pymc SKILL.md skillA
pymc from k-dense-ai/scientific-agent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add k-dense-ai/scientific-agent-skills/pymc@v2.0Pins v2.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- k-dense-ai/scientific-agent-skills
- Path
skills/pymc/SKILL.md- Versions recorded
- 8
- Latest version
- v2.0, committed Oct 1, 2026
- First version recorded
- Jun 11, 2026
- Size
- 10,736 bytes
- Repository stars
- 56,497
- License
- MIT
Builds and checks Bayesian models with PyMC, including hierarchical models, NUTS MCMC, variational inference, mutable-data predictions, posterior predictive checks, diagnostics, and PSIS-LOO model comparison. Use for probabilistic modeling and uncertainty inference in PyMC.
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 ## Version and scope Targets **PyMC 6.3.2**, **PyTensor 3.3.2**, and **ArviZ 1.3.0**. These are local Python APIs, with no service endpoint, credentials, or remote inference required. The native tests use the PyMC NUTS sampler on small synthetic models. Optional nutpie/JAX samplers, SMC, and production-scale convergence are not validated by those tests. Record the complete resolved environment, backend, seeds, preprocessing, and data provenance for a scientific run. Local macOS validation used `PYTENSOR_FLAGS="cxx="` after the C linker failed with `library 'd64' not found`; this disables PyTensor C compilation for that process. The Python library workflows passed under that setting; it does not establish that the C backend works on this host. ArviZ 1 splits into base/stats/plots packages, re-exported by `import arviz as az`. PyMC returns an xarray `DataTree` despite the legacy `return_inferencedata` option name. `az.summary(..., round_to="none")` returns numerical columns; the default formats for display. Use `az.plot_ppc_dist`, `az.plot_dist`, and `az.plot_trace_dist`; save their returned `PlotCollection`, not a separate pyplot …
Read the whole file at its exact version.
How to install
mdr add k-dense-ai/scientific-agent-skills/pymc@sha256:77d29ba7adf73d82The line at the top of this page pins the label v2.0, 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_cysn27k66cz5oaky)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 8 versions of this file, between Jun 11, 2026 and Oct 1, 2026, about one every 16 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v2.0 latest | 2026-10-01 | a92663a | 10,736 B | A | view · diff |
| v1.6 | 2026-09-30 | a0aea74 | 11,967 B | A | view · diff |
| v1.5 | 2026-09-30 | ce9e6e9 | 11,967 B | A | view · diff |
| v1.4 | 2026-09-02 | 1e5eeff | 11,671 B | A | view · diff |
| v1.3 | 2026-07-28 | 4fb7e0b | 10,713 B | A | view · diff |
| v1.2 | 2026-07-26 | 2f2022d | 10,652 B | A | view · diff |
| v1.1 | 2026-07-26 | b085e11 | 17,423 B | A | view · diff |
| git:20260611.1b8fae3 | 2026-06-11 | 1b8fae3 | 17,428 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 (10736 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
k-dense-ai/scientific-agent-skills · 56,497 stars · license MIT · pushed 2026-11-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_cysn27k66cz5oaky GET https://markdownregistry.com/api/v1/resolve?ref=k-dense-ai/scientific-agent-skills/pymc GET https://markdownregistry.com/api/v1/blob/77d29ba7adf73d822329eab576d15a748811633a60bca88f5e93954793b3ea8a
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.
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