- name
- interview-prep
- description
- 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
- Collect input:
- Prefer job_id (from /api/jobs/recent) OR provide company + role_title + jd_text.
- 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}
- Parse response and present:
- summary - likely_focus - key_storylines - top interview questions (question, intent, answer_tips)
- 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.