List account conversion goals

Live, flexible insights query. The account's platform picks the contract: **Meta (facebook/instagram)**: forwards caller-chosen `fields`, `breakdowns` and `filtering` to any Meta insights node and returns Meta's rows verbatim. `objectId` (required) selects the node; `level` sets row granularity. Semantic validation is Meta's: an unknown field or invalid breakdown combination returns a 400 carrying Meta's message. For long ranges or agency-scale accounts prefer the async variant (POST /v1/ads/insights/reports). **Google Ads (googleads)**: raw GAQL passthrough. Send any read-only GAQL SELECT via `query` (campaign/keyword/search-term/geo/demographic/asset/shopping resources, `change_event`, any `segments.*`) and rows come back verbatim (camelCase, counters as strings). Results are paged at a fixed 10,000 rows; follow `paging.nextPageToken` with `pageToken`. `adAccountId` (alias `customerId`) is only needed when the connection has several Google Ads accounts. Semantic validation is Google's: an invalid query returns a 400 carrying Google's message (note: selecting `segments.date` requires a finite date filter). Queries run against Google Ads API **v25**, so write GAQL against the v25 field reference. One exception is translated for backward compatibility: the legacy `campaign.start_date` / `campaign.end_date` (removed by Google in v23) are rewritten to `campaign.start_date_time` / `campaign.end_date_time`, and rows still carry `campaign.startDate` / `campaign.endDate` as `YYYY-MM-DD`. In WHERE, `=`, `<`, `<=`, `>`, `>=`, `BETWEEN` and `IS [NOT] NULL` against a `'YYYY-MM-DD'` literal are translated; any other form returns Google's 400. New code should select the `_date_time` fields directly. **TikTok (tiktok/tiktokads)**: passthrough of TikTok's synchronous report (`/report/integrated/get/`). Send `adAccountId`, `dataLevel`, `dimensions`, `metrics`, `fromDate`/`toDate` (TikTok caps the span at 365 days) and optionally `filtering` in the same `[{"field", "operator", "value"}]` shape as Meta (operator is TikTok's `filter_type`, e.g. `IN`; array values are JSON-encoded for TikTok). Rows come back verbatim as `{ dimensions, metrics }` with page-number paging. *De-duplicated reach across a set of campaigns, ad groups or ads*: filter the set and group by `country_code` instead of the entity id. TikTok then counts each person once across the whole set and range, per country. Example, two campaigns for a month: `dataLevel=AUCTION_CAMPAIGN&dimensions=country_code&metrics=reach,impressions,frequency&fromDate=2026-09-01&toDate=2026-09-30&filtering=[{"field":"campaign_ids","operator":"IN","value":["1876574798182050","1876575504573650"]}]`. For a set of ads use `dataLevel=AUCTION_AD` with `ad_ids`. A filter on a finer entity than `dataLevel` (e.g. `ad_ids` at `AUCTION_CAMPAIGN`) returns 400: TikTok would otherwise widen it to every parent entity containing those ids. When the set delivers in several countries, reach is per country; summing the rows counts a person reached in two countries twice. `AUCTION_ADVERTISER` rejects entity filters.