My approach is to use words that indicate what I want like 'concise', 'brief', etc. If you know a word that precisely describes your desired type of content then use that. It's similar to art generation models, a single word brings so much contextual baggage with it. Finding the right words helps a lot. You can even ask the LLMs for assistance in finding the words to capture your intent.

As an example of contextual baggage, I wrote a tool where I had to adjust the prompt between Claude and GPT-4 because using the word "website" in the prompt caused GPT-4 (API) to go into its 'I do not have access to the internet' tirade about 30% of the time. The tool was a summary of web pages experiment. By removing 'website' and replacing it with 'content' (e.g. 'summarize the following content') GPT-4 happily complied 100% of the time.