```json { "action": "tool_call", "reasoning": "The evidence shows llm_calls.cost_usd has a total of $609.16 across 49,360 calls, making it the primary business metric tracking AI spend. I need to identify the specific calls with the highest and lowest costs to show the extremes of this distribution.", "tool": "query_sql", "args": { "sql": "WITH ranked AS (SELECT id, created_at, purpose, model, provider, input_tokens, output_tokens, cache_read_tokens, cost_usd, latency_ms, ROW_NUMBER() OVER (ORDER BY cost_usd DESC) as rank_high, ROW_NUMBER() OVER (ORDER BY cost_usd ASC) as rank_low FROM raw.llm_calls WHERE cost_usd > 0) SELECT id, created_at, purpose, model, provider, input_tokens, output_tokens, cache_read_tokens, cost_usd, latency_ms, CASE WHEN rank_high <= 10 THEN 'Highest' WHEN rank_low <= 10 THEN 'Lowest' END as extreme FROM ranked WHERE rank_high <= 10 OR rank_low <= 10 ORDER BY cost_usd DESC", "purpose": "Get the 10 highest and 10 lowest cost LLM calls to show the extremes of the most important business metric", "source": "raw" } } ```