/**
 * @copyright Sister Software
 * @license AGPL-3.0
 * @author Teffen Ellis, et al.
 *
 *   `mailwoman corpus audit` — per-source slice-count vs source_weight diagnostic.
 *
 *   Reads a corpus dir's MANIFEST.json (or scans slices directly), counts slices per source,
 *   optionally loads a training config to pair the counts with the configured source_weights, and
 *   reports the estimated sampled-row distribution at training time.
 *
 *   Would have caught v0.3.0's "NAD = 411/674 train slices × 2.0 weight = ~75% of sampled mix"
 *   finding before the v0.3.0 retrospective surfaced it.
 *
 *   Emits warnings to stderr and the audit table to stdout; never throws on an empty corpus.
 */
import { type PathBuilderLike } from "path-ts";
export interface AuditOpts {
    corpusDir: PathBuilderLike;
    configPath?: string;
    /**
     * Sample at most N slices per split when counting sources. Default 100 for speed; bump to read the full set on a slow
     * run. The first row of each slice determines its source — corpus-v0.2.0+ slices are 100% source-segregated, so a
     * one-row read is authoritative.
     */
    sampleSliceCount?: number;
}
export declare function audit(opts: AuditOpts): Promise<void>;
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