Coding

Interview

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Interview preparation system with company research, story building, and mock interview practice. Use when user mentions job interviews, interview prep, behav...

What it does

Interview mastery system. Preparation that wins offers.

The skill document

Interview

Interview mastery system. Preparation that wins offers.

Critical Privacy & Safety

Data Storage (CRITICAL)

  • All interview data stored locally only: memory/interview/
  • No external job platforms connected
  • No application tracking systems integrated
  • No sharing of interview content
  • User controls all data retention and deletion

Safety Boundaries

  • ✅ Research companies and roles
  • ✅ Build story libraries from experience
  • ✅ Run mock interviews with feedback
  • ✅ Prepare salary negotiation strategies
  • NEVER guarantee job offers
  • NEVER provide false information
  • NEVER replace genuine preparation

Data Structure

Interview data stored locally:

  • memory/interview/research.json - Company research briefs
  • memory/interview/stories.json - Story library
  • memory/interview/practice.json - Mock interview records
  • memory/interview/salary.json - Salary research and strategies
  • memory/interview/feedback.json - Post-interview notes

Core Workflows

Research Company

User: "Research Acme Corp for my interview Friday"
→ Use scripts/research_company.py --company "Acme Corp" --role "Product Manager"
→ Generate comprehensive research brief with talking points

Build Story

User: "Help me build a story about the project failure"
→ Use scripts/build_story.py --situation "project-failure" --lesson "learned"
→ Structure STAR format story with specific details

Mock Interview

User: "Run a mock interview for PM role"
→ Use scripts/mock_interview.py --role "Product Manager" --level senior
→ Ask realistic questions, provide honest feedback

Prepare Salary

User: "How should I handle the salary question?"
→ Use scripts/prep_salary.py --role "Product Manager" --location "SF"
→ Research market data, prepare negotiation strategy

Draft Follow-up

User: "Draft thank you email for today's interview"
→ Use scripts/draft_followup.py --interview "INT-123" --tone professional
→ Generate specific, memorable follow-up message

Module Reference

  • Company Research: See references/research.md
  • Story Building: See references/stories.md
  • Mock Interviews: See references/mock-interviews.md
  • Salary Negotiation: See references/salary.md
  • Difficult Questions: See references/difficult-questions.md
  • Follow-up Strategy: See references/followup.md
  • Handling Rejection: See references/rejection.md

Scripts Reference

ScriptPurpose
research_company.pyGenerate company research brief
build_story.pyBuild STAR format stories
mock_interview.pyRun practice interview
prep_salary.pyPrepare salary strategy
draft_followup.pyDraft follow-up messages
analyze_role.pyAnalyze job description
identify_gaps.pyIdentify experience gaps
log_feedback.pyLog post-interview feedback

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