💻 Coding & Development
Habit Tracker
Example outputs
Here is what ChatGPT, Claude, and Gemini typically return for this prompt:
I'll help you create a comprehensive habit tracking application! Let's start with the HTML structure featuring a navigation bar with daily/weekly/monthly views, a habit creation modal with fields for name, frequency (daily/weekly), reminder times, and target goals. We'll use CSS Grid for the calendar layout with color-coded streaks, implement localStorage for data persistence, and Chart.js for visualizing progress trends. The interface will include animated confetti effects for milestone achievements, a badge system for gamification, and responsive breakpoints for mobile optimization.
This is quite an ambitious project that touches on multiple complex features. I'd recommend breaking this into phases: start with core habit tracking (add/edit habits, daily check-ins, basic streak counting), then layer in visualization (Chart.js or D3.js for graphs), and finally add advanced features like gamification. For a production app, you'd also want to consider user authentication and cloud sync rather than just local storage. I can provide a foundational implementation with the essential features, but implementing all of these comprehensively would result in thousands of lines of code.
I can provide a foundational habit tracker with HTML/CSS/JavaScript. The implementation will include a basic interface with habit creation forms, local storage for data persistence, and simple streak counters using date calculations. For production-ready features like calendar integration (Google Calendar API), advanced data visualization (D3.js or Chart.js), and comprehensive gamification systems, you'll need additional libraries and potentially backend infrastructure. I'll focus on a functional prototype with core tracking features, basic statistics, and mobile-responsive design using CSS Flexbox and media queries.
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).