import { Tool } from "fastmcp";
import { z } from "zod";
import { recordTelemetry } from "../../../utils/telemetry.js";

// ============================================================================
// SIP-012 PERFORMANCE ANALYSIS AND COST OPTIMIZATION TOOLS
// ============================================================================

// Schema for contract performance analysis
const ContractAnalysisScheme = z.object({
  contractCode: z.string().describe("The Clarity contract code to analyze"),
  functionName: z.string().optional().describe("Specific function to analyze (optional)"),
  optimizationLevel: z.enum(["basic", "intermediate", "advanced"]).describe("Level of optimization analysis"),
});

const CostEstimationScheme = z.object({
  operation: z.enum([
    "map-read", "map-write", "list-append", "list-filter", "string-concat",
    "arithmetic", "contract-call", "token-transfer", "batch-operation"
  ]).describe("Type of operation to estimate"),
  dataSize: z.number().describe("Size of data being processed (e.g., list length, string length)"),
  iterations: z.number().optional().describe("Number of iterations for batch operations"),
});

const OptimizationRecommendationScheme = z.object({
  contractPattern: z.enum([
    "token-contract", "nft-collection", "defi-pool", "dao-governance", 
    "marketplace", "staking-pool", "generic"
  ]).describe("Type of contract pattern"),
  currentIssues: z.array(z.string()).describe("Current performance issues identified"),
  targetThroughput: z.string().optional().describe("Target performance goals"),
});

// SIP-012 Cost Functions (simplified representative values)
const SIP012_COSTS = {
  // Runtime costs (in units)
  runtime: {
    mapGet: 64,
    mapSet: 64,
    mapDelete: 64,
    listAppend: 32,
    listFilter: 64,
    listMap: 64,
    listFold: 64,
    stringConcat: 32,
    arithmetic: 1,
    contractCall: 1000,
    tokenTransfer: 50000,
  },
  
  // Storage costs (per byte)
  storage: {
    read: 1,
    write: 10,
  },
  
  // Block limits (post SIP-012)
  limits: {
    runtime: 5000000000,
    readCount: 15000,
    readLength: 100000000,
    writeCount: 15000,
    writeLength: 15000000,
  }
};

// Generate performance analysis for Clarity contract
export const analyzeContractPerformanceTool: Tool<undefined, typeof ContractAnalysisScheme> = {
  name: "analyze_contract_performance",
  description: "Analyze a Clarity contract for performance bottlenecks and SIP-012 optimization opportunities. Provides detailed cost breakdown and optimization recommendations.",
  parameters: ContractAnalysisScheme,
  execute: async (args, context) => {
    try {
      await recordTelemetry({ action: "analyze_contract_performance" }, context);
      
      // Parse contract for performance analysis
      const analysis = analyzeContractCode(args.contractCode, args.functionName);
      const optimizations = generateOptimizations(analysis, args.optimizationLevel);
      
      return `# SIP-012 Performance Analysis

## Contract Overview
- **Functions Analyzed**: ${analysis.functionCount}
- **Map Operations**: ${analysis.mapOperations}
- **List Operations**: ${analysis.listOperations}
- **Contract Calls**: ${analysis.contractCalls}

## Performance Metrics

### Estimated Resource Usage
\`\`\`
Runtime Cost: ${analysis.estimatedCosts.runtime.toLocaleString()} units
Read Operations: ${analysis.estimatedCosts.readCount}
Write Operations: ${analysis.estimatedCosts.writeCount}
Storage Read: ${analysis.estimatedCosts.readLength} bytes
Storage Write: ${analysis.estimatedCosts.writeLength} bytes
\`\`\`

### Block Capacity Usage
- **Runtime**: ${((analysis.estimatedCosts.runtime / SIP012_COSTS.limits.runtime) * 100).toFixed(2)}% of block limit
- **Read Count**: ${((analysis.estimatedCosts.readCount / SIP012_COSTS.limits.readCount) * 100).toFixed(2)}% of block limit
- **Write Count**: ${((analysis.estimatedCosts.writeCount / SIP012_COSTS.limits.writeCount) * 100).toFixed(2)}% of block limit

## Performance Issues Detected

${analysis.issues.map(issue => `### ${issue.type}
- **Severity**: ${issue.severity}
- **Description**: ${issue.description}
- **Impact**: ${issue.impact}
- **Location**: ${issue.location || 'Multiple locations'}
`).join('\n')}

## SIP-012 Optimization Opportunities

${optimizations.map(opt => `### ${opt.title}
- **Type**: ${opt.type}
- **Potential Savings**: ${opt.savings}
- **Implementation**: ${opt.implementation}

**Before:**
\`\`\`clarity
${opt.before}
\`\`\`

**After:**
\`\`\`clarity
${opt.after}
\`\`\`
`).join('\n')}

## Performance Recommendations

### Immediate Actions
${optimizations.filter(o => o.priority === 'high').map(o => `- ${o.title}: ${o.savings}`).join('\n')}

### Medium-term Improvements  
${optimizations.filter(o => o.priority === 'medium').map(o => `- ${o.title}: ${o.savings}`).join('\n')}

### Advanced Optimizations
${optimizations.filter(o => o.priority === 'low').map(o => `- ${o.title}: ${o.savings}`).join('\n')}

## Next Steps
1. Implement high-priority optimizations first
2. Profile contract with Clarinet performance tests
3. Monitor gas usage in production
4. Consider batch operations for high-frequency functions
5. Leverage SIP-012 dynamic list sizing for collections

## SIP-012 Specific Benefits
✅ **2x Database Operations**: Take advantage of increased read/write limits
✅ **Dynamic List Storage**: Reduce storage costs with actual-size assessment
✅ **Optimized Cost Functions**: More accurate performance modeling
✅ **Enhanced Throughput**: Better block space utilization`;
      
    } catch (error) {
      return `❌ Failed to analyze contract performance: ${error}`;
    }
  },
};

// Estimate costs for specific operations
export const estimateOperationCostTool: Tool<undefined, typeof CostEstimationScheme> = {
  name: "estimate_operation_cost",
  description: "Estimate the computational cost of specific Clarity operations based on SIP-012 cost functions. Useful for planning contract optimization.",
  parameters: CostEstimationScheme,
  execute: async (args, context) => {
    try {
      await recordTelemetry({ action: "estimate_operation_cost" }, context);
      
      const costs = calculateOperationCost(args.operation, args.dataSize, args.iterations || 1);
      const blockUtilization = calculateBlockUtilization(costs);
      
      return `# Operation Cost Estimation

## Operation Details
- **Type**: ${args.operation}
- **Data Size**: ${args.dataSize.toLocaleString()}
- **Iterations**: ${args.iterations || 1}

## Estimated Costs (SIP-012)

### Resource Consumption
\`\`\`
Runtime Cost: ${costs.runtime.toLocaleString()} units
Read Count: ${costs.readCount} operations
Write Count: ${costs.writeCount} operations  
Read Length: ${costs.readLength.toLocaleString()} bytes
Write Length: ${costs.writeLength.toLocaleString()} bytes
\`\`\`

### Block Utilization
- **Runtime**: ${blockUtilization.runtime.toFixed(4)}% (${costs.runtime.toLocaleString()}/${SIP012_COSTS.limits.runtime.toLocaleString()})
- **Read Count**: ${blockUtilization.readCount.toFixed(4)}% (${costs.readCount}/${SIP012_COSTS.limits.readCount})
- **Write Count**: ${blockUtilization.writeCount.toFixed(4)}% (${costs.writeCount}/${SIP012_COSTS.limits.writeCount})
- **Read Length**: ${blockUtilization.readLength.toFixed(4)}% (${costs.readLength.toLocaleString()}/${SIP012_COSTS.limits.readLength.toLocaleString()})
- **Write Length**: ${blockUtilization.writeLength.toFixed(4)}% (${costs.writeLength.toLocaleString()}/${SIP012_COSTS.limits.writeLength.toLocaleString()})

### Performance Analysis
${blockUtilization.runtime > 50 ? '⚠️ **High Runtime Usage**: Consider optimization' : '✅ **Runtime**: Within reasonable bounds'}
${blockUtilization.readCount > 50 ? '⚠️ **High Read Count**: Consider batching or caching' : '✅ **Read Count**: Efficient database usage'}
${blockUtilization.writeCount > 50 ? '⚠️ **High Write Count**: Consider data structure optimization' : '✅ **Write Count**: Efficient storage usage'}

## Optimization Suggestions

${getOptimizationSuggestions(args.operation, costs, blockUtilization)}

## Batch Operation Analysis
${args.iterations && args.iterations > 1 ? `
**Single Operation Cost**: ${Math.round(costs.runtime / args.iterations).toLocaleString()} runtime units
**Batch Efficiency**: ${(args.iterations > 10 ? 'High' : args.iterations > 5 ? 'Medium' : 'Low')} efficiency gain
**Recommended Batch Size**: ${getRecommendedBatchSize(args.operation, costs)}
` : 'Single operation - consider batching for multiple operations'}

## SIP-012 Improvements
✅ **Enhanced Limits**: 2x more database operations available
✅ **Better Costing**: More accurate runtime cost estimation  
✅ **Dynamic Storage**: List storage based on actual size
✅ **Improved Throughput**: Better block space utilization`;
      
    } catch (error) {
      return `❌ Failed to estimate operation cost: ${error}`;
    }
  },
};

// Generate optimization recommendations
export const generateOptimizationRecommendationsTool: Tool<undefined, typeof OptimizationRecommendationScheme> = {
  name: "generate_optimization_recommendations",
  description: "Generate specific optimization recommendations for Clarity contracts based on SIP-012 improvements and best practices.",
  parameters: OptimizationRecommendationScheme,
  execute: async (args, context) => {
    try {
      await recordTelemetry({ action: "generate_optimization_recommendations" }, context);
      
      const recommendations = generatePatternOptimizations(args.contractPattern, args.currentIssues);
      
      return `# SIP-012 Optimization Recommendations

## Contract Pattern: ${args.contractPattern.toUpperCase()}

${args.targetThroughput ? `**Target Performance**: ${args.targetThroughput}` : ''}

## Current Issues Analysis
${args.currentIssues.map(issue => `- ${issue}`).join('\n')}

## Optimization Strategy

${recommendations.map((rec: any, index: number) => `
### ${index + 1}. ${rec.title}
**Priority**: ${rec.priority.toUpperCase()}
**Expected Impact**: ${rec.impact}
**Implementation Effort**: ${rec.effort}

**Problem**: ${rec.problem}

**Solution**: ${rec.solution}

**Implementation**:
\`\`\`clarity
${rec.code}
\`\`\`

**Benefits**:
${rec.benefits.map((b: string) => `- ${b}`).join('\n')}

**SIP-012 Advantages**: ${rec.sip012Benefits}
`).join('\n')}

## Implementation Roadmap

### Phase 1: Critical Optimizations (Week 1-2)
${recommendations.filter((r: any) => r.priority === 'high').map((r: any) => `- ${r.title}: ${r.impact}`).join('\n')}

### Phase 2: Performance Improvements (Week 3-4)  
${recommendations.filter((r: any) => r.priority === 'medium').map((r: any) => `- ${r.title}: ${r.impact}`).join('\n')}

### Phase 3: Advanced Optimizations (Week 5-6)
${recommendations.filter((r: any) => r.priority === 'low').map((r: any) => `- ${r.title}: ${r.impact}`).join('\n')}

## SIP-012 Specific Optimizations

### Database Operations
- **Leverage 2x Capacity**: Use increased read/write limits for complex operations
- **Batch Processing**: Group operations to minimize overhead
- **Efficient Indexing**: Optimize map key structures

### Storage Efficiency  
- **Dynamic Lists**: Take advantage of actual-size pricing
- **Data Packing**: Combine related data into tuples
- **Lazy Loading**: Defer expensive computations

### Performance Monitoring
\`\`\`clarity
;; Add performance monitoring to your contracts
(define-read-only (get-operation-cost)
  {
    estimated-runtime: u50000,
    read-operations: u2,
    write-operations: u1
  }
)
\`\`\`

## Testing Strategy
1. **Clarinet Performance Tests**: Measure actual costs
2. **Load Testing**: Test with maximum data sizes
3. **Benchmark Comparisons**: Before/after optimization
4. **Production Monitoring**: Track real-world performance

## Success Metrics
- [ ] Runtime costs reduced by ${recommendations.filter(r => r.priority === 'high').length * 25}%
- [ ] Database operations optimized for SIP-012 limits
- [ ] Storage costs minimized with dynamic sizing
- [ ] Transaction throughput improved
- [ ] User experience enhanced with faster confirmations`;
      
    } catch (error) {
      return `❌ Failed to generate optimization recommendations: ${error}`;
    }
  },
};

// Helper functions for analysis
function analyzeContractCode(code: string, targetFunction?: string) {
  // Simplified contract analysis
  const mapOperations = (code.match(/map-(get|set|delete)\?/g) || []).length;
  const listOperations = (code.match(/\b(append|filter|map|fold)\b/g) || []).length;
  const contractCalls = (code.match(/contract-call\?/g) || []).length;
  const functionCount = (code.match(/define-(public|private|read-only)/g) || []).length;
  
  // Estimate costs based on operations
  const estimatedCosts = {
    runtime: mapOperations * SIP012_COSTS.runtime.mapGet + 
            listOperations * SIP012_COSTS.runtime.listAppend + 
            contractCalls * SIP012_COSTS.runtime.contractCall,
    readCount: mapOperations + listOperations,
    writeCount: (code.match(/map-set|map-delete/g) || []).length,
    readLength: mapOperations * 40 + listOperations * 100,
    writeLength: (code.match(/map-set|map-delete/g) || []).length * 40,
  };
  
  // Identify performance issues
  const issues = [];
  
  if (mapOperations > 10) {
    issues.push({
      type: "High Database Usage",
      severity: "Medium",
      description: "Contract performs many map operations",
      impact: "May hit read/write count limits",
      location: "Multiple functions"
    });
  }
  
  if (listOperations > 5) {
    issues.push({
      type: "Inefficient List Processing",
      severity: "Medium", 
      description: "Multiple list operations detected",
      impact: "High runtime costs",
      location: "List processing functions"
    });
  }
  
  if (contractCalls > 3) {
    issues.push({
      type: "Cross-Contract Dependencies",
      severity: "Low",
      description: "Multiple external contract calls",
      impact: "Increased transaction complexity",
      location: "External interactions"
    });
  }
  
  return {
    functionCount,
    mapOperations,
    listOperations,
    contractCalls,
    estimatedCosts,
    issues
  };
}

function generateOptimizations(analysis: any, level: string) {
  const optimizations = [];
  
  if (analysis.mapOperations > 5) {
    optimizations.push({
      title: "Consolidate Map Operations",
      type: "Data Structure",
      priority: "high",
      savings: "30-50% reduction in database operations",
      implementation: "Combine multiple maps into tuple-based storage",
      before: "(define-map user-names principal (string-ascii 50))\n(define-map user-ages principal uint)",
      after: "(define-map user-data principal {name: (string-ascii 50), age: uint})"
    });
  }
  
  if (analysis.listOperations > 3) {
    optimizations.push({
      title: "Optimize List Processing",
      type: "Algorithm",
      priority: "medium",
      savings: "40-60% reduction in runtime costs",
      implementation: "Use single-pass operations instead of multiple iterations",
      before: "(let ((filtered (filter condition items)))\n  (map transform filtered))",
      after: "(fold process-and-transform items initial-value)"
    });
  }
  
  if (level === "advanced") {
    optimizations.push({
      title: "Implement Lazy Computation",
      type: "Caching",
      priority: "low",
      savings: "20-80% for repeated operations",
      implementation: "Cache expensive computations",
      before: "(expensive-calculation input)",
      after: "(match (map-get? cache input)\n  cached cached\n  (let ((result (expensive-calculation input)))\n    (map-set cache input result)\n    result))"
    });
  }
  
  return optimizations;
}

function calculateOperationCost(operation: string, dataSize: number, iterations: number) {
  const baseCosts = SIP012_COSTS.runtime;
  let costs = {
    runtime: 0,
    readCount: 0,
    writeCount: 0,
    readLength: 0,
    writeLength: 0
  };
  
  switch (operation) {
    case "map-read":
      costs.runtime = baseCosts.mapGet * iterations;
      costs.readCount = iterations;
      costs.readLength = dataSize * 40 * iterations;
      break;
      
    case "map-write":
      costs.runtime = baseCosts.mapSet * iterations;
      costs.writeCount = iterations;
      costs.writeLength = dataSize * 40 * iterations;
      break;
      
    case "list-append":
      costs.runtime = baseCosts.listAppend * iterations * Math.log2(dataSize);
      costs.writeCount = iterations;
      costs.writeLength = dataSize * 8 * iterations;
      break;
      
    case "token-transfer":
      costs.runtime = baseCosts.tokenTransfer * iterations;
      costs.readCount = iterations;
      costs.writeCount = iterations * 2;
      costs.readLength = 40 * iterations;
      costs.writeLength = 80 * iterations;
      break;
      
    case "batch-operation":
      const batchEfficiency = Math.min(0.8, Math.log10(iterations) / 2);
      costs.runtime = baseCosts.mapSet * iterations * (1 - batchEfficiency);
      costs.readCount = Math.ceil(iterations / 2);
      costs.writeCount = iterations;
      costs.writeLength = dataSize * iterations;
      break;
      
    default:
      costs.runtime = 1000 * iterations;
  }
  
  return costs;
}

function calculateBlockUtilization(costs: any) {
  return {
    runtime: (costs.runtime / SIP012_COSTS.limits.runtime) * 100,
    readCount: (costs.readCount / SIP012_COSTS.limits.readCount) * 100,
    writeCount: (costs.writeCount / SIP012_COSTS.limits.writeCount) * 100,
    readLength: (costs.readLength / SIP012_COSTS.limits.readLength) * 100,
    writeLength: (costs.writeLength / SIP012_COSTS.limits.writeLength) * 100,
  };
}

function getOptimizationSuggestions(operation: string, costs: any, utilization: any): string {
  const suggestions = [];
  
  if (utilization.runtime > 25) {
    suggestions.push("**Runtime Optimization**: Consider algorithm improvements or caching");
  }
  
  if (utilization.readCount > 25) {
    suggestions.push("**Database Optimization**: Implement data consolidation or batching");
  }
  
  if (utilization.writeCount > 25) {
    suggestions.push("**Storage Optimization**: Use tuple-based storage or reduce write frequency");
  }
  
  switch (operation) {
    case "list-append":
      suggestions.push("**List Optimization**: Consider using dynamic lists (SIP-012 benefit)");
      break;
    case "map-write":
      suggestions.push("**Map Optimization**: Batch multiple updates into single operation");
      break;
    case "token-transfer":
      suggestions.push("**Transfer Optimization**: Use batch transfer functions for multiple recipients");
      break;
  }
  
  return suggestions.join('\n');
}

function getRecommendedBatchSize(operation: string, costs: any): string {
  const runtimePerOp = costs.runtime;
  
  if (runtimePerOp < 1000) return "50-100 operations";
  if (runtimePerOp < 10000) return "25-50 operations";
  if (runtimePerOp < 50000) return "10-25 operations";
  return "5-10 operations";
}

function generatePatternOptimizations(pattern: string, issues: string[]) {
  const baseOptimizations = {
    "token-contract": [
      {
        title: "Implement Batch Transfers",
        priority: "high",
        impact: "50-70% cost reduction for multiple transfers",
        effort: "Medium",
        problem: "Individual transfers are expensive",
        solution: "Batch multiple transfers in single transaction",
        code: "(define-public (batch-transfer (transfers (list 25 {recipient: principal, amount: uint})))\n  (fold execute-transfer transfers (ok u0)))",
        benefits: ["Reduced per-transfer overhead", "Better UX for airdrops", "Lower gas costs"],
        sip012Benefits: "Leverages increased write capacity for efficient batch processing"
      },
      {
        title: "Optimize Balance Storage",
        priority: "medium",
        impact: "20-30% storage cost reduction",
        effort: "Low",
        problem: "Separate maps for different user data",
        solution: "Consolidate user data into single map with tuple",
        code: "(define-map user-data principal {balance: uint, last-transfer: uint, flags: uint})",
        benefits: ["Fewer database operations", "Consolidated user data", "Easier maintenance"],
        sip012Benefits: "Reduced read/write operations with tuple-based storage"
      }
    ],
    
    "nft-collection": [
      {
        title: "Dynamic Metadata Storage",
        priority: "high",
        impact: "40-60% metadata storage savings",
        effort: "Medium",
        problem: "Fixed-size metadata allocations waste storage",
        solution: "Use SIP-012 dynamic list sizing for variable metadata",
        code: "(define-map token-metadata uint {name: (string-ascii 64), traits: (list 20 (string-ascii 32))})",
        benefits: ["Pay only for actual metadata size", "Flexible trait system", "Reduced costs"],
        sip012Benefits: "Dynamic list storage assessment based on actual content"
      }
    ],
    
    "defi-pool": [
      {
        title: "State Consolidation",
        priority: "high",
        impact: "30-50% operation cost reduction",
        effort: "High",
        problem: "Multiple state variables require separate reads/writes",
        solution: "Consolidate pool state into single tuple",
        code: "(define-data-var pool-state {reserve-a: uint, reserve-b: uint, k: uint, fees: uint} ...)",
        benefits: ["Atomic state updates", "Consistent data", "Fewer operations"],
        sip012Benefits: "Single read/write operations for complete state updates"
      }
    ],
    
    "generic": [
      {
        title: "Implement Caching Strategy",
        priority: "medium",
        impact: "Variable (20-80% for repeated operations)",
        effort: "Medium",
        problem: "Expensive computations repeated multiple times",
        solution: "Cache computation results in maps",
        code: "(define-map computation-cache uint uint)\n(define-private (cached-compute (input uint))\n  (match (map-get? computation-cache input)\n    cached cached\n    (let ((result (expensive-computation input)))\n      (map-set computation-cache input result)\n      result)))",
        benefits: ["Avoid redundant computations", "Predictable costs", "Better performance"],
        sip012Benefits: "Efficient caching with optimized map operations"
      }
    ]
  };
  
  return baseOptimizations[pattern as keyof typeof baseOptimizations] || baseOptimizations["generic"];
}