Generate conservative, editable English outreach drafts for foreign-trade sales from structured lead inputs and customer-intel signals. Use when an operator needs a first-touch or follow-up email draft that calls confirmed recent/customer-market signals from the customer-intel Skill, with subject options, review notes, and explicit reminders not to present unconfirmed facts as facts.
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用这个 Skill 把结构化客户信息和客户背调信号转换成可人工修改后发送的英文邮件草稿。
当前定位：复核型开发信工作台
角色定位：
开发信策略员客户背调skill/ 输出的桥接结果客户背调skill/当前只覆盖两个场景：
first_touch：首轮开发信follow_up：跟进邮件它不是自动发送工具。目标是把零散输入整理成更稳定、更易复核的英文草稿。
输入统一为 JSON：
{
"email_type": "first_touch",
"customer_name": "Anna",
"company_name": "Acme Foods",
"product_or_offer": "frozen mixed vegetables",
"goal": "introduce our factory and ask whether they are open to new suppliers",
"country_or_market": "Poland",
"customer_profile_summary": "Company website shows private-label frozen food focus in EU retail.",
"previous_contact_context": "",
"tone": "professional,warm",
"sender_name": "Leo",
"sender_company": "Ningbo FreshGrow Foods",
"signature": "",
"constraints": ""
}
email_type is first_touch or follow_up.source_context comes from customer intel, require draft_authorization = approved and one approved selected_sales_angle.ANGLE-*, CL-*, and EV-* references in the review package.source_context includes recent customer signals or market signals, use them only when a dated source URL and medium/high confidence are present.evidence_signals_usedunconfirmed_fact_checklistsend_policy = manual_review_onlyDear there、Dear unknown 等占位语ANGLE-*、对应 CL-* 与 EV-* 结构化对象，不只保留文本摘要Open by...、Connect the note... 等写作指令原样复制到客户正文follow_up 必须消费真实 previous_contact_context；缺失时阻断，不得自动补写历史沟通follow_up 默认只承诺产品详情与规格；只有卖方能力、证明或授权资料明确支持样品时才能使用 sample 表达workflow_guidancesource_context客户背调skill/ 编造客户事实默认脚本入口是 build_email_draft.py。
python3 ./scripts/build_email_draft.py --input-json ./examples/first-touch.json
python3 ./scripts/run_regression_checks.py
source_contextready_for_manual_send | hold_for_manual_review是否更新到对应 Skill 以便下次自动复用。真实写入必须得到用户授权。如需数据留存、统一编排、多代理协作或飞书落地，请查看飞书文档：
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Run or resume a deliverable active-outreach workflow across lead discovery, screening, customer intel, and outreach email. Use when an operator or system pipeline needs durable run state, visible intermediate artifacts, evidence gates, report-bound human approval, and a final editable email draft that is never auto-sent.
日本語の概要は準備中です。原文の説明を表示しています。
Build bilingual, evidence-backed, SIEGER v2 customer intelligence reports for foreign-trade leads. Use when OpenClaw or a sales operator needs claim-level citations, decision gates, an industry-specific analysis lens, a non-fabricated verdict card, and sales angles that require approval before downstream outreach drafting.
日本語の概要は準備中です。原文の説明を表示しています。
OpenClaw-native SIEGER-aligned customer intelligence. Use a structured evidence bundle to produce a bilingual report with claim-level evidence, decision gates, industry-specific analysis, and proposed sales angles that require explicit approval before email drafting.
日本語の概要は準備中です。原文の説明を表示しています。
Find the first batch of foreign-trade prospect companies from public web, LinkedIn, and user-authorized data sources such as customs exports, trade show lists, association directories, CRM/Excel files, or historical customer data, then output a conservative, structured candidate list ready for lead screening.
日本語の概要は準備中です。原文の説明を表示しています。
Discover prospect companies from a structured OpenClaw search brief, including public search and user-authorized data sources, then output a conservative candidate list ready for lead screening.
日本語の概要は準備中です。原文の説明を表示しています。
Normalize and screen scattered foreign-trade leads into a conservative, structured lead pool that can flow into customer-intel research. Use when an operator has company names, websites, emails, or contact clues from search results and needs a standardized output with missing-field warnings, review flags, next-step suggestions, and customer-intel-ready JSON.
日本語の概要は準備中です。原文の説明を表示しています。