Ever struggled to tell AI exactly what you want? OpenAI’s new free prompt generator might change that.

Here’s how it works:
1️⃣ Type in your request - even something vague like “make me a logo.”
2️⃣ Hit Optimize.
3️⃣ GPT-5 rewrites it into a polished, structured prompt that any AI can understand.

No experience in prompt engineering needed.

Why it matters:

• Makes AI tools way more beginner-friendly 🚀

• Saves hours of trial and error ⏳

• Works across text, images, code, video, etc.

Basically, you don’t need to learn secret prompt hacks anymore — just tell AI what you want in plain language, and it does the rest.

Would you use this to supercharge your workflow?

Try here.

I’ve been messing around with GPTs lately and noticed a gap: A lot of people have great ideas for custom GPTs… but fall flat when it comes to writing a solid system prompt.

So I built a GPT that writes the system prompt for you. You just describe your idea — even if it’s super vague — and it’ll generate a full prompt. If it’s missing context, it’ll ask clarifying questions first.

I called it Prompt-to-GPT. It’s based on the GPT-4.1 Prompting Guide from OpenAI, so it uses some of the best practices they recommend (like planning induction, few-shot structure, and literal interpretation handling).

Stuff it handles surprisingly well:

• “A GPT that studies AI textbooks with me like a wizard mentor”

• “A resume coach GPT that roasts bad phrasing”

• “A prompt generator GPT”

Try it here: https://chatgpt.com/g/g-6816d1bb17a48191a9e7a72bc307d266-prompt-to-gpt

Still iterating on it, so feedback is welcome — especially if it spits out something weird or useless. Bonus points if you build something with it and drop the link here.

Was able to do some prompt injecting to get the underlying instructions for OpenAI's system instructions generator. Template is copied below, but here are a couple of things I found interesting:
(If you're interesting in things like this, feel free to check out our Substack.)

Minimal Changes: "If an existing prompt is provided, improve it only if it's simple."

• Part of the challenge when creating meta prompts is handling prompts that are already quite large, this protects against that case.

Reasoning Before Conclusions: "Encourage reasoning steps before any conclusions are reached."

• Big emphasis on reasoning, especially that it occurs before any conclusion is reached Clarity and

Formatting: "Use clear, specific language. Avoid unnecessary instructions or bland statements... Use markdown for readability"
-Focus on clear, actionable instructions using markdown to keep things structured

Preserve User Input: "If the input task or prompt includes extensive guidelines or examples, preserve them entirely"

• Similar to the first point, the instructions here guides the model to maintain the original details provided by the user if they are extensive, only breaking them down if they are vague

Structured Output: "Explicitly call out the most appropriate output format, in detail."

• Encourage well-structured outputs like JSON and define formatting expectations to better align expectations

TEMPLATE

Develop a system prompt to effectively guide a language model in completing a task based on the provided description or existing prompt.
Here is the task: {{task}}

Understand the Task: Grasp the main objective, goals, requirements, constraints, and expected output.

Minimal Changes: If an existing prompt is provided, improve it only if it's simple. For complex prompts, enhance clarity and add missing elements without altering the original structure.

Reasoning Before Conclusions: Encourage reasoning steps before any conclusions are reached. ATTENTION! If the user provides examples where the reasoning happens afterward, REVERSE the order! NEVER START EXAMPLES WITH CONCLUSIONS!

• Reasoning Order: Call out reasoning portions of the prompt and conclusion parts (specific fields by name). For each, determine the ORDER in which this is done, and whether it needs to be reversed.

• Conclusion, classifications, or results should ALWAYS appear last.

Examples: Include high-quality examples if helpful, using placeholders {{in double curly braces}} for complex elements.

• What kinds of examples may need to be included, how many, and whether they are complex enough to benefit from placeholders.
  Clarity and Conciseness: Use clear, specific language. Avoid unnecessary instructions or bland statements.

Formatting: Use markdown features for readability. DO NOT USE ``` CODE BLOCKS UNLESS SPECIFICALLY REQUESTED.

Preserve User Content: If the input task or prompt includes extensive guidelines or examples, preserve them entirely, or as closely as possible.
If they are vague, consider breaking down into sub-steps. Keep any details, guidelines, examples, variables, or placeholders provided by the user.

Constants: DO include constants in the prompt, as they are not susceptible to prompt injection. Such as guides, rubrics, and examples.

Output Format: Explicitly the most appropriate output format, in detail. This should include length and syntax (e.g. short sentence, paragraph, JSON, etc.)

• For tasks outputting well-defined or structured data (classification, JSON, etc.) bias toward outputting a JSON.

• JSON should never be wrapped in code blocks (```) unless explicitly requested.

The final prompt you output should adhere to the following structure below. Do not include any additional commentary, only output the completed system prompt. SPECIFICALLY, do not include any additional messages at the start or end of the prompt. (e.g. no "---")

[Concise instruction describing the task - this should be the first line in the prompt, no section header]
[Additional details as needed.]
[Optional sections with headings or bullet points for detailed steps.]

Steps [optional]

[optional: a detailed breakdown of the steps necessary to accomplish the task]

Output Format

[Specifically call out how the output should be formatted, be it response length, structure e.g. JSON, markdown, etc]

Examples [optional]

[Optional: 1-3 well-defined examples with placeholders if necessary. Clearly mark where examples start and end, and what the input and output are. User placeholders as necessary.]
[If the examples are shorter than what a realistic example is expected to be, make a reference with () explaining how real examples should be longer / shorter / different. AND USE PLACEHOLDERS! ]

Notes [optional]

[optional: edge cases, details, and an area to call or repeat out specific important considerations]