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Achievement: Pull Shark

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Achievement: Pull Shark

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  1. jev-ads-analysis jev-ads-analysis Public

    把决策模型 Jev 接进亚马逊广告优化的参考实现：规则层出可追溯结论，Jev 出独立第二意见，分歧即信号。输出可落到飞书多维表格。

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  2. jev-decision-layer jev-decision-layer Public

    把决策模型（typesafe/jev-1.13，经 OpenRouter 的 decisions 端点调用）封装成业务决策工具：注册表驱动，带置信度门控与硬约束。非官方项目。

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  3. TaskGateway-Local TaskGateway-Local Public

    Universal local TaskGateway CLI and MCP server for deterministic search, planning, and fail-closed invocation rendering

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  4. amazon-ads-optimization amazon-ads-optimization Public

    可执行的亚马逊广告投放优化方法论（Agent Skill）：盈亏平衡 ACoS 口径、9 层诊断规则表、SQP 份额漏斗、6 轮理论交叉验证、零依赖 CLI。

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  5. dsh-model-order dsh-model-order Public

    Reorder the model list of any llm-pi-ai route from Settings > Models; the composer model menu follows the same order.

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