I need to explore the temporal patterns in this dataset. The card shows two temporal axes: `posting_date` (2024-01-01 to 2025-04-30) and `application_deadline` (2024-01-16 to 2025-07-11). Let me start by examining the posting date trends since that's likely the primary temporal dimension for job postings. ```json { "action": "tool_call", "reasoning": "The dataset has posting_date as a temporal dimension. I'll query the time series of job postings by month to identify spikes, dips, or breaks in the pattern. Using a monthly aggregation will show clear trends while avoiding daily noise.", "tool": "query_sql", "args": { "sql": "SELECT DATE_TRUNC('month', posting_date) as month, COUNT(*) as job_count FROM raw.ai_job_dataset GROUP BY DATE_TRUNC('month', posting_date) ORDER BY month", "purpose": "Get monthly job posting counts to identify temporal spikes, dips, or breaks", "source": "raw" } } ```