Job Search

---

name: Job Search slug: job-search version: 1.0.1 changelog: Minor refinements for consistency description: Navigate job hunting with application tracking, company research, and interview preparation. metadata: {"clawdbot":{"emoji":"💼","requires":{"bins":[]},"os":["linux","darwin","win32"]}}

When to Use

User is job hunting — searching for positions, applying to companies, or preparing for interviews. Agent handles opportunity tracking, company research, application materials, and interview prep.

Architecture

Memory lives in ~/job-search/. See memory-template.md for setup.

~/job-search/
├── memory.md          # HOT: preferences, target criteria
├── applications.md    # Active pipeline
├── companies.md       # Research on target companies
├── materials/         # CV versions, cover letters
└── archive/           # Closed applications

Quick Reference

Core Rules

1. Quality Over Volume

• 5 targeted applications beat 50 generic ones
• Each application needs company-specific customization
• Never spray-and-pray — it burns reputation

2. Verify "Remote" Claims

Before recommending remote positions, check:

• Geographic restrictions ("US only", "EU timezone required")
• Tax/legal requirements in fine print
• Actual timezone overlap expectations

3. Detect Red Flags

4. Preserve User Voice

• Materials must sound like the USER, not generic AI
• Ask for writing samples to match tone
• Never over-optimize with keywords at cost of authenticity
• Recruiters detect AI-written content — personalization matters

5. Track Application State

Maintain in ~/job-search/applications.md:

• Company, role, date applied
• Current status, next action
• Contacts, interview dates
• Follow-up reminders

6. Research Before Applying

For each target company, gather:

• Financial health (funding, revenue trends)
• Glassdoor sentiment (filter for recency)
• Recent news (layoffs, acquisitions)
• Hiring manager profile if findable

7. Adjust for User Context

Common Traps

• ATS optimization kills authenticity — keyword stuffing passes filters but humans reject robotic text
• Salary data goes stale fast — verify ranges are current, not 2-year-old estimates
• "Perfect match" overconfidence — 60% requirement fit still means likely rejection
• Networking advice without context — cold outreach fails without warm introduction strategy
• Long-term advice for urgent needs — "build your brand" doesn't pay rent this month