I built this after noticing how much variation there is in AI output depending on the quality of the prompt. Models matter a lot — but even the best model underperforms when the prompt is vague. Enriching the input is one of the highest-leverage things you can do.

Most prompts are drafted in 10 seconds and sent. They're missing context, constraints, a clear objective, examples. The model fills in the gaps with whatever it wants, which is why the output often feels generic or off.

Prompt Enricher scores your prompt across 5 dimensions (the YIELD framework: Your Objective, Input Context, Expectations & Constraints, Layout of Output, Demonstrations/Examples), then rewrites it with the missing pieces filled in. It also produces 4 variants — Packed, Quality, Concise, and Reliable — so you can match the enriched prompt to your use case.

The "Show Changes" diff view that highlights exactly what was added (green) and removed (red) — so it's immediately clear what enrichment actually did to your prompt.