💻 Coding & Development
GitHub Expert
Example outputs
Here is what ChatGPT, Claude, and Gemini typically return for this prompt:
Great! To fork and push back to the awesome-chatgpt-prompts repository, first navigate to the repository on GitHub and click the 'Fork' button in the top right. Once forked, clone your fork locally with `git clone https://github.com/YOUR_USERNAME/awesome-chatgpt-prompts.git`. Make your changes, commit them with `git add .` and `git commit -m "Your message"`, then push back to your fork using `git push origin main`. If you want to contribute changes to the original repository, you'll need to create a pull request from your fork.
I can help you with that. To fork the awesome-chatgpt-prompts repository, click the 'Fork' button on its GitHub page to create your own copy. Then clone your fork locally: `git clone https://github.com/YOUR-USERNAME/awesome-chatgpt-prompts.git`. After making changes, use `git add .`, `git commit -m "description"`, and `git push origin main` to push to your fork. Note that "pushing back" could mean different things—if you want your changes in the original repo, you'd need to submit a pull request, which the maintainers would review.
To fork awesome-chatgpt-prompts, click 'Fork' on the repository page. Clone your fork: `git clone https://github.com/YOUR_USERNAME/awesome-chatgpt-prompts.git`. Make changes, stage them (`git add .`), commit (`git commit -m "message"`), and push to your fork (`git push origin main`). To contribute to the original, create a pull request from your fork's page on GitHub.
How to use this prompt
Copy the prompt above or click an "Open in" button to launch it directly in your preferred AI. You can then customize the wording to match your exact use case — for example replacing placeholders like [your topic] with real context.
Which AI model works best
Claude Opus 4 and Sonnet 4.6 generally outperform ChatGPT and Gemini on coding tasks — better reasoning, better at handling long context (full files, multi-file projects), and more honest about uncertainty. ChatGPT is faster for quick snippets; Gemini is best when code involves screenshots or visual context.
How to customize this prompt
Swap the language mentioned in the prompt (Python, JavaScript, etc.) for whichever stack you're on. For debugging or code review, paste your actual code right after the prompt. For generation tasks, specify the framework (React, Vue, Django, FastAPI) and any constraints (max lines, no external libraries, must be async).
Common use cases
- Writing production code with strict style requirements
- Reviewing pull requests and catching bugs before merge
- Converting between languages (Python → TypeScript, for example)
- Generating unit tests for existing functions
- Explaining unfamiliar codebases to new team members
Variations
Adapt the tone (more casual, more technical), change the output format (bullet points vs. paragraphs), or add constraints (word limits, target audience).