causal-experiments
causal-experiments is an Experimentation & statistics skill for AI agents, published by RobsonTigre in the everyday-causal-skills repository on GitHub. Skillspace rates causal-experiments D (66/100) and it passed the safety scan; the rating is based on static analysis only.
Designs and analyzes randomized experiments with power analysis, balance checks, and robust standard errors in R or Python. Use when user asks about RCT, A/B test, power analysis, randomization, or experimental design. Not for observational data.
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 53
Unproven: rated by static analysis only, not yet compared head-to-head.
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
- 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
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