run-experiment
run-experiment is a Model training & evaluation skill for AI agents, published by isaac-sim in the IsaacLab-Arena repository on GitHub. Skillspace rates run-experiment D (61/100) and it passed the safety scan; the rating is based on static analysis only.
Runs existing Isaac Lab-Arena Experiment Definitions locally with experiment_runner.py in a ready native or Docker runtime, coordinates required local OpenPI or GR00T servers, applies local CLI overrides, and verifies generated result and report artifacts. Use for local named-Run or batch policy evaluations, variation listing, visualization or video, and result inspection. Do not use for installation or runtime preparation (setup-arena), pytest or regression checks (run-tests), interactive no-policy inspection (environment_runner.py), direct Policy Runner workflows, or OSMO preview, submission, or management.
- Grade
- D
- Quality
- 61 / 100
- Safety
- Passed
- GitHub stars
- 563
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
- 94 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- Not declared. Check the repository before reusing it.
What the scanner flagged
- over-broad allowed-tools ('*')
Not checked yet
- Category is a classifier prediction; no model has read this skill 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.