解决什么问题
它不是一个普通链接,而是一个可拆解的工作样本
适合解决“想看一个智能体原型(Agent)如何从提示词走向可运行应用”的学习问题。
本地完整包已通过基础压缩包检查;有说明文件(README),便于学员理解;包含可拆解的提示词和智能体指令素材;原清单识别到许可协议信息。
核心功能
它具体能做什么
- 支持日程查询、员工/候选人查找、创建会议或候选人记录、更新已有记录
- 强调重要动作需要 human supervision/用户同意,适合学习 Agent 权限边界
- 以工具模块方式连接 HR 数据和操作动作,不只是回答问题
- 适合做“HR Agent 怎么防止乱调用工具”的案例
工作原理
可以重点拆解哪一层结构
基本原理是:通过应用代码或 CLI 接收用户输入,调用大模型、提示词和相关依赖完成分析、对话或报告生成。
- 📅 Checking your schedule - It can fetch information about your upcoming meetings and calls.
- 💼 Employee and candidate lookup - Retrieving information about employees or candidates.
- 📝 Creating records - From scheduling meetings or calls to adding new candidates and more.
- 🔄 Updating existing records - Easily modify existing entries, like adding participants to existing meetings
- The lack of user consent for utilizing a tool at the moment makes the agent unlikely to attempt using that tool in further conversation. In such cases, it is recommended to create a new chat with a clean history.
适用边界
建议谁用,谁先不要用
适合
适合想学习 HR 助手、招聘智能体、多角色智能体或 Copilot 原型的学员、HR 数字化负责人和技术同学。
不适合
不适合希望不读说明文件(README)、不做环境适配、马上用于真实业务的用户。
使用方法
建议按这个顺序学习
- 先读说明文件、依赖清单和 package 配置,确认运行入口和依赖
- 先用示例数据或模拟数据运行,不接入真实候选人或员工数据
- 观察智能体的输入、处理过程和输出报告三段结构,再决定是否值得课堂演示
依赖提示:可能需要按说明文件(README)安装依赖、配置 API key 或在测试平台导入。
包内线索
从哪些文件开始看
关键文件
- README.md
- mint_agent/prompts/PromptController.py
说明文件信号(README)
- 📅 Checking your schedule - It can fetch information about your upcoming meetings and calls.
- 💼 Employee and candidate lookup - Retrieving information about employees or candidates.
- 📝 Creating records - From scheduling meetings or calls to adding new candidates and more.
- 🔄 Updating existing records - Easily modify existing entries, like adding participants to existing meetings
- The lack of user consent for utilizing a tool at the moment makes the agent unlikely to attempt using that tool in further conversation. In such cases, it is recommended to create a new chat with a clean history.
- Some tools are now restricted to operating only on certain modules due to the ease of testing and to narrow down options for the LLM so it provides more reliable results.
下载与来源
下载前需要先知道什么
保持原作者、来源和许可协议信息;使用模拟数据完成学习练习。
GitHub 下载链接:https://github.com/eVolpe-AI/AI-HR-Agent/archive/refs/heads/main.zip
GitHub 项目页:https://github.com/eVolpe-AI/AI-HR-Agent