/**
 * Title highlight — extract table titles, apply LLM-selected keywords as {red:**keyword**}.
 *
 * Ported from feishu_tool.py cmd_highlight.
 *
 * Workflow:
 *   1. highlightExtract() → JSON batches of {code, title}
 *   2. (LLM selects keywords from batches — external step)
 *   3. highlightApply() → wrap matched keywords in {red:**keyword**}
 */
export interface TitleEntry {
    code: string;
    title: string;
}
export interface KeywordEntry {
    code: string;
    keyword: string;
}
/**
 * Extract titles from markdown tables for LLM keyword selection.
 *
 * Assumes first column is code, second column is title.
 * Returns batches of {code, title} entries.
 */
export declare function highlightExtract(mdText: string, batchSize?: number): TitleEntry[][];
/**
 * Save extraction batches to JSON files.
 * Returns the list of created file paths.
 */
export declare function saveBatches(batches: TitleEntry[][], inputPath: string): string[];
/**
 * Apply keywords from JSON back to markdown.
 * Wraps matched keywords in {red:**keyword**} within title columns.
 */
export declare function highlightApply(mdText: string, keywords: KeywordEntry[]): {
    markdown: string;
    applied: number;
};
/**
 * Auto-highlight quantitative metrics in narrative/mixed documents.
 *
 * Wraps percentages (71.2%) and multipliers (4.3×, 4.3\times) in {red:...}
 * when they appear near result-context words. Skips code fences, tables,
 * headings, and already-highlighted content.
 */
export declare function autoHighlightMetrics(md: string): {
    text: string;
    count: number;
};
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