insightslisted

# OpenAI ChatGPT Ads — Insights Answer performance questions via the `get_insights` tool. ## Request The user's question: $ARGUMENTS ## How the insights API thinks - **level** picks the scope path: `ad_account` (whole account), or `campaign` / `ad_group` / `ad` with an `entity_id`. - **aggregation_level** picks the row granularity *within* that scope — the ranking trick: `level="ad_account", aggregation_level="ad", sort_field="clicks", limit=5` = top 5 ads account-wide. - **time_granularity**: `"none"` for totals, `"daily"` for trend rows. - **since/until**: YYYY-MM-DD. Metrics: impressions, clicks, spend, ctr, cpc, cpm. ## Workflow 1. `get_ad_account` once for currency and account name. 2. Map the question to one or two `get_insights` calls (scope → aggregation → time range → sort). "Best/worst X" → sort by the metric they care about; default clicks. 3. Resolve names: insights rows carry ids — when the user thinks in names, cross-reference `list_campaigns`/`list_ads`. 4. Answer in plain language first (one sentence with the number that answers the question), then a compact table. State the date range you actually queried. Flag low-volume rows (<100 impressions) as too thin to compare. ## Anti-patterns - Dumping raw JSON instead of answering the question asked. - Comparing CTRs across rows with wildly different impression counts without saying so. - Inventing metrics the API doesn't return (no conversions in insights today — that's the Conversions API, not yet covere