Clinical study design. Select and classify endpoints, estimate sample size / power (means / proportions / survival), and score a study plan for a GO / GO-WITH-C
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请阅读 https://ai.atlankj.com/install/asset/gh-claude-skills-a7be63d91feb ,按照其中的说明把「cs-clinical-research」安装到你(当前 AI 工具)中。执行前先告诉我将运行的命令和写入的位置,等我确认。
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Run the clinical-research skill on this input:
$ARGUMENTS
endpoint_selector.py — Score candidate endpoints across clinical relevance, measurability, regulatory acceptance, sensitivity-to-change, and burden. Classify PRIMARY / KEY-SECONDARY / EXPLORATORY. Flags unvalidated surrogates (cannot be primary). Industry tuning via --profile.
sample_size_estimator.py — Closed-form power / sample size for two-arm means (Cohen's d), proportions (normal approx), or survival (Schoenfeld events). Inflates for dropout. The effect/difference/HR must trace to a published or anchor-based source.
phase_gate_scorer.py — Score the study plan 0-100 across recruitment feasibility, endpoint readiness, statistical power, operational complexity, and budget fit. Verdict + named owners (PI, Medical Monitor, Biostatistician, Regulatory Owner).
Every output is an ESTIMATE, not a protocol. A biostatistician, medical monitor, and regulatory owner sign the final design.
python3 skills/clinical-research/scripts/onboard.py (area, alpha, power, dropout, named owners) — saved config pre-configures every tool. --show lists the questions.skills/clinical-research/scripts/ar_evaluator.py (feasibility_composite, higher is better).ra-qm-team — that's the regulatory submission. This designs the study.research/grants — that finds funding. This designs the trial.product-team/experiment-designer — that's a product A/B. This is a clinical trial.