occams-razorlisted

# Occam's Razor ## Overview When several explanations all fit the evidence, prefer the one that assumes the least. It is a selection heuristic, not a proof — it tells you what to bet on first, pending evidence that can tell the candidates apart. This is one of three composable motions in the deciqAI collection: [first-principles](../first-principles/SKILL.md) decomposes *downward* to irreducible bedrock; **occams-razor** chooses *sideways* among the competing accounts; [second-order-thinking](../second-order-thinking/SKILL.md) traces *forward* through time and consequence. Compose: reduce to bedrock (first-principles), pick the simplest fitting hypothesis (here), then trace where that pick leads (second-order). ## When to Use Apply when: **multiple explanations/designs/diagnoses** need ranking; a proposal keeps **accreting special cases**; someone says "simplify this," "which is more likely," "are we overcomplicating this?" **When NOT:** candidates don't equally fit the evidence (establish fit first); only one option exists; applying it would drop a known datum (over-shaving); cost of being wrong dwarfs cost of one extra assumption. ## Coaching Novices (Adaptive Front Door) Two delivery modes — pick one: **Engine mode** (user has concrete options → run full Parsimony Audit directly). **Coach mode** (user signals unfamiliarity → guide step by step). Unsure? Ask: *"Want me to run this on specific options, or walk you through the method?"* In Coach mode, respond one ste