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Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/paperclipai/companies --skill ab-test-analysis命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Create agent company packages conforming to the Agent Companies specification (agentcompanies/v1). Use when a user wants to create a new agent company from scratch, build a company around an existing git repo or skills collection, or scaffold a team/department of agents. Triggers on: "create a company", "make me a company", "build a company from this repo", "set up an agent company", "create a team of agents", "hire some agents", or when given a repo URL and asked to turn it into a company. Do NOT use for importing an existing company package (use the CLI import command instead) or for modifying a company that is already running in Paperclip.
Update the root README.md with entries for new or changed agent companies. Use when a new company has been added to the repo, when company details have changed (agents added/removed, skills added/removed), or when the user asks to refresh/sync the README. Triggers on: "update the readme", "add this company to the readme", "sync readme", "refresh readme", or after creating a new company with company-creator.
Analyze and prioritize a list of feature requests by theme, strategic alignment, impact, effort, and risk
基于 SOC 职业分类
正在显示 SKILL.md
| name | ab-test-analysis |
| description | Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations |
| metadata | {"sources":[{"kind":"github-file","repo":"phuryn/pm-skills","path":"pm-data-analytics/skills/ab-test-analysis/SKILL.md","commit":"36ccefdc6c2e00d7c0c12cb0a52bf93e8ec50da4","attribution":"Pawel Huryn","license":"MIT","usage":"referenced"}]} |
Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split test data, or deciding whether to ship a variant.
