experiment-designer
Use when planning product experiments, writing testable hypotheses, estimating sample size, prioritizing tests, or interpreting A/B outcomes with practical statistical rigor.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/alirezarezvani/claude-skills --skill experiment-designer- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads experiment-designer automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Experiment Designer
Design, prioritize, and evaluate product experiments with clear hypotheses and defensible decisions.
When To Use
Use this skill for:
- A/B and multivariate experiment planning
- Hypothesis writing and success criteria definition
- Sample size and minimum detectable effect planning
- Experiment prioritization with ICE scoring
- Reading statistical output for product decisions
Core Workflow
- Write hypothesis in If/Then/Because format
- If we change
[intervention] - Then
[metric]will change by[expected direction/magnitude] - Because
[behavioral mechanism]
- Define metrics before running test
- Primary metric: single decision metric
- Guardrail metrics: quality/risk protection
- Secondary metrics: diagnostics only
- Estimate sample size
- Baseline conversion or baseline mean
- Minimum detectable effect (MDE)
- Significance level (alpha) and power
Use:
python3 scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --mde-type absolute
- Prioritize experiments with ICE
- Impact: potential upside
- Confidence: evidence quality
- Ease: cost/speed/complexity
ICE Score = (Impact * Confidence * Ease) / 10
- Launch with stopping rules
- Decide fixed sample size or fixed duration in advance
- Avoid repeated peeking without proper method
- Monitor guardrails continuously
- Interpret results
- Statistical significance is not business significance
- Compare point estimate + confidence interval to decision threshold
- Investigate novelty effects and segment heterogeneity
Hypothesis Quality Checklist
- Contains explicit intervention and audience
- Specifies measurable metric change
- States plausible causal reason
- Includes expected minimum effect
- Defines failure condition
Common Experiment Pitfalls
- Underpowered tests leading to false negatives
- Running too many simultaneous changes without isolation
- Changing targeting or implementation mid-test
- Stopping early on random spikes
- Ignoring sample ratio mismatch and instrumentation drift
- Declaring success from p-value without effect-size context
Statistical Interpretation Guardrails
- p-value < alpha indicates evidence against null, not guaranteed truth.
- Confidence interval crossing zero/no-effect means uncertain directional claim.
- Wide intervals imply low precision even when significant.
- Use practical significance thresholds tied to business impact.
See:
references/experiment-playbook.mdreferences/statistics-reference.md
Tooling
scripts/sample_size_calculator.py
Computes required sample size (per variant and total) from:
- baseline rate
- MDE (absolute or relative)
- significance level (alpha)
- statistical power
Example:
python3 scripts/sample_size_calculator.py \
--baseline-rate 0.10 \
--mde 0.015 \
--mde-type absolute \
--alpha 0.05 \
--power 0.8
FAQ
What does the experiment-designer skill do?
Use when planning product experiments, writing testable hypotheses, estimating sample size, prioritizing tests, or interpreting A/B outcomes with practical statistical rigor.
How do I install experiment-designer?
Run npx skills add https://github.com/alirezarezvani/claude-skills --skill experiment-designer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/experiment-designer/ (personal) or .claude/skills/experiment-designer/ (project).
Which AI agents can use experiment-designer?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is experiment-designer safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains experiment-designer?
It is published by alirezarezvani in alirezarezvani/claude-skills. It has 609 recorded installs.
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