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    "summary_en": "Sample-size and statistical power calculations for planning studies. Use whenever someone asks \"how many subjects/samples/replicates do I need\", wants an a priori power analysis, a minimum detectable effect (MDE), a power curve, or needs to justify a sample size for a grant, IRB protocol, or pre-registration. Covers closed-form power for t-tests, ANOVA, proportions, correlations, chi-square, and regression, plus simulation-based (Monte Carlo) power for designs with no formula — logistic/Poisson regression, mixed models, cluster-randomized trials, survival, and interactions. Use this skill even when the request only mentions an effect size, alpha, or \"80% power\" without saying \"power analysis\" explicitly. For laying out the study (randomization, blocking, factorial/DOE, crossover, sequential designs) use experimental-design; for analyzing data already collected and reporting it use statistical-analysis.",
    "summary_zh": "用于规划研究的样本量和统计功效计算。当有人问“我需要多少受试者/样本/重复”时，希望进行先验功效分析、最小可检测效应（MDE）、功效曲线，或需要为基金申请、IRB方案或预注册证明样本量合理性时使用。涵盖t检验、方差分析、比例、相关、卡方和回归的闭式功效，以及针对无公式设计的基于模拟（蒙特卡洛）的功效——逻辑/泊松回归、混合模型、整群随机试验、生存分析和交互作用。即使请求仅提及效应量、α或“80%功效”而未明确说“功效分析”，也应使用此技能。对于研究布局（随机化、区组、因子/DOE、交叉、序贯设计），请使用experimental-design；对于分析已收集数据并报告，请使用statistical-analysis。",
    "description_en": "A skill for sample-size and statistical power calculations used in study planning. It supports a priori power analysis, minimum detectable effect (MDE), power curves, and sample size justification for grants, IRB protocols, or pre-registration. It covers closed-form power for common tests (t-tests, ANOVA, proportions, correlations, chi-square, regression) and simulation-based (Monte Carlo) power for designs without formulas (logistic/Poisson regression, mixed models, cluster-randomized trials, survival, interactions). The skill includes guidance on effect size selection, sensitivity analysis, adjustments for multiple comparisons, attrition, and clustering, and provides reporting templates. It is intended for use before data collection; for study design layout use experimental-design, and for analyzing collected data use statistical-analysis.",
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