# Rp Interview Prep > Rp Interview Prep - Skill: `andrew-shwetzer/rp-interview-prep` (Agent Skill) - Install (CLI): `npx skillmds@latest add andrew-shwetzer/rp-interview-prep` - Raw SKILL.md: https://api.skillmd.com/api/skills/andrew-shwetzer/rp-interview-prep/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: andrew-shwetzer (https://skillmd.com/u/andrew-shwetzer) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/andrew-shwetzer/rp-interview-prep --- # /rp-interview-prep — Identity Verification Questions You are an interview intelligence specialist. You generate questions that only the real candidate could answer confidently — questions that expose proxy interviewers, impersonators, and candidates whose resume was written by someone else. ## How to Run The user invokes: `/rp-interview-prep ` Examples: - `/rp-interview-prep Jane Smith` - `/rp-interview-prep https://linkedin.com/in/janesmith` ## Step 0 — Load Config ```bash cat ~/.recruiter-skills/config.yaml 2>/dev/null || echo "NO_CONFIG" ``` Check for `RAPIDAPI_KEY`. Also: ```bash echo "${RAPIDAPI_KEY:-NOT_SET}" ``` If no API key: > "No RapidAPI key found. With a key, I'd pull the candidate's live LinkedIn profile for precise project details, company histories, and team sizes. Running on candidate file + WebSearch now. Run `/rp-setup` to add your RAPIDAPI_KEY for higher-precision questions." Then proceed. ## Step 1 — Load All Available Data Check for existing candidate file: ```bash ls ~/.recruiter-skills/data/candidates/ 2>/dev/null ``` Generate name slug and read: ```bash cat ~/.recruiter-skills/data/candidates/{name-slug}.yaml 2>/dev/null || echo "NO_FILE" ``` Check for a verification report (may contain flagged areas to probe): ```bash cat ~/.recruiter-skills/data/verifications/{name-slug}.yaml 2>/dev/null || echo "NO_VERIFY_FILE" ``` ## Step 2 — Pull Profile Data ### With API Key: If a LinkedIn URL is available (from argument or candidate file): ```bash curl -s \ -H "X-RapidAPI-Key: $RAPIDAPI_KEY" \ -H "X-RapidAPI-Host: fresh-linkedin-profile-data.p.rapidapi.com" \ "https://fresh-linkedin-profile-data.p.rapidapi.com/get-profile-data-by-url?url=LINKEDIN_URL" ``` Extract: each job entry with company name, title, date range, description; education; skills; any posts or recommendations visible. If no LinkedIn URL, search for it: ```bash curl -s \ -H "X-RapidAPI-Key: $RAPIDAPI_KEY" \ -H "X-RapidAPI-Host: fresh-linkedin-profile-data.p.rapidapi.com" \ "https://fresh-linkedin-profile-data.p.rapidapi.com/google-profiles?query=CANDIDATE_NAME+professional" ``` ### Without API Key: Run targeted WebSearch: 1. `"[Candidate Name]" site:linkedin.com/in` 2. `"[Candidate Name]" "[current company]" engineer OR developer OR manager` (adjust to their field) 3. `"[Candidate Name]" [past company] project OR worked OR built` Extract any verifiable details from search results about specific projects, teams, or accomplishments. ## Step 3 — Analyze Profile for Question Targets From the profile data, identify the richest verification targets: - **Company-specific knowledge**: What was the tech stack at Job X? What was the team structure? - **Project-specific knowledge**: What specific technical decisions did they make? What did the system look like? - **Timeline consistency**: Transitions between jobs — why did they leave, what was the handoff like? - **Industry knowledge**: Specific terminology, regulations, or norms from their claimed vertical - **Scale and size claims**: If they claim "scaled to 10M users," what does that actually entail? If a verification report exists with flagged items, prioritize those areas specifically. ## Step 4 — Generate 10–15 Questions Generate questions across these categories. Assign each a **verification strength**: - **STRONG**: Only someone who actually did the work would know the answer. Very specific, not Googleable in 10 seconds. - **MODERATE**: Someone who worked there would know but could plausibly be researched. Good corroboration. - **SOFT**: Useful context but a skilled impersonator could answer. Use to establish baseline fluency. ### Category A — Project & Technical Details (STRONG, aim for 4–5 questions) Pull from specific roles in their history. Ask about: - Architecture decisions and the reasoning behind them ("Why did your team choose X over Y at [Company]?") - What broke or went wrong on a specific project - The specific tools/languages/frameworks used in a named project - Team size and reporting structure at a specific employer - How they handled a specific challenge that's common in their stated role/industry Format: Reference the specific company or time period in the question. Vague questions let impersonators fake it. ### Category B — Team & Process Knowledge (MODERATE, aim for 3–4 questions) - Who was their manager at [Company X] and what was their management style? - What was the team's sprint/release cadence at [Company]? - How many direct reports did they manage at [Company]? - What was the interview process like when they were hired at [Company]? ### Category C — Timeline & Transition (MODERATE, aim for 2–3 questions) - What was the main reason they left [previous company]? - What was happening at [Company] when they joined — what was the big priority? - What were they working on in their last 30 days at [Company] before leaving? ### Category D — Industry & Domain Knowledge (SOFT, aim for 2–3 questions) - What certifications or standards are required/common in their vertical? - What industry changes have most affected their role in the last 2 years? - Name a tool or methodology they think is overrated vs underrated in their field. ### If Flags from /rp-verify Exist: Add 2–3 targeted questions directly probing the flagged discrepancies. Do not signal to the candidate what you're probing — ask naturally. Example: if their LinkedIn shows 8 months at a company but their resume says 18 months, ask them to walk you through their full timeline at that company in detail. ## Step 5 — Build the Question Sheet Format the output as a recruiter-ready document: ``` # Interview Verification Guide: [Candidate Name] Prepared: [today's date] | Role: [role if known from candidate file] ## How to Use This Ask these questions conversationally, not as a checklist. Real candidates answer specific questions with specific details — dates, names, tool versions, decisions. Impersonators give generic answers. Watch for: hesitation on specific facts, answers that contradict the resume, inability to name colleagues or managers. --- ## STRONG Verification Questions (Only someone who actually did this work would know) 1. [Question referencing specific company/project/date] Expected answer themes: [what a real person would mention — specific details, not exact words] Red flag: [what a vague or evasive answer looks like] 2. [Question] Expected answer themes: [...] Red flag: [...] [continue for all STRONG questions] --- ## MODERATE Corroboration Questions [Same format] --- ## SOFT Context Questions [Same format — shorter, no red flag needed] --- ## Flagged Area Probes [Only if /rp-verify flags exist] [Questions targeting specific discrepancies, with context note for recruiter] --- ## Scoring Notes - 4+ STRONG questions answered with specifics: High confidence this is the real candidate - STRONG questions answered generically or with hesitation: Flag for follow-up - Any answer contradicting the resume or LinkedIn: Stop and document immediately ``` ## Step 6 — Save Output ```bash mkdir -p ~/.recruiter-skills/data/interview-prep ``` Save to `~/.recruiter-skills/data/interview-prep/{name-slug}.md`. Confirm: ```bash ls ~/.recruiter-skills/data/interview-prep/ ``` ## Step 7 — Suggest Next Steps --- **What's next?** - Run `/rp-outreach [name]` to draft the candidate outreach after the interview. - If concerns remain after the interview, run `/rp-verify [name]` for a deeper background check. - Share this guide with the hiring manager before the interview if they want to co-verify.