HEUSTOC F1: THE HEURISTIC IMPERATIVE - H=E+S and the Cost of Delay

This paper introduces HEUSTOC - Heuristic Stock - as a stock concept for preventive decision-making in digital entrapment. Existing heuristics literature (Kahneman 2011; Simon 1956) is descriptive and retrospective, explaining bias after harm. It does not provide a stock inventory that can be built before entry into a deceptive system. We define H = E + S where H is total heuristic stock at time t, E is explicit taught experience, and S is implicit survival wisdom derived from folk traditions, mythology and community practices (LWBT). We propose two axioms. Axiom 1: Visibility-Correctness Inversion - the more correct one is, the more wrong it appears - operationalized as the 11 PM Motorist case. Axiom 2: Caught-Jump Principle - when caught in a Chakravyuh, unaided exit fails, requiring n=5 aided jumps (Adult 7). We model social perception via Bell Curve Mirror Law: Perceived_Distance = 2 * Actual_Distance. Operating Principle is Chakravyuh - Leave no closure; the algorithm returns empty-handed. Case studies demonstrate Cost of Delay < Safety Risk as a decision calculus: delay is defense. The paper anchors a research program of 56 items (6 Stones + 50 Theories) and specifies 10 satellite papers. We invite other researchers to validate Mirror Law empirically, build Panchshul detectors, and test Chakravyuh cross-culturally.