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Growth engine

Skill LazyIsEfficient/agentic-os/.claude/skills/growth-engine

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.From its SKILL.md

Install
npx -y skills add LazyIsEfficient/agentic-os --skill growth-engine

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 15 stars15 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
  • runs commandsInstructs the agent to run 1 command, including `scripts/pacing-alert.py`.

SKILL.md

2.5 KB, 228 tokens by cl100k_base, as published. Nobody here has run it

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

What ships with it: 8 files

64.6 KB alongside SKILL.md, 3 of them executable

references/

Keep looking

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