statistical-reviewer
statistical-reviewer is a Medical documentation & coding skill for AI agents, published by RConsortium in the pharma-skills repository on GitHub. Skillspace rates statistical-reviewer D (64/100) and it passed the safety scan; the rating is based on static analysis only.
Simulates an independent statistical reviewer auditing a clinical trial submission package (SDTM, ADaM, TLG/TLF, SAP, CSR). Use when the user provides clinical trial datasets, tables, listings, figures, analysis outputs, or submission materials and wants an independent check of correctness, consistency, traceability, or data realism. Reviews denominators, populations, endpoints, multiplicity, safety summaries, cross-layer links from TLF to ADaM to SDTM/source, and whether data looks clinically plausible. Trigger on requests to review TLFs, audit a submission package, verify an analysis, reproduce endpoints, check SDTM/ADaM, assess data quality, or detect fabricated or unrealistic trial data across any therapeutic area.
- Grade
- D
- Quality
- 64 / 100
- Safety
- Passed
- GitHub stars
- 85
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
- 81 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- 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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