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.json before 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
1---2name: lofy-career3description: 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.4---56# Career Manager — Job Pipeline78Automates job search: finds roles, tracks applications, tailors resumes, preps for interviews, and manages follow-ups.910## Data File: `data/applications.json`1112```json13{14 "applications": [15 {16 "id": "app_001",17 "company": "Example Corp",18 "role": "Software Engineer",19 "url": "",20 "status": "applied",21 "applied_date": "2026-02-01",22 "source": "linkedin",23 "contact": null,24 "notes": "",25 "follow_up_date": "2026-02-08",26 "interviews": [],27 "outcome": null28 }29 ],30 "stats": { "total_applied": 0, "responses": 0, "interviews": 0, "offers": 0, "response_rate": 0 },31 "saved_roles": []32}33```3435## Resume Tailoring3637When user shares a job description:381. Parse key requirements (must-have vs nice-to-have)392. Map each requirement to user's experience (read `profile/career.md`)403. Suggest bullet point rewrites emphasizing relevant experience414. Flag gaps and suggest how to address in cover letter425. Rate overall match: "You match X/Y requirements strongly, Z partially, N gaps"4344## Interview Prep4546When interview is scheduled:471. Web search: recent company news, product launches, tech blog482. Research interviewer if name provided493. Generate likely questions (technical, behavioral STAR format, system design)504. Prepare talking points per project515. Suggest questions user should ask526. Send prep package 24h before5354## Follow-Up Management5556- 5 business days after apply, no response → draft follow-up email57- After phone screen → draft thank-you within 24h58- After technical → detailed thank-you referencing discussion59- After onsite → personalized thank-you per interviewer60- Track ghosting patterns6162## Application Updates via Natural Language6364- "heard back from [company]" → prompt for details, update status65- "got rejected from [company]" → update to rejected, log reason66- "have a phone screen with [company] next Tuesday" → update status, schedule prep67- "got an offer!" → celebrate, then help evaluate6869## Instructions70711. Always check `data/applications.json` before suggesting roles (avoid duplicates)722. Update JSON immediately after any career conversation733. Be strategic — quality > quantity744. Help spot patterns: what types of roles respond? What keywords work?755. If <10% response rate after 20 apps, reassess approach766. For interviews, always research first — never send generic prep
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