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从真实外部数据源收集商业生态系统分析所需数据，包括企业信息、关系数据、行业信息等，为后续生态系统分析提供高质量数据支持
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Based on SOC occupation classification
行动者网络理论专家分析技能，整合参与者识别、网络分析和转译过程追踪功能，提供全面的ANT分析框架
当用户需要执行行动者网络理论分析，包括参与者识别、关系网络构建、转译过程追踪和网络动态分析时使用此技能
当用户需要检验扎根理论饱和度，包括新概念识别、范畴完善度、关系充分性和理论完整性评估时使用此技能
执行布迪厄场域分析，包括场域边界识别、资本分布分析、自主性评估和习性模式分析。当需要分析社会场域的结构、权力关系和文化资本时使用此技能。
扎根理论专家分析技能，整合开放编码、轴心编码、选择式编码、备忘录撰写和理论饱和度检验功能，提供完整的扎根理论分析框架
当用户需要执行扎根理论的轴心编码，包括范畴识别、属性维度分析、关系建立和Paradigm模型构建时使用此技能
| name | business-ecosystem-data-collection |
| description | 从真实外部数据源收集商业生态系统分析所需数据，包括企业信息、关系数据、行业信息等，为后续生态系统分析提供高质量数据支持 |
| version | 1.0.0 |
| author | socienceAI.com |
| license | MIT |
| tags | ["business","ecosystem","data-collection","real-data","external-sources"] |
| compatibility | Node.js environment |
| metadata | {"domain":"business-analysis","methodology":"data-collection","complexity":"intermediate","integration_type":"analysis_tool","last_updated":"2025-12-26"} |
| allowed-tools | ["node","bash","read_file","write_file"] |
当需要执行商业生态系统数据收集时，调用 ecosystem_data_collector.py 脚本。
{
"targetIndustry": "目标行业名称",
"search_scope": {
"geographic": "地理范围",
"timeRange": "时间范围"
},
"entities": [
{
"id": "实体唯一标识",
"name": "实体名称",
"type": "实体类型",
"industry": "所属行业",
"characteristics": {}
}
],
"relationships": [
{
"source": "源实体ID",
"target": "目标实体ID",
"type": "关系类型",
"strength": "关系强度(0-1)",
"description": "关系描述"
}
],
"data_types": ["company_info", "relationships", "industry_trends"],
"collection_depth": "basic|standard|comprehensive",
"verification_required": true
}
{
"summary": {
"entities_found": "找到的实体数量",
"relationships_found": "找到的关系数量",
"data_quality_score": "数据质量分数(0-1)",
"collection_time": "收集时间"
},
"details": {
"collected_entities": [
{
"id": "实体唯一标识",
"name": "实体名称",
"type": "实体类型",
"industry": "所属行业",
"characteristics": "实体特征"
}
],
"relationships": [
{
"source": "源实体ID",
"target": "目标实体ID",
"type": "关系类型",
"strength": "关系强度(0-1)",
"description": "关系描述"
}
],
"industry_info": "行业信息",
"collection_metrics": {
"target_industry": "目标行业",
"search_scope": "搜索范围",
"data_types": "数据类型",
"collection_depth": "收集深度"
},
"data_quality_report": {
"validation_score": "验证分数",
"validation_details": "验证详情",
"verification_performed": "是否执行验证"
}
},
"metadata": {
"timestamp": "时间戳",
"version": "版本号",
"skill": "技能名称"
}
}