{
    "summary": {
        "overall_match": "候选人具备3D渲染与平面设计基础技能，但学历不满足统招本科的硬性要求，且过往经验偏向电商数码，缺乏高端工业产品视觉设计经验，关键评估信息缺失较多。",
        "key_strengths": [
            "具备3D建模渲染（KeyShot\/C4D）与平面设计复合技能",
            "熟悉AI生图与视频剪辑等岗位加分工具",
            "提供站酷作品集链接，具备一定的设计产出证明"
        ],
        "key_concerns": [
            "学历为统招大专，不满足JD明确要求的统招本科及以上硬性条件",
            "过往经验偏向电商数码产品，缺乏高端工业传感器及国际化品牌视觉设计经验",
            "工作时长、期望薪资、大小周及加班接受度等关键信息严重缺失，导致多个维度无法评估"
        ],
        "recommendation_summary": "候选人技术能力部分匹配，但存在学历硬性不符的风险，且稳定性、薪资、节奏等维度信息缺失导致整体置信度偏低。建议作为pending处理，需进一步核实学历是否可破格，并要求补充缺失信息。"
    },
    "dimensions": [
        {
            "name": "tech_power",
            "raw_score": 80,
            "confidence_level": "medium",
            "jd_requirement": "统招本科及以上，2年以上工业产品视觉设计经验，精通3D建模渲染与平面设计，必须兼具两者能力。",
            "resume_fulfillment": "候选人掌握KeyShot、C4D及PS、AI等工具，有3段设计经历，具备产品渲染与物料设计经验。但经验偏向电商数码，与高端工业传感器场景有差距，且学历为大专，综合评定为部分满足。"
        },
        {
            "name": "stability",
            "raw_score": 50,
            "confidence_level": "low",
            "jd_requirement": "JD未明确说明，按常规评估正式工作任职时长模式。",
            "resume_fulfillment": "候选人有三段工作经历，但具体起止时间全部缺失（显示为乱码），无法计算实际任职时长，信息不足。"
        },
        {
            "name": "salary_match",
            "raw_score": 50,
            "confidence_level": "low",
            "jd_requirement": "10-15K（含大小周），1~3个月年终奖。",
            "resume_fulfillment": "候选人未在简历中提供期望薪资，信息缺失。"
        },
        {
            "name": "pace_match",
            "raw_score": 65,
            "confidence_level": "low",
            "jd_requirement": "深圳办公，初创节奏，大小周（早9晚9），接受有效加班。",
            "resume_fulfillment": "候选人前公司均在上海\/深圳（简历显示深圳），求职状态为随时入职，地点与到岗时间匹配。但未说明是否接受大小周及有效加班，关键意愿缺失。"
        },
        {
            "name": "communication",
            "raw_score": 40,
            "confidence_level": "high",
            "jd_requirement": "此项为简历信息表达质量评估，JD无直接要求。",
            "resume_fulfillment": "简历模块基本清晰，但任职时间等关键字段全部缺失，且存在错别字与语病（如“竟品”、“片品宣图”），信息呈现质量一般。"
        }
    ],
    "match_score": 70.9,
    "overall_confidence": 0.45,
    "recommendation": "pending"
}

{
    "events": [
        {
            "eventName": "ObjectCreated:PutObject",
            "eventSource": "acs:oss",
            "eventTime": "2026-08-15T07:54:59.000Z",
            "eventVersion": "1.0",
            "oss": {
                "bucket": {
                    "arn": "acs:oss:cn-hangzhou:1748673497100614:langbowei-static",
                    "name": "langbowei-static",
                    "ownerIdentity": "1748673497100614",
                    "virtualBucket": ""
                },
                "object": {
                    "deltaSize": 5608,
                    "eTag": "777A1269935B59153E0504AFA6120523",
                    "key": "parsed\/resumes\/1-6a801b03-159ffb-5adc05f859f7__widget_1704704635359_0.pdf.parsed.json",
                    "objectMeta": {
                        "mimeType": "application\/json"
                    },
                    "size": 5608
                },
                "ossSchemaVersion": "1.0",
                "ruleId": "ca5b3a7a3f9032c56d393bfb816e6376962c91d8"
            },
            "region": "cn-hangzhou",
            "requestParameters": {
                "sourceIPAddress": "172.16.0.126"
            },
            "responseElements": {
                "requestId": "6A801B530CA22535349CA27B"
            },
            "userIdentity": {
                "principalId": "300891235492433224"
            }
        }
    ]
}