A tool that rewrites weak prompts using a documented formula β then proves the lift.
A weak prompt asks for something vague: "write a marketing email". An enhanced prompt assigns a role, gives context, sets constraints, specifies output format, and shows examples. The model has less guesswork β and the output gets dramatically better.
ZeroTwo's enhancer uses Claude Sonnet 4.5 to do the rewrite, because it's the strongest instruction-following model on public benchmarks. Then both prompts run across GPT-5, Gemini, Grok, and 60+ others β so the lift is measurable, not assumed.
Five parts. Every one matters.
Assigning a specific role ("You are a senior copy editor") narrows the model's distribution of plausible outputs and improves task adherence.
Anthropic β Prompt engineering overview βAudience, goal, and prior work cut hallucination and force the model to ground its answer in what you actually need.
Brown et al. 2020 β GPT-3 in-context learning βWord counts, banned words, tone limits, and "do not" rules raise instruction-following accuracy on benchmark suites.
Wei et al. 2022 β Chain-of-thought prompting βSpecifying the output schema (JSON, markdown headings, table) makes downstream parsing reliable and cuts retry cycles.
Anthropic β XML tags + structured output βFew-shot examples lift accuracy on every major benchmark vs zero-shot, often by double digits.
Kojima et al. 2022 β Zero-shot CoT βWeak prompt β enhanced prompt β annotated output.
Write me a marketing email for our new running shoe.
You are a senior DTC copywriter writing for runners aged 25-40 who care about marathon PRs. CONTEXT: Launch email for the Stride X9 β carbon plate, 7.4oz, $230. Audience has bought from us before. CONSTRAINTS: 110-130 words. One subject line under 45 chars. No emojis. No "introducing". FORMAT: SUBJECT: ... PREHEADER: ... BODY: ... CTA: ... EXAMPLE TONE: "The plate doesn't make you faster. Less weight does."
a portrait of a woman, cinematic
Editorial portrait of a 35-year-old Korean-Canadian architect, three-quarter view, soft window light from camera-left, shallow depth of field. Shot on Hasselblad H6D, 80mm, f/2.8. Muted earth palette, film grain. --ar 4:5 --style raw --v 6.1
a beautiful mountain landscape
Wide-angle alpine valley at golden hour, jagged granite peaks, glacial lake foreground reflecting amber sky, larch trees turning gold, light fog in middle distance. Photorealistic, 35mm, ISO 100, f/11. Style of Marc Adamus. Negative: people, text, watermark, oversaturated colors, HDR.
refactor this function to be cleaner
You are a senior TypeScript engineer reviewing a teammate's PR. CONTEXT: This handler runs in a Next.js 15 app router route. Hot path β called ~4k req/min. CONSTRAINTS: Preserve public signature. No new dependencies. Add JSDoc. Explain each change in a comment. FORMAT: 1. Refactored code in one fenced block. 2. Bulleted "what changed and why" list under it. EXAMPLE STYLE: early-return guards, named constants over magic numbers, no nested ternaries.
summarize this paper
You are a research assistant briefing a busy product lead. CONTEXT: They have not read the paper and have 90 seconds. CONSTRAINTS: <=180 words. No jargon without a parenthetical definition. Quantify every claim. FORMAT: - One-sentence TL;DR. - "Method" (2 sentences). - "Result" (2 sentences with numbers). - "Why it matters for our product" (2 sentences). EXAMPLE TONE: Stratechery, not academic abstract.
The lift is measured. Not vibes.
Five years of LLM research converges on one finding: structure beats verbosity. Adding a role assignment, context, constraints, output format, and examples consistently raises benchmark accuracy β often by double-digit percentage points. The papers below are primary sources; every number on this page traces back to one of them.
"The hottest new programming language is English."
XML tags + explicit role assignment improve task adherence.
Anthropic prompt-engineering docs βZeroTwo vs the alternatives.
| Feature | PromptPerfect | ChatGPT "improve" | MJ/SD enhancer sites | ZeroTwo |
|---|---|---|---|---|
| Rewrites your prompt with a documented formula | Black-box | Ad-hoc | Token padding | 5-part formula, visible |
| Runs original AND enhanced across multiple models | No | No (one model) | No | 60+ models, side by side |
| Uses Claude (best at instruction-following) for the rewrite | Unknown | GPT only | Heuristics | Claude Sonnet 4.5 |
| Works for text, code, and image prompts | Limited | Text/code | Image only | All three |
| Price | $9.99+/mo | $20/mo | Free / ads | $19.99/mo |
Frequently asked questions.
What is a prompt enhancer?
A prompt enhancer rewrites a weak prompt into a structured, high-performing version using a documented formula: role, context, constraints, output format, and examples. The goal is measurable lift in output quality β not decoration. ZeroTwo's enhancer uses Claude (the strongest instruction-following model) to do the rewrite, then runs both versions across 60+ models so you can see the lift.
How does ZeroTwo enhance prompts?
We pass your weak prompt to Claude Sonnet 4.5 with the 5-part formula as a system prompt. Claude returns a rewritten version with explicit role, context, constraints, format, and (when useful) few-shot examples. You can then run both prompts across GPT-5, Gemini 3 Pro, Grok 4, DeepSeek R1, and any of 60+ other models in parallel β and pick the winning combination. Open the chat to try it.
Why does the 5-part formula work?
Each part attacks a different failure mode. Role narrows the output distribution. Context cuts hallucination. Constraints raise instruction-following. Format makes parsing reliable. Examples teach the pattern. Wei et al. (2022) showed structured prompts lift GSM8K accuracy from 17.9% to 56.9% β a 39 percentage-point jump. The same principle applies to copy, code, and image prompts.
Is a prompt enhancer different from "improve my prompt" in ChatGPT?
Yes. "Improve my prompt" gives you one rewrite from one model with no transparency about why it changed what it changed. A real prompt enhancer applies a documented formula, surfaces the diff, and lets you compare both versions across many models. ZeroTwo does all three.
Does it work for image prompts (Midjourney, Stable Diffusion, Flux)?
Yes. The formula maps cleanly to image prompts: role becomes camera/lens/style, context becomes scene, constraints become aspect ratio + negative prompts, format becomes Midjourney parameter syntax, and examples become artist references. Our enhancer applies the right syntax for each model β "--ar 4:5 --v 6.1" for Midjourney, structured tag order for SDXL, natural language for Flux.
Will an enhanced prompt always beat a weak one?
Almost always β but the size of the lift depends on the task. On reasoning-heavy work the lift is enormous (Kojima et al. saw MultiArith jump from 17.7% to 78.7%). On simple lookups the lift is small. ZeroTwo runs both versions in parallel so you see the actual delta on your specific task, not a vendor's marketing number.
Which model should I use for the rewrite step?
Claude Sonnet 4.5 is currently the strongest at following meta-instructions like "rewrite this prompt using the 5-part formula". GPT-5 is a close second and slightly better at structured output. Gemini 3 Pro is the most consistent on long, technical prompts. ZeroTwo defaults to Claude for the rewrite, but you can switch any time.
How much does ZeroTwo cost?
ZeroTwo is $19.99 per month for unlimited access to 60+ frontier models β Claude, GPT-5, Gemini 3 Pro, Grok 4, DeepSeek R1, Llama, image models, and more. The prompt enhancer is included. No per-model subscriptions, no usage caps on the main plan.
- 01 βA prompt enhancer rewrites weak prompts using a 5-part formula: role, context, constraints, output format, examples.
- 02 βThe lift is measurable. Wei et al. showed a 39 percentage-point jump on GSM8K reasoning from structured prompting alone.
- 03 βClaude Sonnet 4.5 is the best model to do the rewrite β strongest instruction-following on public benchmarks.
- 04 βThe formula maps cleanly to text, code, and image prompts β same five parts, different vocabulary.
- 05 βRunning both versions across 60+ models is the only honest way to confirm the lift. ZeroTwo is the only platform that bundles both steps for $19.99/mo.