Free AI Prompt Library - ChatGPT, Claude, Gemini

Sora Prompt for Generating JavaScript Code

Sora, developed by OpenAI, is a versatile artificial intelligence model that can be used to assist in various creative and technical tasks, including JavaScript code generation. Although Sora is primarily known for its video generation capabilities, its integration into the OpenAI ecosystem allows you to leverage its text features to produce functional code snippets. By crafting precise and structured prompts, you can obtain clean, commented, and ready-to-use JavaScript code for your web projects. Whether you need utility functions, interactive components, or complete scripts, the key lies in the quality of your prompt. A well-constructed prompt should specify the usage context, technical constraints, desired code style, and edge cases to handle. In this guide, we offer optimized prompts to get the most out of Sora for JavaScript code generation, with variants suitable for all expertise levels. Discover how to structure your requests to obtain reliable, maintainable code that meets modern web development standards.

Gemini Prompt to Create E2E Tests

End-to-end (E2E) tests are essential to guarantee an application's overall correct functioning, yet writing them is often time-consuming and repetitive. Gemini, Google's AI model, excels at generating structured code and can dramatically accelerate the creation of complete E2E test suites. By providing the technical context of your application — tech stack, critical user journeys, and the test framework used — Gemini can produce robust test scenarios covering both main flows and edge cases. Whether you use Playwright, Cypress, or Selenium, the AI adapts to your framework's conventions to generate directly usable code. The prompt engineering approach allows you to precisely specify the desired coverage level, the selector patterns to favor, and the test data management strategy. The result: maintainable, readable tests aligned with your team's best practices, produced in a fraction of the usual time.

GitHub Copilot Prompt for Creating a REST API

GitHub Copilot has become an essential assistant for developers looking to accelerate the creation of REST APIs. Thanks to its direct integration into the code editor, it understands the context of your project and generates structured code in real time. Whether you work with Node.js and Express, Python and FastAPI, or Java and Spring Boot, Copilot adapts to your tech stack to produce endpoints conforming to REST conventions. The main challenge lies in formulating the prompt: a well-structured prompt yields a complete API with data validation, error handling, authentication, and documentation. A vague prompt, on the other hand, will produce generic code requiring many adjustments. In this guide, we offer an optimized prompt that fully leverages GitHub Copilot's capabilities to generate a professional, testable, production-ready REST API. You will also discover variants adapted to your experience level as well as practical tips to get the most out of this tool on a daily basis.

Midjourney Prompt for Debugging Code

Midjourney, primarily known for artistic image generation, can play a surprisingly effective role in the code debugging process. By creating visual representations of logical flows, system architectures, or data structures, Midjourney allows developers to step back from their code and identify issues that escape purely textual reading. Visualization is a powerful cognitive tool: turning a complex algorithm into a visual diagram helps spot infinite loops, missing conditional branches, or circular dependencies. Using well-crafted prompts, you can generate conceptual diagrams of your architecture, visual metaphors for understanding data flows, or educational illustrations to document a bug and communicate it to your team. This complementary approach to traditional debugging aligns with the growing trend of visual programming and visual thinking applied to software development. Whether you're facing a stubborn bug or seeking to better understand a legacy system, Midjourney offers a unique perspective to approach your code problems from a new and creative angle.

DALL-E Prompt for Creating E2E Tests

DALL-E, OpenAI's image generation model, can play a surprising yet effective role in creating end-to-end (E2E) tests. While DALL-E doesn't directly generate test code, it excels at producing visual mockups, wireframes, and simulated screenshots that serve as visual references for your test scenarios. By generating faithful representations of expected interface states—login pages, dashboards, filled forms, error messages—you create precise visual documentation that guides the writing of your Cypress, Playwright, or Selenium tests. This visual approach allows QA teams to validate user journeys even before development is complete, identify visual edge cases, and clearly communicate acceptance criteria. The generated images become reference artifacts in your CI/CD pipeline, facilitating visual regression testing. Whether you are working on a complex web application or a mobile interface, using DALL-E to materialize the expected states of your application transforms your testing process by making it more visual, collaborative, and rigorous.

DALL-E Prompt for Code Refactoring

DALL-E, OpenAI's image generation model, may seem a surprising choice for code refactoring. Yet visualization is a powerful lever for rethinking software architecture. By generating conceptual diagrams, architecture schemas, or visual representations of data flows, DALL-E enables developers to step back from their codebase and identify refactoring patterns that escape a linear reading of the code. This visual approach is particularly effective for communicating architectural decisions to a team, documenting a complex refactoring before implementing it, or exploring different modular organizations. Rather than refactoring the code directly, DALL-E intervenes upstream: it produces clear visual representations of the current and target states, facilitating the planning and collective validation of structural changes. Combined with code tools like ChatGPT or Claude, DALL-E completes the workflow by bringing the visual dimension often missing in refactoring processes. This page guides you in creating DALL-E prompts that generate useful architectural visualizations for your refactoring projects.

Sora Prompt to Create a Chatbot

Sora, the video generation model developed by OpenAI, opens fascinating possibilities for creating visual content related to chatbots. Although Sora is primarily an AI video generation tool, it can play a key role in chatbot design by producing demonstration videos, animated tutorials, and realistic video avatars that enrich the conversational experience. By combining Sora with chatbot development platforms, you can create conversational agents with an immersive visual dimension: an animated avatar that responds to users, personalized video sequences generated in real time, or illustrated interactive guides. The approach involves using Sora to produce the visual elements that accompany and humanize your chatbot, transforming a simple textual interface into an engaging multimodal experience. Whether you are developing a customer assistant, an educational chatbot, or a virtual companion, well-crafted Sora prompts will allow you to generate coherent and professional video content that brings your chatbot to life and significantly improves user engagement.

Mistral Prompt for Creating a Prototype

Mistral, the leading French AI model, stands out as a powerful tool for accelerating prototype creation. Whether you're developing a web application, an API, or a digital product, Mistral can generate functional code, structure your architecture, and produce a testable prototype in minutes. Unlike a traditional approach where prototyping requires several days of development, using Mistral allows you to quickly validate an idea by obtaining a complete functional skeleton. The model particularly excels at generating structured code, proposing coherent architectures, and creating basic but functional user interfaces. By crafting a precise prompt that describes your product vision, key features, and technical constraints, you get a prototype that serves as a solid foundation for iteration. This approach is especially popular with startups, product managers, and independent developers looking to test a market hypothesis without investing weeks of development. Here's how to leverage Mistral to turn your idea into a concrete prototype.

Midjourney Prompt for Generating Unit Tests

Midjourney, known for its powerful AI image generation, can be creatively repurposed to support the unit test creation process. While Midjourney does not generate code directly, it excels at producing visual diagrams, architecture schemas, and graphical representations that make designing and documenting your test suites easier. By visualizing data flows, decision trees, and edge cases as clear illustrations, you can better structure your testing strategy before writing a single line of code. This visual approach is particularly useful for teams practicing TDD (Test-Driven Development) who want to map out their test scenarios intuitively. The generated diagrams also serve as excellent technical documentation assets, making test suites more understandable for new developers joining a project. Discover how to leverage Midjourney to transform your approach to unit testing through optimized prompts and advanced visualization techniques.

Perplexity Prompt for Generating Unit Tests

Perplexity stands out from other AI tools by combining real-time web search with code generation. For creating unit tests, this advantage is significant: Perplexity can identify current best practices in testing, conventions of frameworks like Jest, Pytest or JUnit, and apply them directly to your code. Unlike a classic LLM that relies solely on its training data, Perplexity checks the APIs and function signatures of the most recent test libraries, reducing errors from outdated versions. Whether you are testing a simple utility function, a service with external dependencies, or a React component with user interactions, a well-structured prompt yields tests covering nominal cases, edge cases, and error scenarios. This page provides you with optimized prompts to fully leverage Perplexity in your testing workflow, from the beginner developer discovering tests to the technical lead seeking exhaustive coverage with mocks and stubs.

DALL-E Prompt for Debugging Code

DALL-E, OpenAI's image generator, offers a unique visual approach to debugging code. Instead of getting stuck on lines of text, you can ask DALL-E to create visual representations of your software architectures, data flows, or error structures. This method is particularly useful for identifying complex logic issues, visualizing dependencies between modules, or understanding a request's path through a distributed system. By generating diagrams, flowcharts, or conceptual illustrations of your code, you activate spatial thinking that complements traditional textual analysis. Developers who adopt this approach report a better understanding of bugs related to race conditions, memory leaks, and infinite loops. DALL-E doesn't replace your debugger, but it transforms an abstract problem into a concrete image you can analyze, share with your team, and annotate. It's a visual thinking tool that integrates into your existing debugging process to accelerate the resolution of the most stubborn issues.

Stable Diffusion Prompt for Debugging Code

Stable Diffusion, known for its power in image generation, can become an unexpected ally in the code debugging process. By generating conceptual visualizations — flow diagrams, software architecture representations, error schematics, or dependency maps — this tool enables developers to better understand their code structure and visually identify failure points. Instead of reading hundreds of lines of logs, imagine producing a clear illustration of your program's execution path, highlighting bottlenecks and infinite loops. Stable Diffusion excels at creating technical visual representations when the prompt is properly structured: by specifying the desired diagram type, the programming language involved, and the nature of the bug being hunted, you obtain images that serve as powerful thinking aids. This visual approach to debugging perfectly complements traditional tools like debuggers and profilers, offering a different perspective on complex problems. Whether you're facing memory leaks, logic errors, or concurrency issues, a well-crafted prompt transforms Stable Diffusion into a formidably effective visual diagnostic tool.