NIMBLE is an R package for hierarchical Bayesian modeling that implements a domain-specific language (BUGS) for model specification and compiles models to C++ for efficient MCMC, Laplace approximation, and other inference algorithms. The architecture is a hybrid R/C++ system where R handles model parsing, compilation orchestration, and high-level algorithm construction, while generated C++ code (using embedded Eigen and CppAD libraries) performs efficient sampling and automatic differentiation. Key entry points include `nimbleModel()`, `buildMCMC()`, `runMCMC()`, and `compileNimble()`. The package provides a 'programming with models' framework allowing users to write custom inference algorithms that operate on arbitrary model structures. It bundles extensive classic BUGS benchmarks for regression testing. While the core functionality is well-maintained, the vendored Eigen and CppAD libraries and the complex compilation system introduce potential drift risks.