/**
 * Two-pass LLM extraction of team knowledge from conversation transcripts.
 *
 * Pass 1 (Gate check): "Does this conversation contain explicit corrections
 *   or stated preferences?" — cheap, avoids expensive extraction for irrelevant chats.
 *
 * Pass 2 (Structured extraction): Extracts category + statement + evidence_quote
 *   + confidence + scope per insight.
 *
 * Critical guard: evidence_quote must appear as a substring in the raw transcript.
 * If it doesn't, the insight is discarded (hallucination protection).
 */
import type { LLMProvider } from "../llm/provider.js";
import type { Transcript } from "./parser.js";
export type InsightCategory = "coding_rule" | "anti_pattern" | "architecture_decision" | "domain_knowledge" | "team_preference" | "gotcha";
export interface ExtractedInsight {
    category: InsightCategory;
    statement: string;
    evidence_quote: string;
    confidence: number;
    scope: "repo" | "workspace" | "global";
}
/**
 * Extracts insights from a conversation transcript using a two-pass LLM approach.
 * Returns an empty array if the gate check fails or no valid insights are found.
 */
export declare function extractInsights(transcript: Transcript, llm: LLMProvider): Promise<ExtractedInsight[]>;
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