Per-request cost estimation is computed and available for monitoring

Raw token counts are an abstraction that most product decisions do not operate on. Knowing a request consumed 1,200 tokens tells you nothing actionable; knowing it cost $0.014 does. Dollar cost estimation unlocks concrete decisions: which feature is too expensive to offer on the free plan, which user is consuming 10x the cohort average, whether a model swap will save $300/month, and at what traffic level a cost-per-user budget is breached. NIST AI RMF MEASURE 2.5 requires quantitative monitoring of AI operational costs; dollar estimates are that quantification.

Add a cost calculator utility in src/lib/ai/cost-calculator.ts that converts token counts to dollar amounts using model pricing constants, then call it immediately after logging token usage.

// src/lib/ai/cost-calculator.ts
const PRICE_PER_1M_TOKENS = {
  "gpt-4o":         { input: 2.50,  output: 10.00 },
  "gpt-4o-mini":    { input: 0.15,  output: 0.60  },
  "claude-3-5-sonnet-20241022": { input: 3.00, output: 15.00 },
} as const;

export function estimateCost(
  model: keyof typeof PRICE_PER_1M_TOKENS,
  promptTokens: number,
  completionTokens: number
): number {
  const p = PRICE_PER_1M_TOKENS[model];
  return (promptTokens * p.input + completionTokens * p.output) / 1_000_000;
}

Store cost_usd alongside token counts in ai_request_logs. Verify by querying the table and confirming the values are plausible for the model used.