Add "code structure and style" section

Author: drbenvincent

AGENTS.md

@@ -27,3 +27,13 @@
 - **API documentation**: Auto-generated from docstrings via Sphinx autodoc, no manual API docs needed
 - **Build**: Use `make html` to build documentation
 - **Doctest**: Use `make doctest` to test that Python examples in doctests work
+
+## Code structure and style
+
+- **Experiment classes**: All experiment classes inherit from `BaseExperiment` in `causalpy/experiments/`. Must declare `supports_ols` and `supports_bayes` class attributes. Only implement abstract methods for supported model types (e.g., if only Bayesian is supported, implement `_bayesian_plot()` and `get_plot_data_bayesian()`; if only OLS is supported, implement `_ols_plot()` and `get_plot_data_ols()`)
+- **Model-agnostic design**: Experiment classes should work with both PyMC and scikit-learn models. Use `isinstance(self.model, PyMCModel)` vs `isinstance(self.model, RegressorMixin)` to dispatch to appropriate implementations
+- **Model classes**: PyMC models inherit from `PyMCModel` (extends `pm.Model`). Scikit-learn models use `RegressorMixin` and are made compatible via `create_causalpy_compatible_class()`. Common interface: `fit()`, `predict()`, `score()`, `calculate_impact()`, `print_coefficients()`
+- **Data handling**: PyMC models use `xarray.DataArray` with coords (keys like "coeffs", "obs_ind", "treated_units"). Scikit-learn models use numpy arrays. Data index should be named "obs_ind"
+- **Formulas**: Use patsy for formula parsing (via `dmatrices()`)
+- **Custom exceptions**: Use project-specific exceptions from `causalpy.custom_exceptions`: `FormulaException`, `DataException`, `BadIndexException`
+- **File organization**: Experiments in `causalpy/experiments/`, PyMC models in `causalpy/pymc_models.py`, scikit-learn models in `causalpy/skl_models.py`