/**
 * FSRS-6 — Free Spaced Repetition Scheduler.
 *
 * Pure math, zero dependencies. Extracted from idapixl-cortex/src/engines/memory.ts.
 *
 * FSRS-6 uses a power-law decay model to predict recall probability
 * and schedule optimal review intervals. Each memory has:
 * - stability: expected days until recall probability drops to 90%
 * - difficulty: 1-10 scale of how hard the memory is to retain
 * - state: new → learning → review → relearning lifecycle
 *
 * Rating scale: 1=Again, 2=Hard, 3=Good, 4=Easy
 */
import type { FSRSData, ScheduleResult } from '../core/types.js';
/** Default FSRS-6 weights (w[0]..w[20]) from the open-source paper. */
export declare const FSRS_WEIGHTS: readonly number[];
export declare const DESIRED_RETENTION = 0.9;
/**
 * Probability of recall after `elapsed_days` with given `stability`.
 * Decays from 1.0 toward 0 following a power curve.
 */
export declare function retrievability(stability: number, elapsed_days: number): number;
/**
 * Initial stability for a new card rated 1-4 on first review.
 */
export declare function initialStability(rating: 1 | 2 | 3 | 4): number;
/**
 * Schedule the next review for a memory given a rating.
 * Returns updated FSRS fields and the next interval in days.
 *
 * @param fsrs - Current FSRS state of the memory
 * @param rating - Review quality: 1=Again, 2=Hard, 3=Good, 4=Easy
 * @param elapsed_days - Days since last review (0 for new memories)
 */
export declare function scheduleNext(fsrs: FSRSData, rating: 1 | 2 | 3 | 4, elapsed_days?: number): ScheduleResult;
/**
 * Calculate elapsed days between a date and now.
 */
export declare function elapsedDaysSince(date: Date | null): number;
/**
 * Create fresh FSRS state for a new memory.
 */
export declare function newFSRSState(): FSRSData;
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