How can an LLM detect and correct poorly structured prompts

Question

Can you tell me How can an LLM detect and correct poorly structured prompts?

Answer 1

You can detect and correct poorly structured prompts using an LLM by combining a classification head for prompt quality assessment with a generation head for rewriting.

Here is the code snippet below:

In the above code, we are using the following key points:

• A pre-trained seq2seq model (T5) fine-tuned or prompted for grammar correction.

• A custom input format (fix prompt:) to signal instruction-specific tasks.

• Tokenization and decoding to generate structured, readable prompts.

Hence, combining prompt quality evaluation with correction using a generative model improves prompt clarity and model performance.