import type { GolfScorecard, ShotRecord, ShotResult, HoleStats, ConditionRecord, SpecialPlay, TrainingSession, NutritionEntry, NineteenthHole, SprintType, AgentBreakdown, ClubSelection, HazardHit } from './types.js';
/** Runtime-friendly shot input accepted by buildScorecard, including MCP/JS aliases. */
export interface ScorecardShotInput {
    ticket_key?: string;
    /** Backward-compatible alias used by early MCP examples. */
    ticket?: string;
    title?: string;
    club: ClubSelection;
    result: ShotResult;
    hazards?: Array<HazardHit | string>;
    provisional_declared?: boolean;
    notes?: string;
}
/**
 * Compute HoleStats from a shots array.
 * Derives fairways_hit, GIR, hazards_hit, and miss_directions
 * entirely from shot data — no manual counting needed.
 *
 * - fairways_total = shots.length (every ticket is a fairway opportunity)
 * - fairways_hit = shots where result is fairway, green, or in_the_hole
 * - greens_total = shots.length
 * - greens_in_regulation = shots where result is green or in_the_hole
 * - hazards_hit = total hazards across all shots
 * - miss_directions = count of each missed_* result direction
 * - putts and penalties default to 0 (must be provided separately if needed)
 */
export declare function computeStatsFromShots(shots: ShotRecord[], overrides?: {
    putts?: number;
    penalties?: number;
}): HoleStats;
/**
 * Normalize any stats shape to a proper HoleStats object.
 * Handles the simplified format ({ fairway: true, putts: 0 }) used by
 * some scorecards, falling back to safe defaults for missing fields.
 */
export declare function normalizeStats(raw: unknown, shotCount?: number): HoleStats;
/** Minimal input for building a scorecard — everything else is computed */
export interface ScorecardInput {
    sprint_number: number;
    theme: string;
    par: 3 | 4 | 5;
    slope: number;
    date: string;
    shots: ScorecardShotInput[];
    player?: string;
    putts?: number;
    penalties?: number;
    /** Optional judged final score. Defaults to par plus recorded misses/penalties. */
    score?: number;
    type?: SprintType;
    conditions?: ConditionRecord[];
    special_plays?: SpecialPlay[];
    training?: TrainingSession[];
    nutrition?: NutritionEntry[];
    nineteenth_hole?: NineteenthHole;
    bunker_locations?: string[];
    yardage_book_updates?: string[];
    course_management_notes?: string[];
    skills_used?: string[];
    skills_created?: string[];
    skills_recommended?: string[];
    skills_skipped?: string[];
    skill_gaps_found?: string[];
    agents?: AgentBreakdown[];
    inspired_by?: string[];
}
/**
 * Build a complete GolfScorecard from minimal input.
 *
 * Auto-computes:
 * - stats (from shots array via computeStatsFromShots)
 * - score (shots.length + penalties)
 * - score_label (from computeScoreLabel)
 *
 * You only need to provide the parts requiring judgment:
 * shot results, hazard descriptions, training, nutrition, reflection.
 */
export declare function buildScorecard(input: ScorecardInput): GolfScorecard;
/** Input for building per-agent breakdowns from swarm session data */
export interface AgentShotInput {
    session_id: string;
    agent_role: string;
    shots: ShotRecord[];
}
/**
 * Build AgentBreakdown entries from per-agent shot data.
 * Each agent's score and stats are computed independently.
 */
export declare function buildAgentBreakdowns(agents: AgentShotInput[]): AgentBreakdown[];
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