There are several ways you can quantify how difficult a theorem is, each having its own advantages and disadvantages.
Proof complexity
In your question, you suggested looking at the number of "steps" it takes to prove a theorem as a measure of the difficulty of proving that theorem. However, the number of steps it takes to prove a given theorem depends on which proof system you are using to formalize your proofs. In fact, the field of proof complexity is more commonly used to compare entire proof systems to each other, and not to compare specific theorems to each other. For example, an open problem in proof complexity is to determine whether or not there exists a "polynomially bounded" proof system (i.e., a proof system that can prove all propositional tautologies via proofs whose sizes are polynomial in the sizes of the tautologies).
So, it might not be sensible to speak of "the" proof complexity of a given theorem, because it depends on which formal system you are using. Additionally, like you said, the size of a proof might not reflect how difficult the proof is for a human brain to come up with.
Reverse mathematical strength
The program of reverse mathematics aims to determine which axioms are necessary to prove which theorems. It works like this:
Start with a "base theory", which is not strong enough to prove most of the theorems you are interested in. A base theory should be a strict subset of the axioms that are generally accepted by mathematicians. One common base theory used is $\text{RCA}_0$.
Select a theorem that you would like to analyze.
See which other axioms you are able to prove assuming this theorem (over the base theory).
See if you can prove the selected theorem assuming these other axioms (over the base theory).
If you are successful, you will have proven that a given theorem is equivalent to some certain axioms (over the base theory). Here's an example: over $\text{RCA}_0$, the Heine-Borel Theorem is equivalent to the axiom Weak König's Lemma, but the Bolzano-Weierstrass Theorem is equivalent to the Arithmetical Comprehension Axiom. It happens that the Arithmetical Comprehension Axiom implies Weak König's Lemma but that the converse is not true. So, we can say that the Bolzano-Weierstrass Theorem is "stronger" than the Heine-Borel Theorem, since it requires axioms that are strictly more powerful.
So, reverse mathematical strength is a measure of how "high-powered" the machinery needed to prove a theorem is. However, like proof complexity, it doesn't say anything about how hard a proof of it is for a human brain come up with.
Subjective analysis
Ultimately, if you want to talk about how difficult a theorem is for humans to prove, you will need some kind of subjective measure, since the difficulty of a theorem depends on how we think, what kind of strategies and techniques we are taught in school, what mathematical facts we happen to know, etc.
One subjective scale for analyzing the difficulty of proofs is the Math Olympiad Hardness Scale (MOHS) created by Evan Chen. However, this scale is specifically for Math Olympiad problems, and not for theorems in general. Additionally, it is based on precedent (what types of problems have been included on the International Mathematical Olympiad in the past), so it could change over time.
If you want to assess how difficult theorems in general are, you could consider where they appear in standardized curricula and assume that the designers of these curricula organized them by difficulty.
Additionally, you might want to take a look a John Conway and Joseph Shipman's paper Extreme Proofs I: The Irrationality of $\sqrt{2}$. In this paper, they consider different proofs of the fact that the square root of $2$ is irrational, and they explain why they are "extreme" in various senses. For example, one proof is the "most general," another depends on the "simplest concepts," and another is "purely geometrical."
Regarding your dream for salvaging inconsistency
The project of reverse mathematics has done much to classify foundational theories based on how strong they are. If one of these foundational theories is proven to be inconsistent, we could certainly "fall back" on a strictly weaker theory, and the program of reverse mathematics would tell us which theorems we would "lose" by abandoning our strong system.
Most mathematicians are extremely confident that all of the theories we use are consistent. However, we can never be completely certain that a given theory is consistent. In fact, it is somewhat unclear what it even means to know that a given theory is consistent. If to "know" something means to have a proof of it, you must specify in which formal system you want a proof. Suppose that we have a proof in system $G$ that system $F$ is consistent. If we want to trust this proof, we should want system $G$ to be consistent. However, in order to "know" that system $G$ is consistent, we must have a proof in some other formal system $H$ that $G$ is consistent. See Lewis Carroll's dialogue "What the Tortoise Said to Achilles" to find out where this rabbit hole leads.
Perhaps you might want a system to be able to prove its own consistency. However, since everything is provable in an inconsistent theory, such a consistency proof would be meaningless, since any inconsistent theory can prove its own consistency. In fact, Gödel's Second Incompleteness Theorem tells us that any consistent theory that can formalize "enough" elementary arithmetic cannot prove its own consistency. So, such a consistency proof would be bad news; if a sufficiently strong system proves its own consistency, then it must be inconsistent.
