Agent Cost Optimizer

Overview

agent-cost-optimizer provides comprehensive cost tracking, budget enforcement, and ROI measurement for AI agent operations.

Purpose: Control and optimize AI spending while maximizing value delivered

Pattern: Task-based (7 operations for cost management)

Key Innovation: Real-time cost tracking with automatic budget enforcement and cost-effective fallbacks

Industry Context (2025):

• Average AI spending: $85,521/month (36% YoY increase)
• Only 50% of organizations can measure AI ROI
• IT teams struggle with hidden costs

Solution: Comprehensive cost management from tracking to optimization

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When to Use

Use agent-cost-optimizer when:

• Tracking AI costs across skills
• Preventing budget overruns
• Measuring ROI (cost vs. value delivered)
• Optimizing model selection (Opus vs. Sonnet vs. Haiku)
• Planning AI budgets
• Cost-effective development
• Enterprise cost accountability

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Prerequisites

Required

• AI API access (Anthropic, OpenAI, Google)
• Cost tracking capability (API usage data)

Optional

• Paid.ai or AgentOps integration (advanced cost tracking)
• Prometheus/Grafana (cost visualization)
• Budget approval workflow

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Cost Operations

Operation 1: Track Token Usage

Purpose: Monitor token consumption per skill invocation

Process:

1. Initialize Tracking:

   {
     "tracking_id": "track_20250126_1200",
     "skill": "multi-ai-verification",
     "started_at": "2025-01-26T12:00:00Z",
     "tokens": {
       "prompt": 0,
       "completion": 0,
       "total": 0
     },
     "cost": {
       "amount_usd": 0.00,
       "model": "claude-sonnet-4-5"
     }
   }
   

2. Track During Execution:

   // After each AI call
   trackTokens({
     prompt_tokens: response.usage.input_tokens,
     completion_tokens: response.usage.output_tokens,
     model: 'claude-sonnet-4-5'
   });
   
   // Update running totals
   

3. Finalize Tracking:

   {
     "tracking_id": "track_20250126_1200",
     "skill": "multi-ai-verification",
     "completed_at": "2025-01-26T12:45:00Z",
     "duration_minutes": 45,
     "tokens": {
       "prompt": 15234,
       "completion": 8932,
       "total": 24166
     },
     "cost": {
       "amount_usd": 0.073,
       "model": "claude-sonnet-4-5",
       "rate": "$3 per million tokens"
     }
   }
   

4. Save to Cost Log:

   # Append to daily cost log
   cat tracking.json >> .cost-tracking/$(date +%Y-%m-%d).json
   

Outputs:

• Token usage per invocation
• Cost per invocation
• Model used
• Daily/monthly aggregates

Validation:

• Tracking initialized
• Tokens counted accurately
• Cost calculated correctly
• Logs saved

Time Estimate: Automatic (integrated into skills)

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Operation 2: Calculate Costs

Purpose: Compute accurate costs based on provider pricing

Pricing (2025 rates):

Anthropic (Claude):

OpenAI (Codex):

Google (Gemini):

Process:

function calculateCost(usage, model) {
  const pricing = {
    'claude-sonnet-4-5': { input: 3, output: 15 },
    'claude-haiku-4-5': { input: 0.80, output: 4 },
    'claude-opus-4-5': { input: 15, output: 75 },
    // ... more models
  };

  const rates = pricing[model];
  const inputCost = (usage.prompt_tokens / 1_000_000) * rates.input;
  const outputCost = (usage.completion_tokens / 1_000_000) * rates.output;

  return {
    input_cost: inputCost,
    output_cost: outputCost,
    total_cost: inputCost + outputCost,
    currency: 'USD'
  };
}

Outputs:

• Accurate cost per invocation
• Model-specific pricing
• Input vs. output cost breakdown

---

Operation 3: Enforce Budget Caps

Purpose: Prevent exceeding monthly budget limits

Process:

1. Set Budget:

   {
     "monthly_budget_usd": 100,
     "skill_budgets": {
       "multi-ai-verification": 70,
       "multi-ai-research": 20,
       "multi-ai-testing": 10
     },
     "alert_thresholds": {
       "warning": 0.80,
       "critical": 0.95
     }
   }
   

2. Check Before Operation:

   async function checkBudget(skill, estimated_cost) {
     const usage = getCurrentMonthUsage();
     const remaining = budget.monthly_budget_usd - usage.total_cost;
   
     if (estimated_cost > remaining) {
       return {
         allowed: false,
         reason: `Budget exceeded: $${usage.total_cost}/$${budget.monthly_budget_usd}`,
         overage: estimated_cost 
   

...