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Auto Prompt Creator

Anneal loop that graduates prompts at 92%+ accuracy on cheap models.

Quick install
$ git clone https://github.com/MitchellkellerLG/auto-prompt-creator.git

What it does

A prompt optimization system that makes Haiku produce outputs indistinguishable from Opus on a defined task. Takes a baseline prompt, scores it against expert ground truth, and mutates it through a phased anneal loop — bootstrap, generalize, polish — with mutation diversity constraints that prevent overfitting. Graduates to a portable library entry when it clears 92% on held-out validation data.

How it works

Auto Prompt Creator — how it works

Features

  • Phased mutation loop (bootstrap, generalize, polish) prevents example memorization
  • Weighted rubric scoring against train/val/holdout splits
  • Auto halt on threshold, plateau, overfitting, or token budget
  • Subtractive check at iteration 8 proves generalization, not lookup
  • Graduated prompts land in `library/` with full accuracy metadata

Who it's for

  • Porting an Opus prompt down to Haiku for a 10x cost cut
  • Tuning classification, extraction, or enrichment prompts for production pipelines
  • Building a reusable prompt library with measured accuracy per task

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