AI is everywhere now.
Developers use it to debug code. Designers use it to generate concepts. Founders use it to validate ideas. Marketers use it to write campaigns. Students use it to learn faster. Creators use it to produce images, videos, scripts, and music.
But there is still one annoying problem:
Most people are rewriting prompts from scratch every single day.**
The same debugging prompt.
The same landing page prompt.
The same SEO prompt.
The same product strategy prompt.
The same image generation prompt.
The same resume prompt.
The same study prompt.
So I built Prompt Empir — a professional, open-source AI prompt library designed to make high-quality prompts easier to discover, copy, improve, and share.
GitHub repo: https://github.com/gavuvapro/prompt-empire
Prompt Empir is a curated open-source collection of reusable prompts for major AI tools and real professional workflows.
It is built for:
The goal is simple:
Make prompt engineering practical, organized, reusable, and open-source.
Instead of keeping your best prompts scattered across Notion, Google Docs, random chats, and browser bookmarks, Prompt Empir gives them a clean home.
There are many AI prompt lists online, but most of them have the same problems:
I wanted something that feels closer to:
A prompt library should not just be a list of random phrases.
A good prompt is a reusable workflow.
It should include context, constraints, role, expected output, use cases, and example results.
That is what Prompt Empir is trying to standardize.
Prompt Empir is not only for ChatGPT.
It includes prompts for many major AI systems, including:
This makes the project useful for people working across text, code, design, image generation, video generation, and audio generation.
Prompt Empir is organized by professional use case, not just by tool.
Current categories include:
The idea is to make it easy to find prompts based on what you are trying to do.
Not just:
“Give me a ChatGPT prompt.”
But:
“Give me a prompt to review a Next.js API route for security issues.”
Or:
“Give me a prompt to create a SaaS pricing strategy.”
Or:
“Give me a prompt to generate a cinematic Runway video ad shot list.”
Each prompt is written in Markdown and follows a consistent structure:
## Description
Explain what the prompt does.
## Best AI Models
- ChatGPT
- Claude
- Gemini
## Use Cases
- Example 1
- Example 2
## Prompt
[prompt here]
## Example Output
[sample output]
This makes the repository easy to read on GitHub and easy to convert into a website.
It also makes contributions easier because everyone follows the same standard.
Here is the kind of prompt structure the project encourages:
## Description
Reviews REST or GraphQL API designs for correctness, security, scalability, and developer experience.
## Best AI Models
- ChatGPT
- Claude
- DeepSeek
- GitHub Copilot
## Use Cases
- Validate endpoint design
- Improve API documentation
## Prompt
You are a principal backend architect. Review this API design for resource modeling, authentication, authorization, validation, pagination, errors, idempotency, rate limiting, observability, and versioning.
Provide a concise scorecard and improved endpoint examples.
API draft:
{{api_draft}}
Business requirements:
{{requirements}}
## Example Output
Scorecard: Authentication 8/10, Authorization 5/10.
Recommendation: add object-level authorization checks for GET /projects/{id} and use cursor pagination for list endpoints.
Notice that this is not just “write an API prompt.”
It gives the AI a role, a task, evaluation areas, context placeholders, and a clear output expectation.
That is what makes prompts more reusable.
Prompt Empir is not only a GitHub folder.
It also includes a website built with:
The website supports:
This means the project can work both as:
Prompt quality improves when people can inspect, discuss, edit, and contribute.
Open-source makes this possible.
Anyone can:
The contribution flow is simple:
git clone https://github.com/gavuvapro/prompt-empire.git
cd prompt-empire
Then:
The project uses the MIT License, so it is friendly for learning, remixing, and professional use.
Use prompts for:
Use prompts for:
Use prompts for:
Use prompts for:
Use prompts for:
Use prompts for:
One lesson I learned while building this project:
A good prompt is not just a command. It is a structured request.
The best prompts usually include:
Bad prompt:
Write a landing page.
Better prompt:
Act as a senior conversion copywriter.
Write landing page copy for {{product}} targeting {{audience}}.
Include hero headline, subheadline, benefits, objections, social proof, FAQ, and CTA variants.
Use a clear, confident, non-hype tone.
That difference matters.
The first prompt gives you generic output.
The second prompt gives the AI a job, a user, a structure, and a quality bar.
AI tools are becoming more powerful, but many people still do not know how to communicate with them effectively.
Prompt Empir can help by giving people reusable examples they can learn from.
It can become:
The long-term vision is to make professional prompting less mysterious and more practical.
Some possible future improvements:
If you have ideas, open an issue or submit a PR.
If you like the idea, the best way to support it is simple:
GitHub repo:
https://github.com/gavuvapro/prompt-empire
AI is changing how we work, but better tools alone are not enough.
We also need better workflows.
Prompts are becoming part of how people think, build, learn, design, sell, research, and create.
So instead of keeping good prompts hidden in private chats, I think we should make them easier to share, improve, and reuse.
That is the idea behind Prompt Empir.
If this sounds useful, check it out, star the repo, and contribute a prompt:
https://github.com/gavuvapro/prompt-empire
You got an idea or insight? Leave it in the comment section.
Let’s build the most useful open-source prompt library together.