lofy-career

Lofy AI 助手的求职自动化——申请跟踪、根据职位描述定制简历、通过公司研究准备面试、通过电子邮件草稿进行后续管理以及管道分析。在跟踪工作申请、定制简历、准备面试、管理后续工作或分析求职策略时使用。

## 概述（中文）

Lofy AI 助手的求职自动化——申请跟踪、根据职位描述定制简历、通过公司研究准备面试、通过电子邮件草稿进行后续管理以及管道分析。在跟踪工作申请、定制简历、准备面试、管理后续工作或分析求职策略时使用。

## 原文

# Career Manager — Job Pipeline

Automates job search: finds roles, tracks applications, tailors resumes, preps for interviews, and manages follow-ups.

## Data File: `data/applications.json`

```json
{
  "applications": [
    {
      "id": "app_001",
      "company": "Example Corp",
      "role": "Software Engineer",
      "url": "",
      "status": "applied",
      "applied_date": "2026-02-01",
      "source": "linkedin",
      "contact": null,
      "notes": "",
      "follow_up_date": "2026-02-08",
      "interviews": [],
      "outcome": null
    }
  ],
  "stats": { "total_applied": 0, "responses": 0, "interviews": 0, "offers": 0, "response_rate": 0 },
  "saved_roles": []
}
```

## Resume Tailoring

When user shares a job description:
1. Parse key requirements (must-have vs nice-to-have)
2. Map each requirement to user's experience (read `profile/career.md`)
3. Suggest bullet point rewrites emphasizing relevant experience
4. Flag gaps and suggest how to address in cover letter
5. Rate overall match: "You match X/Y requirements strongly, Z partially, N gaps"

## Interview Prep

When interview is scheduled:
1. Web search: recent company news, product launches, tech blog
2. Research interviewer if name provided
3. Generate likely questions (technical, behavioral STAR format, system design)
4. Prepare talking points per project
5. Suggest questions user should ask
6. Send prep package 24h before

## Follow-Up Management

- 5 business days after apply, no response → draft follow-up email
- After phone screen → draft thank-you within 24h
- After technical → detailed thank-you referencing discussion
- After onsite → personalized thank-you per interviewer
- Track ghosting patterns

## Application Updates via Natural Language

- "heard back from [company]" → prompt for details, update status
- "got rejected from [company]" → update to rejected, log reason
- "have a phone screen with [company] next Tuesday" → update status, schedule prep
- "got an offer!" → celebrate, then help evaluate

## Instructions

1. Always check `data/applications.json` before suggesting roles (avoid duplicates)
2. Update JSON immediately after any career conversation
3. Be strategic — quality > quantity
4. Help spot patterns: what types of roles respond? What keywords work?
5. If <10% response rate after 20 apps, reassess approach
6. For interviews, always research first — never send generic prep