Agent skill

cost-accrual-tracker

Track real-time API cost accrual during LLM execution. Activate on 'cost tracking', 'token usage', 'API costs', 'budget monitoring', 'usage metrics'. NOT for cost estimation, pricing tiers, or billing systems.

Stars 81
Forks 12

Install this agent skill to your Project

npx add-skill https://github.com/curiositech/some_claude_skills/tree/main/.claude/skills/cost-accrual-tracker

Metadata

Additional technical details for this skill

tags
cost accrual tracker
pairs with
[
    {
        "skill": "cost-optimizer",
        "reason": "Real-time cost tracking data feeds the optimizer decision engine for model downgrades"
    },
    {
        "skill": "cost-verification-auditor",
        "reason": "Tracked costs are validated against actual API bills by the verification auditor"
    },
    {
        "skill": "llm-router",
        "reason": "Cost accrual data informs the router model selection to stay within budget"
    }
]

SKILL.md

Cost Accrual Tracker

Real-time tracking of API costs during LLM execution with support for partial costs on abort.

When to Use

Use for:

  • Implementing real-time cost tracking during execution
  • Capturing partial costs when executions are aborted
  • Building cost display widgets for execution UIs
  • Integrating token counting into execution pipelines
  • Adding budget thresholds with auto-stop

NOT for:

  • Cost estimation before execution (use pricing calculators)
  • Billing system design (use billing-system skill)
  • Price tier management or discounts
  • Historical cost analytics dashboards

Core Patterns

1. Token-Based Cost Calculation

typescript
interface TokenUsage {
  inputTokens: number;
  outputTokens: number;
  cacheReadTokens?: number;   // Prompt caching hits
  cacheWriteTokens?: number;  // Prompt caching misses
}

interface CostCalculation {
  inputCostUsd: number;
  outputCostUsd: number;
  cacheSavingsUsd?: number;
  totalCostUsd: number;
}

function calculateCost(usage: TokenUsage, model: string): CostCalculation {
  const pricing = MODEL_PRICING[model];

  const inputCostUsd = (usage.inputTokens / 1_000_000) * pricing.inputPerMTok;
  const outputCostUsd = (usage.outputTokens / 1_000_000) * pricing.outputPerMTok;

  return {
    inputCostUsd,
    outputCostUsd,
    totalCostUsd: inputCostUsd + outputCostUsd,
  };
}

2. Incremental Accrual Pattern

Track costs as they accrue, not just at completion:

typescript
class CostAccrualTracker {
  private totalInputTokens = 0;
  private totalOutputTokens = 0;
  private accruedCostUsd = 0;
  private readonly model: string;

  constructor(model: string) {
    this.model = model;
  }

  /**
   * Called after each API response (streaming or complete)
   */
  recordUsage(usage: TokenUsage): void {
    this.totalInputTokens += usage.inputTokens;
    this.totalOutputTokens += usage.outputTokens;

    const cost = calculateCost(usage, this.model);
    this.accruedCostUsd += cost.totalCostUsd;
  }

  /**
   * Get current accrued cost (for real-time display)
   */
  getCurrentCost(): number {
    return this.accruedCostUsd;
  }

  /**
   * Finalize on completion or abort
   */
  finalize(reason: 'completed' | 'aborted' | 'failed'): CostReport {
    return {
      totalInputTokens: this.totalInputTokens,
      totalOutputTokens: this.totalOutputTokens,
      totalCostUsd: this.accruedCostUsd,
      completionReason: reason,
      finalizedAt: Date.now(),
    };
  }
}

3. Abort-Aware Cost Capture

Critical: Always capture partial costs on abort:

typescript
// In execution handler
const tracker = new CostAccrualTracker(model);

try {
  for await (const chunk of executeStream(request)) {
    if (abortSignal.aborted) {
      // CRITICAL: Capture cost BEFORE throwing
      const partialCost = tracker.finalize('aborted');
      onCostUpdate(partialCost);
      throw new AbortError('Execution aborted');
    }

    tracker.recordUsage(chunk.usage);
    onCostUpdate(tracker.getCurrentCost());
  }

  return tracker.finalize('completed');
} catch (error) {
  if (error instanceof AbortError) {
    throw error; // Already handled
  }
  return tracker.finalize('failed');
}

4. Budget Threshold Pattern

Auto-stop execution when budget is exceeded:

typescript
interface BudgetConfig {
  maxCostUsd: number;
  warnAtPercentage: number;  // e.g., 0.8 for 80%
  onWarn?: (current: number, max: number) => void;
  onExceed?: (current: number, max: number) => void;
}

function createBudgetGuard(config: BudgetConfig) {
  return {
    check(currentCostUsd: number): 'ok' | 'warn' | 'exceed' {
      const percentage = currentCostUsd / config.maxCostUsd;

      if (percentage >= 1.0) {
        config.onExceed?.(currentCostUsd, config.maxCostUsd);
        return 'exceed';
      }

      if (percentage >= config.warnAtPercentage) {
        config.onWarn?.(currentCostUsd, config.maxCostUsd);
        return 'warn';
      }

      return 'ok';
    }
  };
}

Anti-Patterns

Lost Costs on Abort

Novice thinking: "Just throw an error when aborted"

Reality: If you don't capture costs before aborting, you lose:

  • Token usage data for partial execution
  • Accurate cost reporting for billing
  • Audit trail for debugging

Timeline: Always been an issue, but became critical with expensive models (GPT-4, Claude Opus)

Correct approach: Always call finalize() with partial data BEFORE throwing abort errors.

Polling Without Debounce

Novice thinking: "Poll cost endpoint every 100ms for real-time updates"

Reality:

  • Wastes bandwidth and CPU
  • Cost updates only happen after API responses
  • Polling faster than response rate is pointless

Correct approach: Poll at 1-2 second intervals, or use event-driven updates from the execution stream.

Ignoring Prompt Caching

Novice thinking: "Just multiply tokens by price per token"

Reality: Claude's prompt caching changes the cost model:

  • Cache reads are 90% cheaper
  • Cache writes cost extra on first use
  • Ignoring caching leads to inaccurate costs

Timeline:

  • Pre-2024: No caching, simple calculation
  • 2024+: Claude prompt caching requires separate tracking

Correct approach: Track cache_read_input_tokens and cache_creation_input_tokens separately.

Per-Request Cost Objects

Novice thinking: "Create new tracker for each request"

Reality: For DAG execution with multiple nodes:

  • Need aggregate cost across all nodes
  • Need to attribute costs to specific nodes
  • Need rollup for parent execution

Correct approach: Hierarchical tracking - per-node trackers that roll up to execution-level.

State Flow

                    ┌─────────────────────────────────────────┐
                    │           CostAccrualTracker            │
                    └─────────────────────────────────────────┘
                                        │
              ┌─────────────────────────┼─────────────────────────┐
              │                         │                         │
              ▼                         ▼                         ▼
    ┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
    │  recordUsage()  │     │ getCurrentCost()│     │   finalize()    │
    │                 │     │                 │     │                 │
    │ After each API  │     │ For real-time   │     │ On completion,  │
    │ response        │     │ display         │     │ abort, or fail  │
    └─────────────────┘     └─────────────────┘     └─────────────────┘
              │                         │                         │
              │                         │                         │
              ▼                         ▼                         ▼
    ┌─────────────────────────────────────────────────────────────────┐
    │                        CostReport                               │
    │  { inputTokens, outputTokens, totalCostUsd, completionReason }  │
    └─────────────────────────────────────────────────────────────────┘

UI Display Pattern

For real-time cost display in execution UIs:

typescript
// Poll every 2 seconds while executing
useEffect(() => {
  if (status !== 'running') return;

  const interval = setInterval(async () => {
    const response = await fetch(`/api/execute/${executionId}`);
    const data = await response.json();
    setAccruedCost(data.cost.accruedUsd);
    setTokens({
      input: data.cost.inputTokens,
      output: data.cost.outputTokens,
    });
  }, 2000);

  return () => clearInterval(interval);
}, [executionId, status]);

// Display format
<div className="cost-display">
  <span className="cost-amount">${accruedCost.toFixed(4)}</span>
  <span className="token-count">
    {tokens.input.toLocaleString()} in / {tokens.output.toLocaleString()} out
  </span>
</div>

Integration Points

Component Responsibility
CostAccrualTracker Per-execution token counting and cost calculation
ExecutionManager Aggregates costs across DAG executions
BudgetGuard Threshold monitoring and auto-stop
/api/execute/:id Exposes current cost via polling
Cost Display Widget Real-time UI rendering

References

See /references/claude-api-pricing.md for current Claude API pricing.

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