/**
 * log10x_find_skew — surfaces patterns where one slot value dominates
 * (sampling opportunity).
 *
 * Stage 1 implementation: accepts an `events` paste (the same shape as
 * `log10x_resolve_batch`) and runs the local 10x engine + skew detector.
 * Env-mode auto-pull (query customer TSDB for top patterns, fetch sample
 * events, run detector) is a follow-up feature in Stage 2.
 *
 * Pre-launch GA-track audit (2026-05-28): unified envelope with status,
 * threshold_basis, threshold_audit, structured errors, observation-vs-
 * floor disclosure. The math (concentration percentage) is deterministic.
 * The agent is honest about the floor being unvalidated.
 */
import { z } from 'zod';
import type { ExtractedPatterns, ExtractPatternsOptions } from '../lib/pattern-extraction.js';
import { type StructuredOutput } from '../lib/output-types.js';
/** Default minimum dominant-value fraction. Hand-picked, unvalidated. */
export declare const DEFAULT_MIN_CONCENTRATION = 0.6;
/** Default sampling rate for the savings projection. Hand-picked, unvalidated. */
export declare const DEFAULT_SAMPLE_N = 10;
/** Default minimum events per pattern to bother checking. */
export declare const DEFAULT_MIN_EVENTS = 10;
export declare const findSkewSchema: {
    events: z.ZodArray<z.ZodUnknown, "many">;
    min_concentration: z.ZodDefault<z.ZodNumber>;
    top_n: z.ZodDefault<z.ZodNumber>;
    min_events: z.ZodDefault<z.ZodNumber>;
    sample_n: z.ZodDefault<z.ZodNumber>;
};
export type FindSkewArgs = {
    events: unknown[];
    min_concentration?: number;
    top_n?: number;
    min_events?: number;
    sample_n?: number;
    /** Ignored. Retained in the signature for backward-compat with
     * in-process callers; the markdown view was removed from the public
     * schema in favor of the structured `human_summary` field. */
    view?: 'summary' | 'markdown';
};
/**
 * Top-level call status. Agent branches on this before reading anything else.
 *   - `success`: candidates evaluated, ≥1 found above the concentration floor.
 *   - `no_signal`: candidates evaluated, NONE crossed the floor. Stop searching.
 *   - `insufficient_data`: not enough events to bother analyzing OR no
 *     pattern had ≥ min_events after templating.
 *   - `error`: structural failure (engine crash, input validation failed).
 */
export type FindSkewStatus = 'success' | 'no_signal' | 'insufficient_data' | 'error';
/**
 * Engine seam (dependency injection).
 *
 * `executeFindSkew` runs the local 10x engine via `extractPatterns`, which
 * shells out to a locally-installed `tenx` binary (or local Docker).
 * That is not available deterministically in CI / offline test runs, and
 * the engine's literal-token handling makes it impossible to
 * hand-craft an event string that yields a genuine intra-pattern slot
 * with a controllable dominant percentage.
 *
 * This seam lets tests inject a synthetic `ExtractedPatterns` result so
 * the envelope + detector wrapper can be exercised without a backend.
 * Mirrors the `_setVerifyRunner` injection pattern in commitment-report.ts.
 * Production code path is unchanged: the default impl is the real
 * `extractPatterns`.
 */
type ExtractPatternsFn = (events: unknown[], opts?: ExtractPatternsOptions) => Promise<ExtractedPatterns>;
/** Test-only seam: override the engine. Pass nothing to reset. */
export declare function _setExtractPatterns(impl?: ExtractPatternsFn): void;
export declare function executeFindSkew(args: FindSkewArgs): Promise<StructuredOutput>;
export {};