SkillHub

interview

v3.0.0

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...

Sourced from ClawHub, Authored by AGIstack

Installation

Please help me install the skill `interview` from SkillHub official store. npx skills add AGIstack/interview

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