/**
 * optimize_portfolio Tool
 *
 * Portfolio optimization with rebalancing recommendations using rate-limited vault queries.
 * Analyzes current holdings and provides optimal allocation strategy based on
 * per-vault historical data (price history and performance metrics).
 *
 * Implementation:
 * - Executes rate-limited parallel GraphQL queries (one per vault) using rateLimitedMap
 * - Max 2 concurrent requests to prevent 429 rate limit errors
 * - Each vault gets up to 1000 transactions of historical data
 * - Processes per-vault price history for accurate volatility calculation
 * - Uses per-vault performance data for expected APR estimation
 *
 * Use cases:
 * - Portfolio rebalancing and optimization
 * - Risk-adjusted allocation strategies (equal_weight, risk_parity, max_sharpe, min_variance)
 * - Diversification improvement
 * - Performance enhancement through optimal weighting
 * - Performance: ~800-1200 tokens per optimization (scales with vault count)
 *
 * Cache strategy:
 * - 30-minute TTL (balances freshness with stability)
 * - Cache key: portfolio_optimization:{chainId}:{vaultAddresses}:{strategy}
 * - Cache hit rate target: 70-80%
 * - Cache tags: [CacheTag.PORTFOLIO, CacheTag.ANALYTICS] for invalidation
 */
import { CallToolResult } from '@modelcontextprotocol/sdk/types.js';
import { OptimizePortfolioInput } from '../utils/validators.js';
import { ServiceContainer } from '../core/container.js';
/**
 * Create the executeOptimizePortfolio function with DI container
 *
 * @param container - Service container with dependencies
 * @returns Configured tool executor function
 */
export declare function createExecuteOptimizePortfolio(container: ServiceContainer): (input: OptimizePortfolioInput) => Promise<CallToolResult>;
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