# Experiment > Measure performance or tuning changes with a baseline, controlled comparison, correctness check, and recorded verdict. Use for speed, memory, latency, size, "ทดลอง", or any claim that one approach is better. Not for correctness bugs. - Skill: `ohm41321/experiment` (Agent Skill) - Install (CLI): `npx skillmds@latest add ohm41321/experiment` - Raw SKILL.md: https://api.skillmd.com/api/skills/ohm41321/experiment/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: ohm41321 (https://skillmd.com/u/ohm41321) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/ohm41321/experiment --- # Experiment — no claim without a measurement Optimization needs numbers; null results get recorded too. ## 1. Define the metric before touching code Choose one command that prints the number: runtime, RSS, latency, size, or count. Decide **now** what improvement would count, before seeing results. If no metric command exists, build it first. ## 2. Baseline Run at least 3 times and record all values, not only the mean. Pin what you can: seed, input, cache state, and environment; state what remains uncontrolled. Correctness verify must be green before and after. ## 3. One variable per experiment Change one thing. Multiple changes make the result uninterpretable. ## 4. Measure again Use the Same command, same repetitions, same conditions. A result must beat the baseline spread; Inside the noise = **null result**. ## 5. Verdict and record Follow the repository's existing experiment log; otherwise create and append to `docs/experiments.md`: ``` ## — change: baseline: | result: verdict: WIN | NULL (inside noise) | LOSS decision: ``` Losers and nulls are reverted immediately; the log preserves the finding, not the bad diff. A null result is a finding—record it so it is not retried without new evidence. Never delete a previous entry; append a correction when later evidence overturns it. Route load-bearing nulls through `/retro`.