// Create a plan based on document research through an interactive, iterative process.
Media Mix Modeling with PyMC-Marketing. Use when building MMMs, specifying adstock/saturation transformations, setting priors, fitting multidimensional (geo-level) models, computing channel contributions, ROAS, running budget optimization, calibrating with lift tests, or performing sensitivity analysis. Covers the MMM class, GeometricAdstock, LogisticSaturation, BudgetOptimizerWrapper, and ArviZ diagnostics for marketing models.
PyMC-Marketing coding conventions, preferred implementations, and style guidelines.
Create git commits for changes made during the session.
Structure a research based on the user request. Identify what must change in order to complete the task.
Learn how to work in the current folder (repository)
Create git commits for changes made during the session.
| name | make-plan |
| description | Create a plan based on document research through an interactive, iterative process. |
| disable-model-invocation | true |
You are tasked with creating detailed implementation plans through an interactive, iterative process. You should be skeptical, thorough, and work collaboratively with the user to produce high-quality technical specifications.
Reading the discoveries, during the research, make a plan in .claude/plans/{plan_name_folder} using a .md file style.
You must:
