c6bd4aea27
Education (3): research-to-quiz, student-analysis, lesson-plan Healthcare (3): policy-compliance, meeting-minutes, data-report Design Shantou (4): trend-to-design, competitor-research, client-communication, supply-chain-collect
227 lines
6.7 KiB
YAML
227 lines
6.7 KiB
YAML
# ZCLAW Pipeline - 客户沟通辅助
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# 输入客户需求和沟通背景，生成专业沟通方案（邮件/报价单/产品推荐）
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apiVersion: zclaw/v1
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kind: Pipeline
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metadata:
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name: client-communication
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displayName: 客户沟通辅助
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category: design
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industry: design-shantou
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description: 输入客户需求和背景，自动生成专业沟通邮件、报价单、产品推荐书
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tags:
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- 汕头
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- 客户沟通
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- 报价
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- 外贸
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icon: 💬
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author: ZCLAW
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version: 1.0.0
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spec:
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inputs:
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- name: client_background
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type: text
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required: true
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label: 客户背景
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placeholder: |
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客户公司名、国家、主营业务
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例如：美国 ABC Toys Inc., 主营益智玩具零售
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- name: inquiry_details
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type: text
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required: true
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label: 询盘内容
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placeholder: 粘贴客户询盘原文或描述客户需求
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- name: communication_type
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type: multi-select
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required: false
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label: 生成内容
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default:
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- reply_email
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- quotation
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- product_recommendation
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options:
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- reply_email
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- quotation
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- product_recommendation
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- follow_up_plan
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- name: language
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type: select
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required: false
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label: 输出语言
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default: English
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options:
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- English
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- 中文
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- 双语
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- name: our_products
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type: text
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required: false
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label: 我方产品
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placeholder: 简述可供推荐的产品线和特点
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steps:
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# Step 1: 客户需求分析
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- id: analyze_inquiry
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description: 分析客户询盘和需求
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action:
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type: llm_generate
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template: |
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分析以下客户询盘：
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客户背景:
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```
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{{client_background}}
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```
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询盘内容:
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```
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{{inquiry_details}}
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```
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请生成 JSON 格式分析：
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{
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"client_profile": {
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"company": "公司名",
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"country": "国家",
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"industry": "行业",
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"business_type": "进口商/分销商/零售商",
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"estimated_size": "规模估计"
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},
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"requirements": [
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{"requirement": "具体需求", "priority": "高/中/低", "detail": "详细说明"}
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],
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"pain_points": ["痛点1", "痛点2"],
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"budget_indicator": "预算水平判断",
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"urgency": "紧急程度",
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"decision_factors": ["决策因素1", "决策因素2"]
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}
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input:
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client_background: ${inputs.client_background}
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inquiry_details: ${inputs.inquiry_details}
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json_mode: true
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temperature: 0.4
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max_tokens: 2000
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# Step 2: 产品推荐匹配
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- id: match_products
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description: 匹配推荐产品
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action:
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type: llm_generate
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template: |
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基于客户需求，匹配推荐产品：
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客户需求分析: ${steps.analyze_inquiry.output}
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我方产品: {{our_products}}
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请生成 JSON 格式推荐：
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{
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"recommendations": [
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{
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"product": "产品名称",
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"match_reason": "匹配理由",
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"specs": "规格参数",
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"suggested_price": "建议报价(FOB)",
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"moq": "最小起订量",
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"lead_time": "交货周期",
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"certifications": "相关认证",
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"competitive_edge": "竞争优势"
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}
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],
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"cross_sell_opportunities": ["交叉销售机会1"],
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"upsell_possibilities": ["向上销售可能1"]
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}
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input:
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analysis: ${steps.analyze_inquiry.output}
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our_products: ${inputs.our_products}
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json_mode: true
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temperature: 0.6
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max_tokens: 2500
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# Step 3: 生成沟通内容
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- id: generate_communications
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description: 生成专业沟通内容
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action:
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type: llm_generate
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template: |
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生成专业客户沟通内容：
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客户分析: ${steps.analyze_inquiry.output}
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产品推荐: ${steps.match_products.output}
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输出语言: {{language}}
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生成类型: {{communication_type}}
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请生成 JSON 格式：
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{
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"reply_email": {
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"subject": "邮件主题",
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"body": "邮件正文(专业、简洁、有吸引力)",
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"call_to_action": "行动号召"
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},
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"quotation": {
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"header": "报价单抬头",
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"items": [
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{"item": "产品", "description": "描述", "qty": 0, "unit_price": 0, "amount": 0}
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],
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"terms": "贸易条款",
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"validity": "报价有效期",
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"payment_terms": "付款条件",
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"notes": "备注"
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},
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"product_recommendation": {
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"title": "推荐书标题",
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"sections": ["章节1概述", "产品亮点", "合作优势"],
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"closing": "结束语"
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}
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}
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input:
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analysis: ${steps.analyze_inquiry.output}
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products: ${steps.match_products.output}
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language: ${inputs.language}
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communication_type: ${inputs.communication_type}
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json_mode: true
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temperature: 0.7
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max_tokens: 4000
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# Step 4: 跟进计划
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- id: follow_up_plan
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description: 生成客户跟进计划
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action:
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type: llm_generate
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template: |
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生成客户跟进计划：
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客户: ${steps.analyze_inquiry.output.client_profile}
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紧急度: ${steps.analyze_inquiry.output.urgency}
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请生成 JSON 格式：
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{
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"follow_up_steps": [
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{"day": 0, "action": "立即行动", "channel": "邮件/WhatsApp/电话"},
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{"day": 3, "action": "第一次跟进", "channel": ""},
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{"day": 7, "action": "第二次跟进", "channel": ""},
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{"day": 14, "action": "深度跟进", "channel": ""}
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],
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"relationship_building": ["关系维护建议1", "关系维护建议2"],
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"cultural_notes": "文化注意事项"
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}
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input:
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client_profile: ${steps.analyze_inquiry.output.client_profile}
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urgency: ${steps.analyze_inquiry.output.urgency}
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json_mode: true
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temperature: 0.5
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max_tokens: 1500
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outputs:
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inquiry_analysis: ${steps.analyze_inquiry.output}
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product_match: ${steps.match_products.output}
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communications: ${steps.generate_communications.output}
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follow_up: ${steps.follow_up_plan.output}
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on_error: stop
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timeout_secs: 240
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