I figured I ought to comment as one of the developers...
At this moment, the README is the best guidance we can provide specifically for the use of the program, and we'd like to provide an overall guide explaining the colors and different windows that are included in the program. It’s been a part of a long TODO list for us. Unfortunately, our development of SHARPpy slowed down recently due to both school and job commitments, but we have been picking it back up.
Until we are able to produce a guide of some sort, I’d highly suggest the websites mentioned by those above me as they refer to the program (NSHARP) that we derived heavily from when we wrote SHARPpy. When we wrote the program, we worked closely with SPC and took many cues from those websites when we couldn't meet with them (e.g. with the red, blue and purple bars in the SR-winds with height panel). These websites will provide guidance for most of what you find on the SHARPpy GUI (I’ve recopied them below):
http://www.spc.noaa.gov/exper/mesoanalysis/help/begin.html
http://www.spc.noaa.gov/exper/soundings/help/index.html
https://www.wdtb.noaa.gov/buildTraining/nsharp-interactive/interactive.html
You can think of the program as a subset of tools considered to be important to analyzing, diagnosing, and forecasting the implications of different environments that support deep convection. The subset of tools included in in the program are a direct result of work and experiences of people within both the operational and research community. They will largely acknowledge that no one tool works 100% of the time. The tools are redundant in that often when one calculation or algorithm or tool lights up, others will too. All tools are based off of some calculation of the four primary ingredients: shear, instability, moisture, and lift. Not all functions of the program are explained or validated in the scientific literature (e.g. the Possible Hazard Type Box, the Storm Slinky), but most are described and tested in the literature (e.g. STP, CAPE, SARS) as tools that have some known ability to explain different environments. If you’d like to read those papers, we have a list of those references. We really recommend others to read those papers and learn those concepts. Getting to code SHARPpy and read the papers its functionality derives from gave us an insight into when certain tools may work and when they may fail. Reading the papers can give you a leg up on becoming a SHARPpy power user, I guess. Here's the list of papers many of the program's functions refer to:
http://sharppy.github.io/SHARPpy/references.html
Unfortunately, we can’t comment on CoD's implementation of the SHARPpy program on their website. They deviated significantly from our original color scheme (that we pulled from the SPC operational version of NSHARP), so I would ask them directly what their colors correspond to.