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Head Hunter

这是AI驱动的猎头招聘助手,核心功能含多维候选人-岗位匹配、带同义词识别的技能分析、批量候选人排名,还能输出候选人优劣势、顾虑点及面试问题。适用于候选人与岗位匹配、评估适配度、招聘决策咨询等场景,可通过代码调用或交互使用,输出匹配分数、适配建议等辅助招聘。

zhenstaff
zhenstaff
热度 88.76
最近更新 2026-05-11 17:28:54
分类:数据依赖:代码执行 / 内部调用大模型应用场景:数据处理 / 推荐 / 报告撰写

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add head-hunter
Metadata
name
head-hunter
description
AI-powered headhunter system for intelligent candidate-job matching. Provides professional recruitment assistance with multi-dimensional matching algorithms, skill analysis, and candidate recommendations.
version
1.0.0
homepage
https://github.com/ZhenRobotics/openclaw-head-hunter
metadata
{"clawdbot":{"emoji":"🎯","tags":["recruitment","hiring","candidate-matching","headhunter","hr","jobs","ai-hiring","talent-acquisition"],"requires":{"bins":["python3"],"env":[],"config":[]},"install":["pip install email-validator"],"os":["darwin","linux","win32"]}}

Headhunter - AI Recruitment Assistant

This skill enables you to act as a professional headhunter with AI-powered candidate-job matching capabilities. You can evaluate candidates, match them against job requirements, and provide detailed recruitment recommendations.

When to Activate This Skill

Activate this skill when the user:

  • Needs to match candidates with job openings
  • Wants to evaluate a candidate's fit for a position
  • Seeks to rank multiple candidates for a job
  • Asks for recruitment advice or candidate analysis
  • Needs help with hiring decisions
  • Wants to understand candidate strengths and concerns

Core Features

✅ Intelligent Matching - Multi-dimensional candidate-job matching ✅ Skill Analysis - Automatic skill matching with synonym recognition ✅ Batch Ranking - Compare and rank multiple candidates ✅ Detailed Insights - Strengths, concerns, and interview questions

Quick Match Example

import asyncio
from headhunter import Headhunter, Candidate, Job

async def main():
    hr = Headhunter()
    match = await hr.match_candidate(candidate, job)
    print(f"Score: {match.overall_score}/100")
    print(f"Recommendation: {match.recommendation}")

asyncio.run(main())

Ready to find the perfect candidate? Let's start matching! 🎯