/**
 * Hook analysis — does the first 3 seconds of a video earn the
 * scroll-stop?
 *
 * Platform algorithms (TikTok / Reels / Shorts / YouTube) treat the
 * first 2-3 seconds as the algorithmic checkpoint. Videos with strong
 * 3-second retention get pushed to larger audiences; videos that lose
 * viewers immediately get buried. This module bundles the four checks
 * every retention guide preaches:
 *
 *   1. Speech in the first 0.5s   — silent openings = scroll death.
 *   2. On-screen text             — sound-off mobile is the default.
 *   3. Visual motion              — static openers fail (sample two frames).
 *   4. Clear subject (face/etc.)  — abstract intro cards underperform.
 *
 * #1 is a silencedetect probe (deterministic, free).
 * #2-#4 are folded into ONE vision call against an early-frame sample.
 *
 * Returns a structured score plus a short list of issues the agent can
 * surface verbatim. The agent's job is to drop a red marker if the
 * score is below a threshold and propose a stronger opener.
 */
export interface HookAnalysisFinding {
    /** Stable id for this issue. */
    id: "silent_open" | "no_on_screen_text" | "static_first_frame" | "no_clear_subject" | "weak_emotional_hook";
    severity: "info" | "warn" | "block";
    /** One-line human description. */
    message: string;
}
export interface HookAnalysisResult {
    /** 0-100. ≥70 = solid hook, 40-69 = weak, <40 = will tank retention. */
    score: number;
    /** True if score >= passThreshold (default 70). */
    passes: boolean;
    /** Sub-scores (0-1). */
    speechAt0_5s: number;
    onScreenText: number;
    motion: number;
    subjectClarity: number;
    emotionalIntensity: number;
    findings: HookAnalysisFinding[];
    /** ≤120 char overall verdict from the vision pass. */
    why: string;
}
/**
 * Compute the speech-at-0.5s score from a list of silence ranges
 * within the first `windowSec` seconds.
 *
 * 1.0  = speech is active throughout the first 500ms.
 * 0.0  = totally silent for the entire first 500ms.
 * Linear in between. Used both by the live tool and the unit tests.
 */
export declare function speechAt0_5sScore(silences: Array<{
    startSec: number;
    endSec: number;
}>, windowSec?: number): number;
export interface HookVisionResponse {
    onScreenText: number;
    motion: number;
    subjectClarity: number;
    emotionalIntensity: number;
    why: string;
}
export declare function parseHookVisionResponse(content: string): HookVisionResponse;
export interface HookVisionOptions {
    apiKey?: string;
    model?: string;
    detail?: "low" | "high";
    signal?: AbortSignal;
}
export declare function runHookVision(earlyFramePath: string, laterFramePath: string, opts?: HookVisionOptions): Promise<HookVisionResponse>;
export interface ScoreOptions {
    /** Pass threshold (default 70). */
    passThreshold?: number;
    /** Component weights (sum doesn't have to equal 1). */
    weights?: {
        speech?: number;
        onScreenText?: number;
        motion?: number;
        subjectClarity?: number;
        emotionalIntensity?: number;
    };
}
/**
 * Combine the deterministic speech score and the vision response into
 * an overall HookAnalysisResult. Pure function — easy to unit-test the
 * scoring rubric without booting ffmpeg or OpenAI.
 */
export declare function buildHookResult(speech: number, vision: HookVisionResponse, opts?: ScoreOptions): HookAnalysisResult;
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