Chandler · usage
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Prompt

Show account_crn for all child accounts whose parent_account_crn is 7333782788, as of snapshot date 2026-04-23. Order by account_crn descending. Only return the account_crn column, not parent_account_crn.

Outcome
success
Cost
$1.6656
excludes embeddings
Latency
171.9 s
Query attempts
4
Rows returned
1
Tokens
2,059,822 / 7,314
in / out

Request

request_id
9c059889-ca92-4c6d-9ce6-982a476cbcb3
When
2026-09-08 12:23
Tool
ask
User
yordan@dext.com · Yordan Todorov Ivanov
Identity
google
Session
bed19888-f192-4cab-aa9c-b6bfef1fb538
Model
gpt-5.6-sol

Route taken

Topic
Product Usage - Accounts
Omni model
e407bba6-4fae-4079-ac4e-cd6cf8fdf6f8
Match method
agent loop
Nudge shown
—
Question shape
not classified
Caveat raised
—
Sharper question offered
—

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.

SQL that ran

SELECT
  LISTAGG(omni_dbt__eds_all_accounts."ACCOUNT_CRN", ',') WITHIN GROUP (ORDER BY omni_dbt__eds_all_accounts."ACCOUNT_CRN" DESC) AS "Account CRN"
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."DATE_DAY" = DATE_FROM_PARTS(2026, 4, 23)
  AND TRY_TO_NUMBER(omni_dbt__eds_all_accounts."PARENT_ACCOUNT_CRN") = 7333782788
  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
  AND omni_dbt__eds_all_accounts."SALESFORCE_ACCOUNT_TYPE" <> 'Reseller'
LIMIT 1

Feedback

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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.