---
name: pymc-marketing-sweep
description: Inspect a fitted PyMC-Marketing 1.x MMM, configure candidate prior grids, run PSIS importance-reweighting sweeps, assess posterior overlap and contribution distortion, generate approximate candidate predictions, and emit the exact PyMC-Marketing Prior configuration for a final validation refit. Use for prior sensitivity, sampler-remediation experiments, or deciding which prior design to refit.
---

# PyMC-Marketing 1.x prior sweep

- Read the repository `README.md` and `AGENTS.md` first. This skill targets PyMC-Marketing >=1.0.0,<2 on Python >=3.12.
- Inspect the saved MMM with `pmm-sweep inspect` before creating a grid.
- Modify YAML configuration, not engine source, for user-specific prior experiments.
- Keep only candidates with acceptable Pareto-k, reweighting ESS, and configured posterior-distortion limits.
- Rank feasible candidates by the smallest prior change first.
- Clearly label importance-reweighted summaries and future predictions as approximations.
- Emit the recommended `pymc_extras.prior.Prior(...)` configuration for one real PyMC-Marketing validation fit.
