pymc-bayesian-modeling SKILL.md skillA
pymc-bayesian-modeling from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jaechang-hits/sciagent-skills/pymc-bayesian-modeling@git:20260428.81ea2d2Pins git:20260428.81ea2d2 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jaechang-hits/sciagent-skills
- Path
skills/biostatistics/pymc-bayesian-modeling/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260428.81ea2d2, committed Apr 28, 2026
- First version recorded
- Feb 18, 2026
- Size
- 22,869 bytes
- Repository stars
- 381
- License
- a license file GitHub does not identify
Bayesian modeling with PyMC 5: priors, likelihood, NUTS/ADVI sampling, diagnostics (R-hat, ESS), LOO/WAIC comparison, prediction. Hierarchical, logistic, GP variants; predictive checks.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# PyMC Bayesian Modeling ## Overview PyMC is a Python library for Bayesian statistical modeling and probabilistic programming. It provides an expressive syntax for defining probabilistic models and efficient inference via MCMC (NUTS) and variational methods (ADVI). This skill covers the full Bayesian modeling cycle from model specification through diagnostics, comparison, and prediction. ## When to Use - Estimating parameters with full uncertainty quantification (credible intervals, not just point estimates) - Fitting hierarchical/multilevel models to grouped or nested data - Performing prior and posterior predictive checks to validate model assumptions - Comparing candidate models using information criteria (LOO-CV, WAIC) - Building regression models (linear, logistic, Poisson) in a Bayesian framework - Handling missing data or measurement error as latent parameters - Modeling time series with autoregressive or random walk priors - Generating posterior predictions for new observations with uncertainty bounds - Use **Stan/PyStan** instead for compiled, more scalable Bayesian inference on large models; use **statsmodels** for frequentist statistical tests ## Prerequisites …
Read the whole file at its exact version.
How to install
mdr add jaechang-hits/sciagent-skills/pymc-bayesian-modeling@sha256:c68f5cd1e438ae0aThe line at the top of this page pins the label git:20260428.81ea2d2, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_sai5hx47ih3g2alf)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 2 versions of this file, between Feb 18, 2026 and Apr 28, 2026, about one every 69 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260428.81ea2d2 latest | 2026-04-28 | 81ea2d2 | 22,869 B | A | view · diff |
| git:20260218.8df1694 | 2026-02-18 | 8df1694 | 22,968 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (22869 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
jaechang-hits/sciagent-skills · 381 stars · license a license file GitHub does not identify · pushed 2026-10-16 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_sai5hx47ih3g2alf GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/pymc-bayesian-modeling GET https://markdownregistry.com/api/v1/blob/c68f5cd1e438ae0a4b168c1b0a4a06954add6ba77fe4da964ffe1df489c62823
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.