/**
 * Deterministic randomness for generated fixtures. `Math.random` in a mock makes
 * a failing test unreproducible and a visual snapshot unstable; a seeded
 * generator gives varied-looking data that is identical on every run and on every
 * machine.
 */
export type SeededRng = {
    /** The next value in `[0, 1)`. */
    next: () => number;
    /**
     * An integer in `[min, max]`, both inclusive. Bounds are trusted: `max` below
     * `min` returns a value outside either, unchecked.
     */
    int: (min: number, max: number) => number;
    /** One element. Throws on an empty list. */
    pick: <T>(items: readonly T[]) => T;
    /** A shuffled copy; the input is left alone. */
    shuffle: <T>(items: readonly T[]) => T[];
    /** Rewinds to the seed. Pass this to `setupMocks({ onReset })`. */
    reset: () => void;
};
/**
 * A mulberry32 generator — 32 bits of state, a handful of integer ops, no
 * dependency. Its statistical quality is irrelevant here; reproducibility and
 * being cheap enough to call inside a request handler are the requirements.
 */
export declare function createSeededRng(seed: number): SeededRng;