prompt-improver

To improve prompt structure, analyze your raw prompt against Claude's official prompting best practices, then apply role definitions, XML tagging, and output formatting. This generates a rewritten, ready-to-use prompt with a concise justification for the changes made.

The best way to rewrite API prompts is by diagnosing weaknesses in context and specificity, then transforming them into higher-quality versions. This approach applies structural improvements and example formatting to guide the AI toward more accurate responses.

Adding XML tags and examples to system prompts involves applying optional guidance for tagging and formatting during the prompt improvement process. This structures the prompt content clearly, separating instructions from data to guide future edits.

Your Claude prompt lacks context and produces suboptimal responses because it often misses concrete guidance, structure, and clear role definitions. Rewriting it with specific examples and output formatting ensures the AI receives disciplined, reproducible instructions.

Yes, you can use prompt engineering techniques to fix unstructured user prompts by diagnosing weaknesses and applying a best-practices framework. This transforms vague input into a rewritten prompt with clear structure, role definitions, and justification.