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Scored across 33 tools
Most tools target distinct actions, but several overlap: deprecated fit_clv_model and predict_customer_clv duplicate newer fit/predict tools, compare_models and select_best_model both compare fitted MMMs, and predict_probability_alive overlaps somewhat with get_churn_risk_cohorts. Descriptions do help clarify boundaries, so the set is usable but not sharply distinct.
The dominant pattern is consistent snake_case verb_noun (fit_, predict_, get_, optimize_, register_), which is easy to follow. Minor deviations exist, such as recommend_next_measurement, get_churn_risk_cohorts, and inconsistent use of the mmm suffix (fit_mmm vs get_channel_contributions), but the overall style remains predictable.
With 33 tools, this is a large surface and above the 25+ threshold that typically signals overload. The count is inflated by deprecated tools, separate synchronous/asynchronous fit paths, and many highly granular getter tools, making the set feel heavier than necessary even for a complex marketing analytics domain.
The toolset covers the main MMM lifecycle well: data registration, validation, fitting, diagnosis, cross-validation, calibration, comparison, budget optimization, plotting, and archival. CLV coverage also includes fitting, prediction, and churn risk. Minor gaps such as no generic model listing/deletion tool and no CLV-specific dataset validation are noticeable but workable.