Think of the lengthy prompt as being like a safe combination, if you turn all the dials in juuust the right way, then the model's context reaches an internal state that biases it towards different outputs.

I don't know how well this specific prompt works - I don't see benchmarks - but prompting is a black art, so I wouldn't be surprised at all if it excels more than a blank slate in some specific category of tasks.

For prompts this elaborate I'm always keen on seeing proof that the author explored the simpler alternatives thoroughly, rather than guessing something complex, trying it, seeing it work and announcing it to the world.

It needs some evidence though? At least basic statistical analysis with correlation or χ2 hypotheses tests .

It is not “black art” or nothing there are plenty of tools to provide numerical analysis with high confidence intervals .