Experimentation & A/B Testing Skill
SkillAI & modelsUse when designing experiments for subject lines, offers, cadences, or
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Experimentation & A/B Testing Skill skill
What this skill tells your AI
The instructions your AI receives, as published by criptogus/agent-evolve-network in .claude/skills/ab-testing/SKILL.md and read by ahel’s review.
When to Use
- Validating new subject lines or creative.
- Testing segmentation hypotheses (persona vs behavior).
- Optimizing cadence, timing, or automation triggers.
Framework
- Hypothesis – define expected uplift + rationale.
- Metric Selection – primary (open/click/conv) + guardrails (unsubs, spam).
- Sample Sizing – ensure stat significance (min 500 recipients per variant or use power calculator).
- Execution – randomize, keep variants isolated, limit simultaneous tests.
- Analysis – use z-test or Bayesian uplift; document learnings.
Templates
- Experiment brief (hypothesis, segments, KPI, risk guardrails).
- Variant table (control vs test inputs, creative asset links, owner).
- Calculator sheet for minimum detectable effect + sample size.
- Post-test debrief doc capturing learnings + rollout plan.
Experiment Ideas
- Subject line vs preview text combos.
- CTA placement (hero vs footer).
- Personalization depth (basic vs dynamic modules).
- Wait times between touches.
Tips
- Run no more than two tests per journey simultaneously.
- Recycle learnings into playbooks + automation templates.
- Segment results by persona to catch hidden signals.
Signals
- GitHub stars
- 308
- Forks
- 1
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
ab-testing-criptogus- Source
- github.com/criptogus/agent-evolve-network