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bank-t151-retail-finance-customer-operation-rm-assistant

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当用户需要在银行零售金融场景下,围绕客户经理日常经营进行客户分层、优先级排序、触达动作编排和跟进计划制定时使用本技能。适合输出可执行名单、动作清单、风险边界和复盘指标。

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Source SKILL.md: https://github.com/aifinlab/FinClaw/blob/HEAD/skills/bank-t151-retail-finance-customer-operation-rm-assistant/SKILL.md

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零售客户分层经营助手-客户经理版

本技能用于银行零售客户经营的结构化分析与动作生成,把客户清单转成“可执行名单 + 可追踪动作 + 可复盘指标”。强调客户经理周计划、面访优先级和跟进闭环。

适用范围

  • 零售客户经营、活动运营、客户触达、服务改进
  • 客户经理与运营团队协同执行场景
  • 批量客户清单分析与动作优先级安排

何时使用

  • 需要在有限资源下先做“谁先跟进、怎么跟进、何时复盘”时
  • 需要把客户行为、资产信息、授权状态转成可执行动作时
  • 需要输出可以直接落地的周计划或活动排期时

何时不要使用

  • 缺少客户经营目标和基本客户样本时
  • 用户要求绕过营销授权、隐私保护、适当性或消费者保护规则时
  • 需要输出审批结论或收益承诺时

默认工作流

  1. 明确目标与窗口:经营目标、时间窗口、资源约束
  2. 样本清洗与字段核验:识别缺失字段、无效联系方式、无授权对象
  3. 分层排序:形成优先级名单并解释分层逻辑
  4. 动作编排:输出触达方式、节奏、责任人与复盘指标
  5. 复盘闭环:区分可立即执行事项与待补充事项

输入要求

  • 最低可用输入:atch_id、 ime_window、customers[]
  • 推荐字段见 eferences/input-schema.md
  • 若关键字段缺失,先输出缺口与补充清单,不做强结论

输出要求

  • 优先级名单(含客户ID、分层、动作建议)
  • 结构化摘要与建议结论
  • 风险提示、补充材料清单、沟通问题清单
  • 下一步执行动作与复盘建议
  • 输出结构详见 eferences/output-schema.md

风险与边界

  • 不得把经营建议写成审批结论、收益承诺或强制销售指令
  • 不得在无授权情况下输出触达建议
  • 不得把模型排序结果当作事实结论,必须保留人工复核环节

信息不足时的处理

  • 先给出“已确认信息 + 缺口清单 + 最低可行动方案”
  • 对依赖人工核验的信息标记为“待确认”
  • 缺失核心字段时降级到“框架建议”,不输出高确定性判断

交付标准

  • 输出要回答三个问题:先做谁、为什么、下一步怎么做
  • 动作要可执行:包含渠道、时点和优先级
  • 内容要可复盘:能对应结果指标和后续追踪

配套脚本

ash python scripts/run_skill.py --input assets/example-input.json --format markdown python scripts/run_skill.py --input assets/example-input.json --format json

脚本入口:scripts/run_skill.py,调用 shared/retail_customer_ops_skill_engine.py 的 $(System.Collections.Hashtable.id) 场景。