/**
 * kosha-discovery — Context-management strategy advisor.
 *
 * Pure synthesis over the model + provider catalog: given where a caller is
 * in their conversation, return ranked options (continue / cache / compact /
 * switch model / long-context tier / batch offload) with rough cost math.
 *
 * No tokenization, no model inference — just arithmetic over the registry.
 * @module
 */
import type { ModelCard, ProviderCacheBehavior } from "./types.js";
export interface ContextStrategyInput {
    model: ModelCard;
    currentTokens: number;
    expectedRemainingTurns?: number;
    expectedOutputTokens?: number;
    candidateAlternatives?: ModelCard[];
}
export interface ContextSituation {
    tokensUsed: number;
    contextWindow: number;
    headroomTokens: number;
    headroomPercent: number;
    inLongContextTier: boolean;
    longContextThresholdTokens?: number;
}
export interface StrategyOption {
    strategy: "continue" | "enable_prompt_cache" | "compact_and_continue" | "switch_to_long_context_tier" | "switch_model" | "batch_offload";
    viable: boolean;
    costPerTurnUsd?: number;
    savingsPerTurnUsd?: number;
    notes: string;
    details?: Record<string, unknown>;
}
export interface ContextStrategy {
    model: {
        id: string;
        provider: string;
        contextWindow: number;
    };
    situation: ContextSituation;
    cacheBehavior?: ProviderCacheBehavior;
    options: StrategyOption[];
    recommended: StrategyOption["strategy"];
}
/** Compute ranked context-management options for the given conversation state. */
export declare function computeContextStrategy(input: ContextStrategyInput): ContextStrategy;
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