{
    "summary": {
        "overall_match": "候选人具备丰富的车载智能硬件及嵌入式测试经验，技能栈与岗位核心需求高度重合，但缺乏JD明确要求的AI工具辅助测试经验，且期望城市与岗位地点不符。",
        "key_strengths": [
            "具备9年车载软硬件及嵌入式测试经验，有复杂光学及投影项目主导经验",
            "熟悉底层信号测试、台架联调及示波器等硬件测试仪器，自动化脚本开发能力扎实"
        ],
        "key_concerns": [
            "简历未体现JD明确要求‘必须熟练使用’的AI工具辅助测试经验",
            "期望工作城市为北京，与苏州岗位地点存在差异，且未说明对大小周及早9晚9的接受度",
            "历史多段任职时间较短，平均历史任职年限仅为2年，稳定性存在潜在风险"
        ],
        "recommendation_summary": "候选人核心硬技能部分满足，但缺失JD明确列为‘必须’的AI工具使用经验，触发硬性约束风险；同时存在稳定性潜在风险及地点\/节奏信息缺失，综合评估建议淘汰。"
    },
    "jd_analysis": {
        "must_requirements": [
            "全日制统招本科及以上，电子\/计算机\/自动化相关专业",
            "5年以上嵌入式固件或硬件产品测试经验",
            "熟悉ARM等MCU架构，能阅读C\/C++代码，理解中断、RTOS调度",
            "熟悉UART、I2C、SPI、USB等接口协议，会用示波器\/逻辑分析仪",
            "熟练使用Python\/C++\/Shell至少一门语言",
            "必须熟练使用AI工具辅助测试工作（面试需展示案例）",
            "接受苏州线下办公及大小周(早9晚9)工作安排"
        ],
        "preferred_requirements": [
            {
                "requirement": "有工业相机、读码器、安防、物联网产品测试经验",
                "importance": "high"
            },
            {
                "requirement": "了解ISP Pipeline或图像质量测试",
                "importance": "medium"
            },
            {
                "requirement": "有功耗测试、信号完整性测试经验",
                "importance": "low"
            }
        ],
        "job_environment": {
            "city": "苏州",
            "work_mode": "大小周(早9晚9)",
            "pace": "高速成长期硬科技企业，多项目并行",
            "company_stage": "高速成长期",
            "arrival_requirement": "2026-08-31"
        },
        "salary_range": {
            "min_k": 15,
            "max_k": 25,
            "median_k": 20,
            "source": "explicit"
        }
    },
    "hard_requirements_check": [
        {
            "requirement": "全日制统招本科及以上，电子\/计算机\/自动化相关专业",
            "status": "partially_met",
            "evidence": "候选人本科毕业于吉林外国语大学数字媒体技术专业，属广义计算机\/理工类，但非JD严格指定的电子\/自动化核心专业。"
        },
        {
            "requirement": "5年以上嵌入式固件或硬件产品测试经验",
            "status": "met",
            "evidence": "候选人拥有9年测试经验，近期3年在北京一数科技负责车载投影、光感脚踢等嵌入式及硬件产品测试，具备独立负责复杂项目经历。"
        },
        {
            "requirement": "熟悉ARM等MCU架构，能阅读C\/C++代码，理解中断、RTOS调度",
            "status": "partially_met",
            "evidence": "简历提及嵌入式测试、底层信号交互及SOA\/ECAN信号测试，但未明确提及ARM\/MCU架构及RTOS调度机制。"
        },
        {
            "requirement": "熟悉UART、I2C、SPI、USB等接口协议，会用示波器\/逻辑分析仪",
            "status": "partially_met",
            "evidence": "明确提及熟练使用示波器、万用表及LIN\/CAN通讯，但未明确列出UART、I2C、SPI、USB等具体协议。"
        },
        {
            "requirement": "熟练使用Python\/C++\/Shell至少一门语言",
            "status": "met",
            "evidence": "个人优势及技能栈中明确列出熟悉Python、Shell，并有基于XML\/Python编写自动化脚本的实际项目经验。"
        },
        {
            "requirement": "必须熟练使用AI工具辅助测试工作",
            "status": "unmet",
            "evidence": "简历全文未提及任何使用ChatGPT、Copilot等AI工具辅助生成用例、编写脚本或分析日志的经验。"
        }
    ],
    "dimensions": [
        {
            "name": "tech_power",
            "raw_score": 75,
            "confidence_level": "high",
            "confidence_coefficient": 1,
            "adjusted_score": 75,
            "base_weight": 0.3,
            "adjusted_weight": 0.375,
            "score_breakdown": [
                {
                    "item": "中性基准",
                    "score_change": 50,
                    "evidence": "初始基准分"
                },
                {
                    "item": "核心要求匹配",
                    "score_change": 0,
                    "evidence": "嵌入式\/硬件测试及Python\/Shell满足(+15)，AI工具明确缺失(-15)，MCU及接口协议部分满足，综合计0分"
                },
                {
                    "item": "加分技能",
                    "score_change": 5,
                    "evidence": "具备车载光学产品、TOF性能及投影测试经验，命中图像质量\/物联网相关加分项"
                },
                {
                    "item": "项目证据",
                    "score_change": 15,
                    "evidence": "主导车内投影、岚图H56D光感脚踢等复杂软硬件协同项目，有明确量产交付及EOL验证成果"
                },
                {
                    "item": "经验深度",
                    "score_change": 5,
                    "evidence": "9年工作经验，超出JD要求的5年，超出4年"
                }
            ],
            "reason": "候选人具备扎实的嵌入式及车载硬件测试经验，项目成果丰富，但缺失JD明确要求的AI工具辅助测试经验，导致核心要求部分扣分。"
        },
        {
            "name": "stability",
            "raw_score": 40,
            "confidence_level": "medium",
            "confidence_coefficient": 0.8,
            "adjusted_score": 42,
            "base_weight": 0.25,
            "adjusted_weight": 0.3125,
            "score_breakdown": [
                {
                    "item": "中性基准",
                    "score_change": 50,
                    "evidence": "初始基准分"
                },
                {
                    "item": "历史任职均值",
                    "score_change": -10,
                    "evidence": "最近一段任职36个月(>12个月)，但历史4段任职(吉利10m, 理想6m, 镁佳27m, 启辕25m)四舍五入后均值为2年，低于通过标准(<=2年)"
                }
            ],
            "reason": "候选人最近一段工作任职满3年，但历史多段任职时间较短（存在多段不足1年的经历），历史平均任职年限仅为2年，稳定性低于通过标准。"
        },
        {
            "name": "salary_match",
            "raw_score": 95,
            "confidence_level": "high",
            "confidence_coefficient": 1,
            "adjusted_score": 95,
            "base_weight": 0.2,
            "adjusted_weight": 0.25,
            "score_breakdown": [
                {
                    "item": "中性基准",
                    "score_change": 50,
                    "evidence": "初始基准分"
                },
                {
                    "item": "薪资匹配",
                    "score_change": 45,
                    "evidence": "候选人期望薪资23-24K，完全落在JD预算15-25K范围内"
                }
            ],
            "reason": "候选人期望薪资与岗位预算范围高度匹配，无薪资超支风险。"
        },
        {
            "name": "pace_match",
            "raw_score": 50,
            "confidence_level": "low",
            "confidence_coefficient": 0,
            "adjusted_score": null,
            "base_weight": 0.2,
            "adjusted_weight": null,
            "score_breakdown": [
                {
                    "item": "中性基准",
                    "score_change": 50,
                    "evidence": "初始基准分"
                }
            ],
            "reason": "候选人期望城市为北京，未明确说明是否接受苏州办公、大小周及早9晚9的工作节奏，信息缺失无法进行有效加减分。"
        },
        {
            "name": "communication",
            "raw_score": 95,
            "confidence_level": "high",
            "confidence_coefficient": 1,
            "adjusted_score": 95,
            "base_weight": 0.05,
            "adjusted_weight": 0.0625,
            "score_breakdown": [
                {
                    "item": "中性基准",
                    "score_change": 50,
                    "evidence": "初始基准分"
                },
                {
                    "item": "结构清晰度",
                    "score_change": 10,
                    "evidence": "模块划分清晰，包含个人优势、工作经历、项目经历，阅读顺序合理"
                },
                {
                    "item": "信息完整度",
                    "score_change": 10,
                    "evidence": "任职时间、职位、公司和项目字段完整"
                },
                {
                    "item": "证据表达",
                    "score_change": 15,
                    "evidence": "项目描述包含明确的背景、个人动作和量化结果（如‘蓝牙故障问题率降低90%’、‘回归测试效率提升60%+’）"
                },
                {
                    "item": "一致性",
                    "score_change": 10,
                    "evidence": "技能、经历、项目和时间线相互一致，无明显矛盾"
                }
            ],
            "reason": "简历结构清晰，信息完整度高，项目描述具备明确的动作与量化结果，信息表达质量优秀。"
        }
    ],
    "information_coverage": 0.8,
    "overall_confidence": 0.75,
    "match_score": 70.9,
    "bonus_items": [
        {
            "dimension": "salary_match",
            "score": 95,
            "confidence": "high",
            "impact": 3,
            "evidence": "期望薪资23-24K完全在15-25K预算范围内"
        },
        {
            "dimension": "communication",
            "score": 95,
            "confidence": "high",
            "impact": 0.75,
            "evidence": "简历结构清晰，项目描述包含量化结果，表达质量优秀"
        }
    ],
    "risks": {
        "hard_constraint_risks": [
            {
                "dimension": "tech_power",
                "requirement": "必须熟练使用AI工具辅助测试工作",
                "evidence": "JD明确要求必须熟练使用AI工具且面试需展示案例，候选人简历全文未提及任何AI工具使用经验，状态为unmet。",
                "impact": 4.5
            }
        ],
        "confirmed_high_risks": [],
        "potential_risks": [
            {
                "dimension": "stability",
                "requirement": "历史任职稳定性",
                "evidence": "历史4段正式工作平均任职年限四舍五入后为2年，低于通过标准，原始分40分，存在潜在稳定性风险。",
                "impact": 2
            }
        ]
    },
    "missing_information": [
        "是否接受苏州线下办公",
        "是否接受大小周(早9晚9)工作安排",
        "到岗时间是否能满足2026-08-31的要求"
    ],
    "recommendation": "reject",
    "recommendation_reason": "候选人简历未体现JD明确要求‘必须熟练使用’的AI工具辅助测试经验，存在不可协商的硬性技能缺失风险（hard_constraint_risk）；同时历史任职平均年限较短，稳定性存在潜在风险；且期望城市与岗位地点不符，关键节奏与地点信息缺失。综合评估触发reject规则。"
}

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