Which term specifically evaluates how good a particular action is in a given state?

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The action-value function is the term that specifically evaluates how good a particular action is in a given state. It assigns a value to each state-action pair (s, a), representing the expected return if you take action a in state s and then follow a given policy thereafter. This combines both the current situation and the chosen action to capture the long-term consequences of that choice. It differs from the reward, which is just the immediate signal you get after acting; from the state-value function, which measures how good a state is under a policy regardless of the action taken; and from the policy itself, which is the rule that selects actions rather than providing a numerical score for each action. In practice, learning the action-value function underpins methods like Q-learning, where you derive the best action in a state by picking the one with the highest estimated Q-value.