Interview Prep

Generate interview question bank and answer strategy from JD and company intel.

Interview Prep Skill

Trigger

Activate when user asks:

• "帮我准备这家公司的面试题"
• "根据 JD 出一套面试问题"
• "给我这岗位的回答思路"
• "做一版可背诵的面试提纲"

Workflow

1. Collect input:
   • Prefer job_id (from /api/jobs/recent) OR provide company + role_title + jd_text.
2. Call:
   • POST http://127.0.0.1:8010/api/interview/prep
   • Body example:
     • {"job_id":"<job_id>","use_company_intel":true,"question_count":8}
   • Or:
     • {"company":"MiniAgent","role_title":"AI Agent Intern","jd_text":"...","use_company_intel":true,"question_count":8}
3. Parse response and present:
   • summary
   • likely_focus
   • key_storylines
   • top interview questions (question, intent, answer_tips)
4. Ask user whether to export/continue with mock Q&A.

Command templates (exec tool + curl)

• By job id:
  • curl -sS -X POST "http://127.0.0.1:8010/api/interview/prep" -H "Content-Type: application/json" -d '{"job_id":"<job_id>","use_company_intel":true,"question_count":8}'
• By custom input:
  • curl -sS -X POST "http://127.0.0.1:8010/api/interview/prep" -H "Content-Type: application/json" -d '{"company":"MiniAgent","role_title":"AI Agent Intern","jd_text":"Need Python, LangGraph, RAG","use_company_intel":true,"question_count":8}'

Constraints

• Keep output concise and actionable (avoid long generic theory).
• If API returns non-2xx, surface the raw error and ask user whether to retry.
• Do not claim interview certainty; present as "likely focus" with confidence.