CLIPS/clipspy Rule Order - clips

Question

So I'm trying to self-learn CLIPS and clipspy for a class assignment and I'm a bit stuck. The code below compiles and runs just fine but the output is a bit strange. I am trying to expand on examples I found in the manual.
import clips
import logging
env = clips.Environment()
logging.basicConfig(level=10, format='%(message)s')
router = clips.LoggingRouter()
router.add_to_environment(env)
env.build("""
(defrule whodunit
(shoot ?hunter ?who)
=>
(printout t ?hunter " shot " ?who crlf)
)""")
env.build("""
(defrule animalGame
(animal ?ani)
(shoot $? ?ani)
=>
(assert (game ?ani))
)""")
env.build("""
(defrule gameAnimal
(game ?ani)
=>
(assert (animal ?ani))
)""")
env.build("""
(defrule isIllegal
(shoot ?a ?b)
(not(game ?b))
=>
(assert (criminal ?a))
)""")
env.assert_string("(animal duck)")
env.assert_string("(animal dog)")
env.assert_string("(shoot Brian duck)")
env.assert_string("(shoot Bob rhino)")
env.assert_string("(game deer)")
env.run()
for fact in env.facts():
print(fact)
This outputs:
(initial-fact)
(animal duck)
(animal dog)
(shoot Brian duck)
(shoot Bob rhino)
(game deer)
(animal deer)
(criminal Bob)
(criminal Brian)
(game duck)
It seems that Brian is labeled a criminal for shooting an animal that is not game despite the animal he is shooting being declared game in the next step. Is there anyway to re-evaluate rules to fix this contradiction?

Answer 1

I figured it out. The answer is salience. I also realized there's some logical flaws/inconsistencies declaring all animals hunted as game and charging shooting animals that are not game as criminal. Anyways:
env.build("""
(defrule animalGame
(declare (salience 100))
(animal ?ani)
(shoot $? ?ani)
=>
(assert (game ?ani))
)""")