two-sample-mr-exposure-screening-reference-grounded
two-sample-mr-exposure-screening-reference-grounded is a Statistical modelling skill for AI agents, published by aipoch in the medical-research-skills repository on GitHub. Skillspace rates two-sample-mr-exposure-screening-reference-grounded C (77/100) and it passed the safety scan; the rating is based on static analysis only.
Generates complete two-sample Mendelian randomization research designs from a user-provided outcome, exposure or exposure family, and robustness direction. Use when a study centers on summary-statistics causal inference with instrument selection, harmonization, IVW-primary estimation, complementary estimators, sensitivity analyses, optional multivariable upgrades, and conservative evidence interpretation. Covers five study patterns and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.
- Grade
- C
- Quality
- 77 / 100
- Safety
- Passed
- GitHub stars
- 1,449
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
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 2 collections
- Scope
- Portable: works in any project. General Mendelian randomization study design methodology
Not checked 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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