Bayesian path analysis (observed-variable SEM) in PyMC. Compiles a lavaan-inspired formula DSL into a generative PyMC model, then layers introspection, identification diagnostics, the `do()` operator, and causal estimands (ATE/CATE/ATT/ATU/prob) on top. Use…
Autonomous bug-fix workflow. Guides the orchestrator through state detection, implementation, test/lint validation, and a bounded fix/review loop with an independent reviewer subagent. Use when fixing a GitHub bug report, or when the user says "fix bug",…
Author, configure, and distribute Agent Skills for a Great Docs site. Covers the three scenarios: automatic skill generation, adding a single hand-written skill, and distributing multiple named skills with a switcher page. Use when creating, editing, or…
Configure a Great Docs documentation site through great-docs.yml. Covers theming (navbar gradients, content glow, dark mode), hero sections, logos, announcements, sidebar options, page tags, page status badges, SEO, analytics, and deployment settings. Use…
Generate documentation sites for Python packages with Great Docs. Covers init, build, preview, configuration (great-docs.yml), API reference, CLI docs, user guides, theming, deployment, and the llms.txt agent-context files. Use when creating, configuring,…
Review and improve Python docstrings for Great Docs API reference generation. Covers NumPy and Google style conventions, parameter documentation, return types, examples, cross-references, and Great Docs directives (%seealso, %nodoc). Use when auditing,…
Write and maintain narrative user-guide pages for a Great Docs site. Covers page creation, QMD frontmatter, section grouping, sidebar ordering, callouts, executable code cells, cross-references, and content guidelines. Use when adding, reorganizing, or…