Prompt Enhancer
Rewrite the prompt — visibly — before it runs
Instead of running a vague prompt and producing a generic answer, the system rewrites the prompt first — adding structure, scope, and constraints — and shows the rewrite as a diff. The user accepts, edits, or rejects each augmentation before the run starts. No magic prompts behind the curtain.
Framing
The problem
Vague prompts produce generic answers — but most users do not know what shape a good prompt should have.
The pattern
Rewrite the prompt as a transparent diff before running, with per-change accept/reject and a final prompt preview.
Why chat breaks here
Chat hides any prompt rewriting inside the system prompt; users cannot see what was added or chose what to keep.
Risks
Aggressive rewrites can change the meaning of the original prompt; users may rubber-stamp without reading.
Avoid when
The user is already a fluent prompter and the rewriting layer adds friction without value.
Use when
Many users are not fluent prompters and a transparent rewrite teaches them what good prompts look like.
DOPE evaluation
- Directability
- Accept, edit, or reject each suggested augmentation independently
- Observability
- The rewrite is visible as a diff over the original — nothing is added invisibly
- Predictability
- The final prompt is shown in full before any tokens are spent
- Explainability
- Each augmentation is labeled with the kind of clarity it adds (scope, format, tone, constraint)
In the wild
- Anthropic Workbench Prompt Improver (Anthropic) — Take an existing prompt → "Improve Prompt" → returns the rewritten version with chain-of-thought + clarification. Diff-style review before commit. Hero example.
- OpenAI Playground Optimize (OpenAI) — The Optimize button detects contradictions, missing format, and other weaknesses, then returns a rewritten prompt with a summary of changes. GPT-5 Prompt Optimizer extends this further.
FAQ
When should I use the Prompt Enhancer pattern?
Many users are not fluent prompters and a transparent rewrite teaches them what good prompts look like.
When should I avoid the Prompt Enhancer pattern?
The user is already a fluent prompter and the rewriting layer adds friction without value.
What problem does Prompt Enhancer solve?
Vague prompts produce generic answers — but most users do not know what shape a good prompt should have.
Why is chat the wrong fit for this?
Chat hides any prompt rewriting inside the system prompt; users cannot see what was added or chose what to keep.
Related patterns
- Alternative to: Inline Prompt Controls — Rewrite the prompt as a visible diff vs parse the prompt as inline controls. Both make implicit structure explicit.
- Often paired with: Disambiguation Branch — Enhance the prompt where it is clear; branch where it is ambiguous. Two paths off the same vague start.
- Often paired with: Sample Response — Sample shows the shape you will get; Enhancer shapes the prompt to land closer to the sample you want.