scikit-survival

Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.

1.29x

Quality

88%

Does it follow best practices?

Impact

96%

1.29x

Average score across 3 eval scenarios

Securityby

Critical

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Run	Type	Date	Status
baseline vs usage-spec With / without context 7 months ago Completed	With / without context	7 months ago	Completed

Eval run

019cb989-5aa2-72f8-9c04-cbf7796ae353

Run 7 months ago

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Repository: wu-yc/LabClaw
Path: skills/bio/scikit-survival/SKILL.md
Commit: df37802

Evaluated: 7 months ago
Agent: Claude Code
Model: Claude Sonnet 4.6

Table of Contents

Survival Model Evaluation for Post-Transplant Outcomes Biomarker Prioritization for Clinical Trial Enrollment Bone Marrow Transplant Outcome Analysis

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