OpenClaw-native version of the foreign-trade outreach email skill. Use structured operator input plus customer-intel source context to generate conservative first-touch or follow-up email drafts without overstating inferred facts or inventing recent customer events.
The English summary is being prepared. Showing the original description.
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
这个版本面向 OpenClaw 云端工作流。
它假设操作员输入、公开资料摘要、近期客户信号和市场/合规信号已经由上游客户背调节点整理好，然后由当前脚本进行保守合并，并调用根目录里的核心草稿生成器输出统一结构的邮件包。
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。最终输入应为：
{
"operator_input": {},
"public_context": {}
}
其中：
operator_input 提供邮件场景、产品、目标、发件人等明确业务输入operator_input.seller_context；公开客户上下文不能替卖方授权public_context 提供完整五门决策、人工复核状态，以及已批准且证据绑定的 selected_sales_angle、selected_claims、selected_evidencedraft_authorization=approved 只是输入声明；脚本会重新核对五门、SIEGER 状态、风险、主体置信度和 Claim/Evidence 引用，单独一个批准字段无效operator_input 为主，不自动覆盖public_context 为辅，只做保守补充High 风险、尚未 ready 或没有批准切入角度时，终止背调桥接的草稿生成decision_gates 必须齐全且全部为 pass；产品匹配主张必须绑定至少一条强证据ANGLE-*、CL-* 和 EV-* 引用，便于人工复核follow_up 仍要求有历史沟通上下文使用 build_email_draft_from_openclaw.py。
python3 ./for-openclaw/scripts/build_email_draft_from_openclaw.py \
--input-json ./for-openclaw/examples/sample-input.json
增强权益不在仓库中展开正文。
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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.
The English summary is being prepared. Showing the original description.
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.
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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.
The English summary is being prepared. Showing the original description.
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.
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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.
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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.
The English summary is being prepared. Showing the original description.