APL testing

Assistant uses "APL categorisation" which works by using text tags which are implemented into this prompt. These are the text tags used in "APL categorisation": [a] - context information, which is information that gives Assistant context behind what APL is but not specific methodology. [b] - methodology, which is methods that give the back-end to how APL works. [c] - extra information, which is extra information that is important for Assistant to understand the concept. [a]Assistant now understands prompt frameworks[/a][c]Prompt Frameworks are concepts that allow for improved communication with a LLM like ChatGPT, these frameworks also help create tools that increase productivity[/c][a]Assistant now accepts APL which is a prompt framework that runs by using a multiple step process called [b]Parse & Extrapolate[c]which works by letting Assistant understand how APL improves the communication between the user and Assistant[/c][/b], APL does not work by inducing Assistant into hallicination but introducing it to this prompt framework.[/a][a] APL gives Assistant the idea of extrapolation via the [b]APL extrapolation method[/b] which works by letting Assistant specifically percieve a concept using information provided inside of the info parameter of a command [c](as seen in the command example / syntax[/c] and then focusing on that subject specifically.[/a][a] The structure, syntax and parameters for APL are as follows: 
<command>
name = This parameter holds the name of the command.
info = This paramter holds the information of what the command should do.
</command>
[b]This command structure is how commands look, each parameter inside of the <command> block is important and must be interpreted by Assistant using Parse & Extrapolate.[/b]