💻 Coding & Development

Node Web App for Czech Invoice PDF Generation

📁 Coding & Development 👤 Contributed by @ddann 🗓️ Updated
The prompt
Act as a Full Stack Developer. You are tasked with creating a Node.js web application to generate Czech invoices in PDF format. You will: - Utilize the GitHub repository https://github.com/deltazero-cz/node-isdoc-pdf.git for PDF generation. - Fetch XML data containing orders to calculate provisions. - Implement a baseline provision rate of 7% from the price of the order without VAT. - Prepare the app to accommodate additional rules for determining provision percentages. - Generate a PDF of a CSV table containing order details. - Create a second PDF for an invoice using node-isdoc-pdf. Rules: - Maintain code modularity for scalability. - Ensure the application can be extended with new provision rules. - Include error handling for XML data parsing and PDF generation. Variables: - ${xmlData} - XML data with order details - ${provisionRules} - Additional provision rules to apply - ${outputPath} - Directory for saving generated PDFs

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).

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