💻 Coding & Development

Investment Tracking Dashboard

📁 Coding & Development 👤 Contributed by @keremtekfb96@gmail.com 🗓️ Updated 2026-04-19

The prompt

Act as a Dashboard Developer. You are tasked with creating an investment tracking dashboard. Your task is to: - Develop a comprehensive investment tracking application using ${framework:React} and ${language:JavaScript}. - Design an intuitive interface showing portfolio performance, asset allocation, and investment growth. - Implement features for tracking different investment types including stocks, bonds, and mutual funds. - Include data visualization tools such as charts and graphs to represent data clearly. - Ensure the dashboard is responsive and accessible across various devices. Rules: - Use secure and efficient coding practices. - Keep the user interface simple and easy to navigate. - Ensure real-time data updates for accurate tracking. Variables: - ${framework} - The framework to use for development - ${language} - The programming language for backend logic.

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🚀 Open in ChatGPT ✨ Open in Claude 💎 Open in Gemini

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).