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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这个变体假设搜索意图和本轮可用数据源已经由 OpenClaw 工作流整理好。
Python 层只负责：
data_sources 传入。seller_context 时只做候选客户发现，不声称业务适配或采购可能性。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。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.
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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.
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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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
Normalize an OpenClaw lead bundle into a conservative lead-screening package with missing-field warnings, manual-review reasons, and customer-intel-ready payloads.
中文简介正在准备中。当前显示原文说明。