Magic Mechanics
Apr. 25th, 2007 09:02 am![[personal profile]](https://www.dreamwidth.org/img/silk/identity/user.png){kind=small}
chuckroSo, I was musing on magic system mechanics for various roleplaying systems, and I figured I'd put this out there: Of the following, which do you prefer as a GM or as a player? Why?
1) Spells per day, typically that need to be memorized ahead and are expended when cast.
2) Spell-slot or spell-points systems, where each spell uses up a certain amount of MP or a slot that you regain when you rest. (A variation on this is spell-fatigue, where you don't get a MP limit, but casting tires your character and give you penalties to other rolls.)
3) Backlash systems (Paradox, primarily), where you have theoretically limitless magic, but risk backlash from using it/using it too much/using it in certain ways.
4) Percent-failure systems, where you again have theoretically limitless magic, but have to roll to succeed in using it and/or have a fixed percent-failure chance.
The follow-up/related question is whether you prefer free-form magic or a set spell list. And I'm not going to p[ost my opinions until I get a few responses, so as not to bias my sample.
1) Spells per day, typically that need to be memorized ahead and are expended when cast.
2) Spell-slot or spell-points systems, where each spell uses up a certain amount of MP or a slot that you regain when you rest. (A variation on this is spell-fatigue, where you don't get a MP limit, but casting tires your character and give you penalties to other rolls.)
3) Backlash systems (Paradox, primarily), where you have theoretically limitless magic, but risk backlash from using it/using it too much/using it in certain ways.
4) Percent-failure systems, where you again have theoretically limitless magic, but have to roll to succeed in using it and/or have a fixed percent-failure chance.
The follow-up/related question is whether you prefer free-form magic or a set spell list. And I'm not going to p[ost my opinions until I get a few responses, so as not to bias my sample.
