已有 confirmed task_config_path、modeling_sample_spec_path 和 feature_plan_path 后，用于训练 baseline T-Learner 模型并输出模型元数据、评估指标、打分表、uplift 分箱、分 component 特征重要性和报告。不要用于特征诊断、调参、模型比较或最终报告生成。
How to install uplift-model-t-learner-modeling?
qfin-tech/model-evo/uplift-model-t-learner-modeling
$npx -y skills add qfin-tech/model-evo --skill uplift-model-t-learner-modelingInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/qfin-tech/model-evo" --skill "qfin-tech/model-evo/uplift-model-t-learner-modeling"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/qfin-tech/model-evo" that are relevant to the current task. Run `npx skills add "https://github.com/qfin-tech/model-evo"` and select the relevant skills, then follow their instructions.
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