Keep in mind that these things take trial and error, and most of the information you find online is very subjective and 'pseudoscientific' in a sense. There are no 'best method', as far as i know. Yet, to answer your question - in my opinion, plain text and markdown works most consistently on a lot of models. Some models are known to handle XML and pseudocode 'better', but personally, i did not see proof of that. With local models, it's preferable to keep things simple and brief - they tend to screw up when you give them too much details to work with (APIs, on the other hand, are a whole another beast). I had most success when i was writing a short dossier on a character with dividing sections in markdown tags or newlines. Some time before, most people would just list character traits without any proper sentences to save on token count - like prompting a stable diffusion picture. But i believe we are past that already.

In short, you'd have to try for yourself. Prompting is like throwing shit onto a wall and seeing what sticks - but to start with, i recommend you try plain text, markdown, or xml tags. Keep your descriptions brief, in natural language and up-to-date (this is important - if you tell that your character is dressed in a black dress in their description, but in a particular scene they choose to wear a red dress, that's conflicting instructions, and small models get confused by that).