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growth-engine

Skill17 starsChanged 23 days agoMITView on GitHub

Autonomous growth experimentation framework: creates experiments with hypotheses, logs data points, runs statistical analysis (bootstrap CI + Mann-Whitney U), auto-promotes winners to a living playbook, and suggests next experiments. Use when asked to run growth experiments, analyze A/B tests, build experiment scorecards, or generate pacing alerts. For SEO-specific experiments see seo-ops; for outbound experiments see outbound-engine.

5 other projects use a version of this, 2 of them edited.

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The file

We split this skill into the rules it gives an agent

4 rules. 0 are common, 2 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 5 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Always check the playbook before creating new content — apply proven best practices first.

    line 23
  2. Very specific:

    Use batch mode (--batch-mode) for 3-10 variant tests.

    line 25
  3. Very specific:

    Run scripts/pacing-alert.py to monitor campaign health.

    line 26
  4. Distinctive:

    Do not run this engine for one-off content creation — apply playbook output directly instead.

    line 27

“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “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

Growth Engine

Autonomous growth experimentation framework based on Karpathy's autoresearch pattern applied to marketing. Creates experiments with hypotheses, logs data points, runs statistical analysis (bootstrap CI + Mann-Whitney U), auto-promotes winners to a living playbook, and suggests next experiments. Supports batch mode (up to 10 variants simultaneously).

Core Rules

  1. Always check the playbook before creating new content — apply proven best practices first.
  2. Winner threshold: p < 0.05 AND ≥ 15% lift. Winners auto-promote to the playbook.
  3. Use batch mode (--batch-mode) for 3-10 variant tests.
  4. Run scripts/pacing-alert.py to monitor campaign health; exit code 1 = alerts present.
  5. Do not run this engine for one-off content creation — apply playbook output directly instead.

References

  • references/commands.md — full CLI reference for all commands with recommended workflow
  • references/configuration.md — required and optional environment variables, pacing alert vars, dependencies

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