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CharleneTStrainCharleneTStrain/product-ops-skills/skills/experiment-log/SKILL.md

experiment-log

Skill0 starsChanged 17 days agoMITView on GitHub

Record product experiments and A/B tests in a consistent log — hypothesis, setup, success metric, result, and the decision made — so the team stops rerunning old tests and can see what it has learned. Use when someone is planning a test, has results to write up, asks to log an experiment, wants an experiment brief, or asks "have we tested this before?

1 other project uses a version of this.

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The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Write this before the experiment starts.

    line 18
  2. Distinctive:

    Don't set sample size or run time yourself unless asked.

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  3. Distinctive:

    When asked whether something has been tested, search the log by area and hypothesis, and answer with matching entries or say plainly that …

    line 66

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Experiment log

An experiment is only useful if someone can find it later and trust what it says. The log is the team's memory of what worked, what didn't, and why.

Before you start

If .agents/product-ops-context.md exists (or .claude/product-ops-context.md), read it first. Use the team, owners, tools, meetings, and metric definitions it already has, and only ask for what's missing or specific to this task. If it doesn't exist, go ahead with what you're given, and suggest running product-ops-context once so the next skill doesn't have to ask.

Before the test: the brief

Write this before the experiment starts. Writing the success metric after seeing results is how tests get misread.

### [Experiment name]
- **Status:** Planned
- **Owner:** [person]
- **Hypothesis:** If we [change], then [audience] will [behavior], because [reason].
- **Primary metric:** [one metric, with its definition]
- **Guardrail metrics:** [what must not get worse]
- **Audience:** [who sees it, how they're split]
- **Variants:** Control: [what]. Test: [what].
- **Success looks like:** [the specific result that would make us ship]
- **Planned run time / sample:** [as set by the owner or analyst]
- **Start date:** [date]

Rules:

  • One primary metric. If there are three, ask which one decides.
  • The hypothesis names a reason. "Let's see what happens" is not a hypothesis.
  • Don't set sample size or run time yourself unless asked; record what the owner or analyst set.

After the test: the result

- **Status:** Complete
- **End date:** [date]
- **Result:** [primary metric: control vs test, with the numbers and confidence as reported]
- **Guardrails:** [held / broke, with numbers]
- **What we learned:** [one to three sentences]
- **Decision:** Ship / Don't ship / Iterate / Inconclusive
- **Decided by:** [person]
- **Follow-up:** [next test or action, if any]

Rules:

  • Report results as given by the analysis. Never round a flat result into a win or call a result significant if the source doesn't say it is.
  • "Inconclusive" is a real outcome. Record it as one.
  • Negative results stay in the log. They're the most valuable entries for avoiding repeat tests.

The log

# Experiment log

| Name | Area | Hypothesis (short) | Result | Decision | Date | Owner |
|---|---|---|---|---|---|---|

When asked whether something has been tested, search the log by area and hypothesis, and answer with matching entries or say plainly that nothing similar is logged.

Related skills

  • product-metrics-definitions — define the success metric before the test
  • decision-log — log the decision the result led to
  • beta-program-manager — when the test runs as a beta

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