pymc-modeling
pymc-modeling is a Statistical modelling skill for AI agents, published by pymc-labs in the python-analytics-skills repository on GitHub. Skillspace rates pymc-modeling D (58/100) and it passed the safety scan; the rating is based on static analysis only.
Load whenever the user is working on code that imports pymc, pytensor, or arviz, or asks about Bayesian modeling, MCMC, priors, posteriors, sampling, or model diagnostics. Covers PyMC 6+, PyTensor 3+, ArviZ 1.1+ (DataTree API), pymc-bart, pymc-extras, nutpie, and JAX/NumPyro backends. Use for building probabilistic models, specifying priors, running MCMC, diagnosing convergence, or comparing models. Triggers include: Bayesian inference, posterior sampling, hierarchical/multilevel models, GLMs, time series, Gaussian processes, HSGP, BART, mixture models, prior/posterior predictive checks, MCMC diagnostics, LOO-CV, model comparison, causal inference with do/observe, and any PyTensor Op or graph work.
- Grade
- D
- Quality
- 58 / 100
- Safety
- Passed
- GitHub stars
- 71
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 71 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.