experiment
experiment is an MLOps & model serving skill for AI agents, published by Rockielab in the rockie-claude repository on GitHub. Skillspace rates experiment C (77/100) and it passed the safety scan; the rating is based on static analysis only.
Run a materials-science / ML compute job on Rockie GPU capacity. Trigger words "run experiment", "submit job", "/experiment", or requests to quote/approve GPU spend before an experiment. Picks the right GPU type and count from a natural-language description (DFT for QE/VASP/ABINIT, MD for GROMACS/LAMMPS/OpenMM, training for PyTorch/JAX), generates the script, routes Rockie-originated submits through the embedded budget-term-sheet gate plus `runtime/submit.py`, polls status, streams logs, and surfaces the final artifacts. Use this for anything that needs a GPU — single A100 up to multi-pod B200 clusters.
- Grade
- C
- Quality
- 77 / 100
- Safety
- Passed
- GitHub stars
- 20
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
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
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