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Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations
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
Generate an Ansoff Matrix analysis mapping growth strategies across market penetration, market development, product development, and diversification
Identify the first beachhead market segment for a product launch. Evaluates segments against burning pain, willingness to pay, winnable market share, and referral potential
Design experiments to test assumptions for an existing product — prototypes, A/B tests, spikes, and other low-effort validation methods
| 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.
