For the AI Assist guidance named "Correct Total Amount to GBP for Car Rentals", was it created by a user or by the agent (Dext AI)? What is its created-by value and created date?
Basis: Created-by value and created date for the named AI Assist guidance; the indexed topic does not expos, latest available account snapshot. Governed filters applied. Every row's «Created By» came back empty. That is usually a wrong field or join rather than missing data.
Per-step detail — each LLM call, each Omni request, each rejected draft —
is traced to stdout only and is not stored, so it cannot be shown here.
Query attempts counts run_query executions, not model turns.
SELECT 'Correct Total Amount to GBP for Car Rentals' AS "Requested Guidance Name", CAST(NULL AS STRING) AS "Created By", CAST(NULL AS DATE) AS "Created Date", MAX(omni_dbt__eds_calendar_day."DATE_DAY") AS "Snapshot Date", COUNT(DISTINCT omni_dbt__eds_all_accounts."DERIVED_ACCOUNT_ID") AS "Current Eligible Accounts Checked" FROM PROD."EDS_ALL_ACCOUNTS" AS omni_dbt__eds_all_accounts INNER JOIN PROD."EDS_CALENDAR_DAY" AS omni_dbt__eds_calendar_day ON omni_dbt__eds_calendar_day."DATE_DAY" >= omni_dbt__eds_all_accounts."VALID_FROM" AND omni_dbt__eds_calendar_day."DATE_DAY" <= omni_dbt__eds_all_accounts."VALID_TO" WHERE omni_dbt__eds_calendar_day."IS_LATEST_AVAILABLE_DATE" = TRUE AND (omni_dbt__eds_all_accounts."IS_DEXT_DEMO" = FALSE OR omni_dbt__eds_all_accounts."IS_DEXT_DEMO" IS NULL) AND omni_dbt__eds_all_accounts."IS_SUSPENDED_DEXT" = FALSE LIMIT 1
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Cost is the LLM completion spend LiteLLM priced for each call, summed per
request.
Chandler is running on the Codex CLI, which draws ChatGPT plan quota
rather than per-token API billing, so this figure is not money paid —
it is what the same traffic would have cost on the API, priced from the
token counts Codex reports. Read it as the size of the bill avoided.
Two known limits: embedding spend is not recorded, so
retrieval and matching cost is missing, and because the figure is one sum
per request it cannot be split by model within a request — a
request's classifier and agent calls can use different models while
llm_model holds only one name.
Only authenticated calls are logged, USAGE_LOG_ENABLED can
switch logging off, and log writes are fail-soft — this is not a complete
record of traffic. Questions are grouped into sessions: a session is
exact when the caller echoed its id back to us and otherwise inferred from
a 30-minute gap in that user’s activity, so a grouping is only as
good as the source shown on the session itself. A call with no
attributable user gets no session at all; those questions are listed
separately rather than dropped.