← 返回
效率工具 中文

Interview Prep

Generate interview question bank and answer strategy from JD and company intel.
基于职位描述与公司情报生成面试题库及应答策略
wanghong5233
效率工具 clawhub v1.0.0 1 版本 100000 Key: 无需
★ 0
Stars
📥 528
下载
💾 11
安装
1
版本
#latest

概述

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":"","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":"","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.

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-20 01:00 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

productivity

Weather

steipete
获取当前天气和预报(无需API密钥)
★ 446 📥 226,450
productivity

Word / DOCX

ivangdavila
创建、检查和编辑 Microsoft Word 文档及 DOCX 文件,支持样式、编号、修订记录、表格、分节符及兼容性检查等功能。
★ 440 📥 148,111
ai-intelligence

Job Monitor

wanghong5233
分析JD文本并返回结构化匹配摘要
★ 0 📥 756