experiment-design
experiment-design is a Model training & evaluation skill for AI agents, published by Yeachan-Heo in the My-Jogyo repository on GitHub. Skillspace rates experiment-design D (66/100) and it passed the safety scan; the rating is based on static analysis only.
Best practices for designing reproducible experiments
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 240
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
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Portable: works in any project. generic reproducible-experiment design methodology, no ties
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
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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