Interview

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name: interview description: Interview preparation system with company research, story building, and mock interview practice. Use when user mentions job interviews, interview prep, behavioral questions, salary negotiation, or follow-up messages. Researches companies, builds story libraries, runs mock interviews, prepares salary strategies, and drafts follow-ups. NEVER guarantees job offers.

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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

| Script | Purpose | |--------|---------| | research_company.py | Generate company research brief | | build_story.py | Build STAR format stories | | mock_interview.py | Run practice interview | | prep_salary.py | Prepare salary strategy | | draft_followup.py | Draft follow-up messages | | analyze_role.py | Analyze job description | | identify_gaps.py | Identify experience gaps | | log_feedback.py | Log post-interview feedback |