跳到正文
cccskills

“a-b-testing”的搜索结果

6 个 · 按相关度排序

Build A/B testing frameworks for features. TRIGGERS - Use when user needs help with a-b-testing-framework related tasks.

中文简介正在准备中。当前显示原文说明。

lionelsimai/claude-skills-collection302026年2月8日 更新

Build A/B testing frameworks for features. TRIGGERS - Use when user needs help with a-b-testing-framework related tasks.

中文简介正在准备中。当前显示原文说明。

Winbda/claude-skills-collection42026年4月6日 更新

The science of learning through controlled experimentation. A/B testing isn't about picking winners—it's about building a culture of validated learning and reducing the cost of being wrong. This skill covers experiment design, statistical rigor, feature flagging, analysis, and building experimentation into product development. The best experimenters know that every test, positive or negative, teaches something valuable. Use when "a/b test, experiment, hypothesis, statistical significance, sample size, feature flag, variant, control, treatment, p-value, conversion rate, test winner, split test, experimentation, testing, statistics, feature-flags, hypothesis, growth, optimization, learning, validation" mentioned.

中文简介正在准备中。当前显示原文说明。

omer-metin/skills-for-antigravity1692026年1月22日 更新

Feature flag lifecycle management -- safe feature toggling, gradual rollouts, A/B testing patterns, flag cleanup strategies, and technical debt prevention. Covers LaunchDarkly, Unleash, OpenFeature, and custom implementations.

中文简介正在准备中。当前显示原文说明。

oimiragieo/agent-studio422026年7月14日 更新

A/B 测试专家(验效)。专注于实验设计、样本量计算、统计显著性检验和因果推断,确保实验科学可靠。

中文简介正在准备中。当前显示原文说明。

darker2016/workbuddy-skill-groups282026年8月17日 更新

The science of learning through controlled experimentation. A/B testing isn't about picking winners—it's about building a culture of validated learning and reducing the cost of being wrong. This skill covers experiment design, statistical rigor, feature flagging, analysis, and building experimentation into product development. The best experimenters know that every test, positive or negative, teaches something valuable. Use when "a/b test, experiment, hypothesis, statistical significance, sample size, feature flag, variant, control, treatment, p-value, conversion rate, test winner, split test, experimentation, testing, statistics, feature-flags, hypothesis, growth, optimization, learning, validation" mentioned.

中文简介正在准备中。当前显示原文说明。

MikeCheng1208/BattleTree22026年7月22日 更新