/**
 * Bucket interpretation helpers for log10x_pattern_examples.
 *
 * Classifies per-bucket slot distributions into a structured
 * interpretation: how many emitters, what kind, how much of the
 * slot space is pure envelope noise vs real content variation,
 * and what action the regulator should take.
 */
/**
 * Return true if the slot name comes from the k8s / infra envelope.
 *
 * Strips the ' (inferred)' suffix before matching so medium-confidence
 * inferred names (e.g. "version (inferred)") are also caught.
 *
 * Low-confidence positional slots (slot_N, slot_N_partM) are NOT envelope
 * — they are residual and classified as 'unknown' by the caller.
 */
export declare function classifySlotAsEnvelope(slotName: string): boolean;
/**
 * Infer the type of emitting entity from the set of envelope slot
 * names present in a bucket.
 *
 * Priority order mirrors k8s nesting:
 *   pod_id | pod_name → 'pod'   (most specific k8s identity)
 *   container_id alone → 'container'
 *   host | hostname → 'host'
 *   default → 'process'
 */
export declare function inferEmitterType(envelopeSlots: Set<string>): 'pod' | 'container' | 'process' | 'host';
export interface SlotDistributionEntry {
    slot: string;
    distinct_count: number;
    is_constant: boolean;
    naming_confidence: 'high' | 'medium' | 'low';
    sample_values: string[];
}
export interface BucketInterpretationInput {
    eventCount: number;
    patternEventCount: number;
    slotDistribution: SlotDistributionEntry[];
}
export interface BucketInterpretation {
    active_emitters: number;
    emitter_type: 'pod' | 'container' | 'process' | 'host';
    content_variance: 'none' | 'low' | 'high';
    envelope_share_of_named_slots: number;
    recommended_action: 'drop' | 'compact' | 'sample' | 'keep';
    rationale: string;
    human_summary: string;
}
/**
 * Derive a structured interpretation of one pattern-examples bucket.
 *
 * Steps:
 *   1. Partition slots into envelope / content / residual.
 *   2. Count varying content slots for content_variance.
 *   3. Identify active_emitters as max(distinct_count) across
 *      envelope-identity slots (container_id, pod_id, pod_name).
 *   4. Infer emitter_type from which identity slots are present.
 *   5. Compute envelope_share_of_named_slots (residual excluded).
 *   6. Apply recommended_action heuristic.
 *   7. Build rationale + human_summary strings.
 *
 * @param input.eventCount        Events in this bucket.
 * @param input.patternEventCount Total events across ALL buckets in the pattern.
 * @param input.slotDistribution  Already-built slot_distribution array from
 *                                the bucket output.
 */
export declare function computeBucketInterpretation(input: BucketInterpretationInput): BucketInterpretation;