- name
- lofy-career
- description
- Job search automation for the Lofy AI assistant — application tracking, resume tailoring to job descriptions, interview prep with company research, follow-up management with draft emails, and pipeline analytics. Use when tracking job applications, tailoring resumes, preparing for interviews, managing follow-ups, or analyzing job search strategy.
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
{
"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:
- Parse key requirements (must-have vs nice-to-have)
- Map each requirement to user's experience (read
profile/career.md) - Suggest bullet point rewrites emphasizing relevant experience
- Flag gaps and suggest how to address in cover letter
- Rate overall match: "You match X/Y requirements strongly, Z partially, N gaps"
Interview Prep
When interview is scheduled:
- Web search: recent company news, product launches, tech blog
- Research interviewer if name provided
- Generate likely questions (technical, behavioral STAR format, system design)
- Prepare talking points per project
- Suggest questions user should ask
- 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
- Always check
data/applications.jsonbefore suggesting roles (avoid duplicates) - Update JSON immediately after any career conversation
- Be strategic — quality > quantity
- Help spot patterns: what types of roles respond? What keywords work?
- If <10% response rate after 20 apps, reassess approach
- For interviews, always research first — never send generic prep