Skill: agistack/interview (version 3.0.0)

--- 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. --- # 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](references/research.md) - **Story Building**: See [references/stories.md](references/stories.md) - **Mock Interviews**: See [references/mock-interviews.md](references/mock-interviews.md) - **Salary Negotiation**: See [references/salary.md](references/salary.md) - **Difficult Questions**: See [references/difficult-questions.md](references/difficult-questions.md) - **Follow-up Strategy**: See [references/followup.md](references/followup.md) - **Handling Rejection**: See [references/rejection.md](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 |


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)