linear-cost-tuning

# Linear Cost Tuning

## Overview
Optimize Linear API usage to maximize efficiency and minimize costs.

## Prerequisites
- Working Linear integration
- Monitoring in place
- Understanding of usage patterns

## Cost Factors

### API Request Costs
| Factor | Impact | Optimization Strategy |
|--------|--------|----------------------|
| Request count | Direct rate limit | Batch operations |
| Query complexity | Complexity limit | Minimal field selection |
| Payload size | Bandwidth/latency | Pagination, filtering |
| Webhook volume | Processing costs | Event filtering |

## Instructions

### Step 1: Audit Current Usage
```typescript
// lib/usage-tracker.ts
interface UsageStats {
  requests: number;
  complexity: number;
  bytesTransferred: number;
  period: { start: Date; end: Date };
}

class UsageTracker {
  private stats: UsageStats = {
    requests: 0,
    complexity: 0,
    bytesTransferred: 0,
    period: { start: new Date(), end: new Date() },
  };

  recordRequest(complexity: number, bytes: number): void {
    this.stats.requests++;
    this.stats.complexity += complexity;
    this.stats.bytesTransferred += bytes;
    this.stats.period.end = new Date();
  }

  getStats(): UsageStats {
    return { ...this.stats };
  }

  getDaily(): {
    avgRequestsPerHour: number;
    avgComplexityPerRequest: number;
    projectedMonthlyRequests: number;
  } {
    const hours =
      (this.stats.period.end.getTime() - this.stats.period.start.getTime()) /
      (1000 * 60 * 60);

    return {
      avgRequestsPerHour: this.stats.requests / Math.max(hours, 1),
      avgComplexityPerRequest: this.stats.complexity / Math.max(this.stats.requests, 1),
      projectedMonthlyRequests: (this.stats.requests / Math.max(hours, 1)) * 24 * 30,
    };
  }

  reset(): void {
    this.stats = {
      requests: 0,
      complexity: 0,
      bytesTransferred: 0,
      period: { start: new Date(), end: new Date() },
    };
  }
}

export const usageTracker = new UsageTracker();
```

### Step 2: Re