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---5
6# Career Manager — Job Pipeline
7
8Automates job search: finds roles, tracks applications, tailors resumes, preps for interviews, and manages follow-ups.
9
10## Data File: `data/applications.json`
11
12```json
13{
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": null
28 }
29 ],
30 "stats": { "total_applied": 0, "responses": 0, "interviews": 0, "offers": 0, "response_rate": 0 },
31 "saved_roles": []
32}
33```
34
35## Resume Tailoring
36
37When 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 experience
414. Flag gaps and suggest how to address in cover letter
425. Rate overall match: "You match X/Y requirements strongly, Z partially, N gaps"
43
44## Interview Prep
45
46When interview is scheduled:
471. Web search: recent company news, product launches, tech blog
482. Research interviewer if name provided
493. Generate likely questions (technical, behavioral STAR format, system design)
504. Prepare talking points per project
515. Suggest questions user should ask
526. Send prep package 24h before
53
54## Follow-Up Management
55
56- 5 business days after apply, no response → draft follow-up email
57- After phone screen → draft thank-you within 24h
58- After technical → detailed thank-you referencing discussion
59- After onsite → personalized thank-you per interviewer
60- Track ghosting patterns
61
62## Application Updates via Natural Language
63
64- "heard back from [company]" → prompt for details, update status
65- "got rejected from [company]" → update to rejected, log reason
66- "have a phone screen with [company] next Tuesday" → update status, schedule prep
67- "got an offer!" → celebrate, then help evaluate
68
69## Instructions
70
711. Always check `data/applications.json` before suggesting roles (avoid duplicates)
722. Update JSON immediately after any career conversation
733. Be strategic — quality > quantity
744. Help spot patterns: what types of roles respond? What keywords work?
755. If <10% response rate after 20 apps, reassess approach
766. For interviews, always research first — never send generic prep
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