智能面试问题生成器。基于JD分析、用户简历和公司特点,生成定制化面试问题。支持技术面试、系统设计、行为面试(STAR)、HR面试。提供不同难度级别(简单/中等/困难)。自动维护问题库,追踪练习历史。与jd-analyzer和interview-coach集成。
当用户需要:
基于以下维度生成问题:
编程题:
技术深度问题:
设计问题:
经典系统设计:
大规模系统:
STAR方法问题:
情景问题:
简单 (Easy):
中等 (Medium):
困难 (Hard):
{
"question_id": "unique_id",
"type": "technical|system_design|behavioral|hr",
"category": "algorithm|database|distributed_system|teamwork",
"difficulty": "easy|medium|hard",
"question_text": "...",
"tags": ["array", "dynamic_programming", "google"],
"created_at": "2024-01-01",
"times_asked": 0,
"success_rate": 0.0,
"related_skills": ["Python", "Algorithms"]
}
{
"practice_session": {
"session_id": "unique_id",
"date": "2024-01-01",
"company_id": "...",
"questions_practiced": [...],
"performance": {...},
"improvement_areas": [...]
}
}
使用Read工具读取:
data/companies/{company}.json - 目标公司和JD分析data/resume/base.json - 用户基础简历data/questions/technical.json - 现有技术问题库data/questions/behavioral.json - 现有行为问题库从JD分析中提取:
根据分析结果生成问题:
{
"generated_questions": {
"company": "Google",
"position": "Software Engineer L3",
"technical": {
"easy": [
{
"question_id": "tech_001",
"question": "实现一个LRU Cache",
"category": "data_structure",
"related_skills": ["Hash Table", "Doubly Linked List"],
"estimated_time": "20-30 minutes",
"follow_up_questions": ["如何O(1)时间复杂度实现?", "如何处理并发?"]
}
],
"medium": [...],
"hard": [...]
},
"system_design": [...],
"behavioral": [...],
"hr": [...]
}
}
将新生成的问题添加到对应的问题库文件:
data/questions/technical.jsondata/questions/behavioral.jsondata/questions/system_design.jsondata/questions/hr.json更新 data/analytics/question_generation.json:
{
"generation_history": [
{
"timestamp": "2024-01-01T10:00:00Z",
"company_id": "google",
"position": "Software Engineer L3",
"questions_generated": 15,
"question_types": ["technical", "behavioral", "system_design"],
"difficulty_distribution": {
"easy": 5,
"medium": 7,
"hard": 3
}
}
]
}
Google:
Meta (Facebook):
Amazon:
Microsoft:
Startup:
Junior (L2-L3):
Mid-level (L4):
Senior (L5):
Staff+ (L6+):
## 技术面试问题 - 中等难度
### 问题: 实现一个分布式缓存系统
**背景**:
- 需要支持高并发读写
- 数据需要持久化
- 节点可能故障
**要求**:
1. 设计系统架构
2. 讨论数据一致性策略
3. 处理节点故障
4. 优化性能
**评估要点**:
- CAP理论理解
- 分片策略
- 复制机制
- 一致性协议
- 性能优化
**预计时间**: 45分钟
**相关技能**: Distributed Systems, Cache, Consistency
{
"batch_questions": {
"company": "Google",
"position": "Software Engineer L3",
"total_questions": 20,
"questions_by_type": {
"technical": 8,
"system_design": 4,
"behavioral": 5,
"hr": 3
},
"estimated_preparation_time": "2-3 weeks",
"priority_order": [...]
}
}
此skill可被以下命令调用:
/interview/prep - 生成面试准备问题集/interview/simulate - 为模拟面试提供问题/company/questions - 生成公司特定问题/weakness/practice - 针对弱点生成练习题data/companies/*.json - 公司和JD数据data/resume/base.json - 用户简历data/questions/*.json - 问题库data/analytics/question_generation.json - 生成历史