api-config.json 8.8 KB

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  1. {
  2. "name": "voc-proposal",
  3. "displayName": "VOC产品优化提案生成",
  4. "description": "整合所有VOC分析成果,AI生成结构化的6章节产品优化提案",
  5. "category": "synthesis",
  6. "version": "1.3.0",
  7. "type": "analysis",
  8. "parameters": {
  9. "categoryLandscape": {
  10. "type": "object",
  11. "required": true,
  12. "description": "synthesis/category-landscape 输出"
  13. },
  14. "brandProfile": {
  15. "type": "object",
  16. "required": true,
  17. "description": "synthesis/brand-profile 输出"
  18. },
  19. "competitorData": {
  20. "type": "object",
  21. "required": true,
  22. "description": "competitor-analysis 相关输出汇总"
  23. },
  24. "reviewAnalysis": {
  25. "type": "object",
  26. "required": true,
  27. "description": "review-analysis 相关输出汇总"
  28. },
  29. "socialVocData": {
  30. "type": "object",
  31. "required": false,
  32. "description": "social-voc 相关输出汇总"
  33. },
  34. "userPersona": {
  35. "type": "object",
  36. "required": true,
  37. "description": "synthesis/user-persona 输出"
  38. },
  39. "brandName": {
  40. "type": "string",
  41. "required": true,
  42. "description": "品牌名称"
  43. },
  44. "categoryKeyword": {
  45. "type": "string",
  46. "required": true,
  47. "description": "品类关键词"
  48. }
  49. },
  50. "pipeline": [
  51. {
  52. "step": 1,
  53. "name": "构建数据索引",
  54. "type": "compute",
  55. "logic": "buildDataIndex(categoryLandscape, brandProfile, competitorData, reviewAnalysis, socialVocData, userPersona)",
  56. "algorithm": {
  57. "index": "将所有上游技能输出按章节主题分类索引",
  58. "chapters": {
  59. "ch1_market": "categoryLandscape → 市场总览/CR5/价格带/搜索趋势",
  60. "ch2_competitor": "competitorData → 竞品发现/对比矩阵/定价分析/BSR追踪",
  61. "ch3_voc": "reviewAnalysis → 情感分布/痛点TOP/亮点TOP/关键词云",
  62. "ch4_social": "socialVocData → TikTok热度/IG策略/趋势话题",
  63. "ch5_user": "userPersona → 用户画像/场景分布/决策因素",
  64. "ch6_action": "综合所有数据 → 产品优化行动计划"
  65. },
  66. "completeness": "检查各数据源是否完整,缺失的标记为data_missing"
  67. },
  68. "output": "dataIndex"
  69. },
  70. {
  71. "step": 2,
  72. "name": "AI生成提案",
  73. "type": "ai",
  74. "logic": "generateProposal(dataIndex, { brandName, categoryKeyword, template: '6-chapter' })",
  75. "aiConfig": {
  76. "systemPrompt": "你是跨境电商VOC分析专家。请基于数据生成结构化的产品优化提案。只输出JSON。",
  77. "userPromptTemplate": "品牌: ${brandName}\n品类: ${categoryKeyword}\n\n请生成6章节提案:\n1. 市场总览与机会 (${ch1_data})\n2. 竞争格局与定位 (${ch2_data})\n3. VOC洞察与产品优化 (${ch3_data})\n4. 社媒趋势与营销策略 (${ch4_data})\n5. 用户画像与场景策略 (${ch5_data})\n6. 行动计划与优先级 (${all_data})",
  78. "outputFormat": "{\"chapters\":[{\"title\":\"市场总览与机会\",\"sections\":[{\"heading\":\"\",\"content\":\"\",\"dataRef\":\"\"}],\"keyFindings\":[\"\"],\"recommendations\":[\"\"]}]}",
  79. "temperature": 0.3,
  80. "maxTokens": 8000,
  81. "promptPattern": "system约束JSON输出 + user按章节注入数据摘要 + outputFormat示例引导结构"
  82. },
  83. "output": "proposal"
  84. },
  85. {
  86. "step": 3,
  87. "name": "添加数据引用+生成Markdown",
  88. "type": "compute",
  89. "logic": "addDataReferences(proposal, dataIndex)",
  90. "algorithm": {
  91. "dataRef": "为每个章节的每个结论添加数据来源引用",
  92. "markdown": "将JSON提案转化为完整Markdown文档,包含目录/执行摘要/6章节/附录",
  93. "executiveSummary": "从各章keyFindings和recommendations中提取核心要点生成执行摘要",
  94. "completenessReport": "标注数据完整度: 哪些章节有完整数据支撑,哪些基于AI推断"
  95. },
  96. "output": "finalProposal"
  97. },
  98. {
  99. "step": 4,
  100. "name": "ROI估算与风险整合",
  101. "type": "compute",
  102. "logic": "computeRoiAndRisks(proposal, dataIndex, categoryLandscape, competitorData)",
  103. "algorithm": {
  104. "roiEstimation": {
  105. "perRecommendation": "为每条建议估算: 投入成本/预期收益/回本周期",
  106. "listingOptimization": "$0成本, 预计提升转化率10-20%, 回本0天",
  107. "ppcCampaign": "日预算$30-50, ACOS目标<30%, 14天见效",
  108. "productIteration": "模具/包装改良成本估算, 60-90天回本",
  109. "socialMarketing": "KOL合作费用估算, 30-45天见效"
  110. },
  111. "riskIntegration": {
  112. "method": "从哄类格局/竞品分析中汇总风险预警",
  113. "mitigation": "每个风险配套缓解策略"
  114. }
  115. },
  116. "output": "roiAndRisks"
  117. },
  118. {
  119. "step": 5,
  120. "name": "30天行动时间线",
  121. "type": "compute",
  122. "logic": "build30DayTimeline(proposal, roiAndRisks, dataIndex)",
  123. "algorithm": {
  124. "weeklyBreakdown": {
  125. "week1": ["Listing优化(标题/五点/ST植入核心词)", "差评快速响应机制启动", "广告活动搭建(Auto+手动精准)"],
  126. "week2": ["A+页面优化", "广告Bid调优基于第一周数据", "社媒内容发布启动"],
  127. "week3": ["主图/视频迭代优化", "广告否词清理+新词扩展", "促销活动启动(Coupon/Deal)"],
  128. "week4": ["效果复盘+数据分析", "下月计划制定", "库存补货决策"]
  129. },
  130. "milestones": [
  131. { "day": 7, "target": "Listing优化完成,广告开始积累数据" },
  132. { "day": 14, "target": "广告ACOS降至目标值,有机流量开始提升" },
  133. { "day": 21, "target": "转化率提升可见,社媒引流开始起效" },
  134. { "day": 30, "target": "全面复盘,确认下一阶段重点" }
  135. ]
  136. },
  137. "output": "actionTimeline"
  138. }
  139. ],
  140. "response": {
  141. "type": "object",
  142. "properties": {
  143. "proposal": {
  144. "type": "object",
  145. "description": "完整提案结构",
  146. "properties": {
  147. "title": { "type": "string" },
  148. "date": { "type": "string" },
  149. "executiveSummary": { "type": "string" },
  150. "chapters": {
  151. "type": "array",
  152. "items": {
  153. "type": "object",
  154. "properties": {
  155. "title": { "type": "string" },
  156. "sections": { "type": "array" },
  157. "keyFindings": { "type": "array", "items": { "type": "string" } },
  158. "recommendations": { "type": "array", "items": { "type": "string" } }
  159. }
  160. }
  161. },
  162. "fullMarkdown": { "type": "string", "description": "完整Markdown文档" }
  163. }
  164. },
  165. "dataReferences": {
  166. "type": "object",
  167. "description": "数据引用和完整度",
  168. "properties": {
  169. "completeness": { "type": "number", "description": "0-100数据完整度" },
  170. "availableSources": { "type": "array", "items": { "type": "string" } },
  171. "missingSources": { "type": "array", "items": { "type": "string" } }
  172. }
  173. },
  174. "roiEstimation": {
  175. "type": "array",
  176. "description": "每条建议的ROI估算",
  177. "items": {
  178. "type": "object",
  179. "properties": {
  180. "recommendation": { "type": "string" },
  181. "investmentCost": { "type": "string" },
  182. "expectedReturn": { "type": "string" },
  183. "paybackPeriod": { "type": "string" },
  184. "priority": { "type": "string", "enum": ["high", "medium", "low"] }
  185. }
  186. }
  187. },
  188. "riskAlerts": {
  189. "type": "array",
  190. "description": "整合风险预警+缓解策略",
  191. "items": {
  192. "type": "object",
  193. "properties": {
  194. "title": { "type": "string" },
  195. "level": { "type": "string", "enum": ["high", "medium", "low"] },
  196. "description": { "type": "string" },
  197. "mitigation": { "type": "string" }
  198. }
  199. }
  200. },
  201. "actionTimeline": {
  202. "type": "object",
  203. "description": "30天行动时间线",
  204. "properties": {
  205. "weeks": {
  206. "type": "array",
  207. "items": {
  208. "type": "object",
  209. "properties": {
  210. "week": { "type": "integer" },
  211. "tasks": { "type": "array", "items": { "type": "string" } }
  212. }
  213. }
  214. },
  215. "milestones": {
  216. "type": "array",
  217. "items": {
  218. "type": "object",
  219. "properties": {
  220. "day": { "type": "integer" },
  221. "target": { "type": "string" }
  222. }
  223. }
  224. }
  225. }
  226. }
  227. }
  228. },
  229. "timeout": 300000,
  230. "retry": {
  231. "maxAttempts": 2,
  232. "delay": 3000,
  233. "backoffMultiplier": 2
  234. }
  235. }