIR"
Tutor Help someone else learn "Help my kid with school"

See degrees.md for setup workflows per mode.

On First Use

  1. Ask: What do you want to learn? (degree, skill, certification)
  2. Assess: Current knowledge level, available time per week
  3. Generate: Curriculum with realistic timeline
  4. Configure: Study preferences (formats, schedule, goals)
  5. Create: ~/university/ structure