Contract-First Bayesian Workflows for Hierarchical Behavioural Data R package gp3bayes version 0.5.0 Provides transparent, contract-first infrastructure for Bayesian analysis of repeated-measures and hierarchical behavioural data. It supports approved Bernoulli-logit, positive lognormal duration, and governed Gaussian dynamic-pupillometry workflows with strict readiness auditing, deterministic simulation, explicit preparation and transformation replay, inspectable scale-aware priors, prior and posterior predictive checks, restricted optional fitting through 'brms' with either 'rstan' or 'cmdstanr', sampling and temporal diagnostics, explicit posterior estimands, sensitivity analysis, target-specific predictive validation, simulation-based calibration, and conservative reporting. Core contracts and validation remain backend-independent. Version 0.5 adds governed robust and distributional dynamic pupillometry, bounded ARMA residual structures, Gaussian-process trajectories, explicit measurement uncertainty and missing-data models, joint binocular analysis, predictive model comparison, functional posterior estimands, and experimental nonlinear response-shape models while preserving explicit scientific and computational governance boundaries. Software Imports: withr, stats Suggests: ggplot2, SBC, bayesplot, brms, cmdstanr, detectseparation, knitr, loo, posterior, priorsense, rmarkdown, rstan, testthat (>= 3.0.0) Stefanos Balaskas <s.balaskas@ac.upatras.gr> Comprehensive R Archive Network (CRAN) Stefanos Balaskas [aut, cre, cph] (ORCID: <https://orcid.org/0000-0003-2444-9796>) MIT + file LICENSE (https://CRAN.R-project.org/package=gp3bayes/LICENSE) 2026-08-23 application/tgz https://CRAN.R-project.org/package=gp3bayes doi:10.32614/CRAN.package.gp3bayes