ad-experiment-design
ad-experiment-design is an Experimentation & statistics skill for AI agents, published by RoboSafe-Lab in the ad-safety-research-skills repository on GitHub. Skillspace rates ad-experiment-design D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Design and analyze experiments for autonomous driving safety research: simulation studies, closed-course tests, naturalistic driving analysis, and benchmark evaluations. Covers CARLA, SUMO, CommonRoad, nuScenes, Waymo Open, and standard AD evaluation protocols. Use when planning experiments, choosing benchmarks, or designing test matrices for AD safety validation.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 26
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
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
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
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.