# Blog package manifest

This ZIP contains the complete source for the PyMC-Marketing 1.x prior-sweep case study.

## Publication files

- `BLOG.md`: full article source.
- `BLOG.html`: styled rendered article.
- `AGENT_PROMPT.md`: reusable Codex/Claude/Cursor prompt.
- `AGENT_PROMPT.html`: rendered prompt.
- `README.md`: repository instructions.
- `SOURCES.md`: official technical references.

## Data and outputs

- `data/sku_customer_brand_weekly.csv`: 9,360-row synthetic retail panel.
- `data/true_parameters.csv`: known synthetic truth for evaluation.
- `data/sku_master.csv`: portfolio metadata.
- `data/future_media_price_plan.csv`: future prediction scenario.
- `outputs/story/`: reproducible fixture diagnostics and real PSIS sweep outputs.

## Visuals

`figures/` contains 17 publication-ready figures covering:

- portfolio EDA;
- commercial confounding;
- true elasticity heterogeneity;
- bad traces;
- bad and repaired chain posterior overlays;
- R-hat and ESS;
- sweep methodology;
- PSIS candidate frontier;
- elasticity recovery.

## Code

`scripts/` contains the complete data generator, PyMC-Marketing 1.x model, bad/reference/fixed fit scripts, diagnostics, sweep runner, elasticity extraction, fixture generator, EDA summary, figure rendering and HTML rendering.

## Sweep package and agent skills

`pymc-marketing-sweep/` is the complete PyMC-Marketing 1.x-native sweep repository, including:

- package source;
- unit, stress and integration tests;
- `AGENTS.md`;
- `CLAUDE.md`;
- `.agents/skills/pymc-marketing-sweep/SKILL.md`.

The agent instructions are designed to adapt the workflow to custom PyMC-Marketing 1.x models by inspecting their saved model configuration, posterior variables and dimensions before editing the sweep YAML.
