Chandler · usage
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Prompt

For account CRN 6232467381, compare its MRR on 2026-05-29 to its current MRR, give me just those two numbers

Outcome
success
Cost
$23.2107
excludes embeddings
Latency
127.3 s
Query attempts
3
Rows returned
1
Tokens
2,777,005 / 14,465
in / out

Request

request_id
34773641-8c22-41f8-98f6-628bb50a70cd
When
2026-09-24 18:30
Tool
ask
User
chris.scott@dext.com · Chris Scott
Identity
google
Session
67cf914d-9500-4868-80a9-322430d351e9
Model
gpt-5.6-sol

Route taken

Topic
Bookings
Omni model
e407bba6-4fae-4079-ac4e-cd6cf8fdf6f8
Match method
agent loop
Nudge shown
feedback_nudge
Question shape
decision_shaped
Caveat raised
—
Sharper question offered
—
Shown to user
Basis: Prepare Monthly ACV as the MRR-equivalent for Accountant account CRN 6232467381, snapshots of 29 May 2026 and the latest available date (23 Sep 2026). Governed filters applied.
How did I do with this report?

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

WITH booking_snapshot_grain AS (
  SELECT DISTINCT
    omni_dbt__eds_calendar_day."DATE_DAY" AS "Snapshot Date",
    omni_dbt__eds_calendar_day."IS_LATEST_AVAILABLE_DATE" AS "Is Latest Available Date",
    omni_dbt__eds_bookings."PRIMARY_KEY" AS "Booking Primary Key",
    omni_dbt__eds_bookings."PREPARE_BOOKINGS_MONTHLY_ACV" AS "Monthly Revenue"
  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"
LEFT JOIN PROD."EDS_BOOKINGS" AS omni_dbt__eds_bookings
  ON omni_dbt__eds_all_accounts."DERIVED_ACCOUNT_ID" = omni_dbt__eds_bookings."DERIVED_ACCOUNT_ID" AND omni_dbt__eds_calendar_day."DATE_DAY" >= omni_dbt__eds_bookings."VALID_FROM" AND omni_dbt__eds_calendar_day."DATE_DAY" <= omni_dbt__eds_bookings."VALID_TO"
  WHERE TRY_TO_NUMBER(omni_dbt__eds_all_accounts."ACCOUNT_CRN") = 6232467381
    AND (omni_dbt__eds_calendar_day."DATE_DAY" = DATE_FROM_PARTS(2026, 5, 29)
      OR omni_dbt__eds_calendar_day."IS_LATEST_AVAILABLE_DATE" = TRUE)
    AND omni_dbt__eds_calendar_day."DATE_DAY" >= DATE_FROM_PARTS(2026, 3, 24)
    AND omni_dbt__eds_calendar_day."DATE_DAY" < DATE_FROM_PARTS(2026, 9, 24)
    AND omni_dbt__eds_all_accounts."FINANCE_ACCOUNT_TYPE" = 'Accountant'
    AND COALESCE(omni_dbt__eds_all_accounts."IS_DEXT_DEMO", FALSE) = FALSE
    AND omni_dbt__eds_all_accounts."FRANCHISE_NAME" IS NULL
    AND (omni_dbt__eds_all_accounts."SALESFORCE_ACCOUNT_TYPE" != 'Reseller'
      OR omni_dbt__eds_all_accounts."SALESFORCE_ACCOUNT_TYPE" IS NULL)
)
SELECT
  SUM(CASE WHEN "Snapshot Date" = DATE_FROM_PARTS(2026, 5, 29) THEN "Monthly Revenue" END) AS "MRR on 2026-05-29",
  SUM(CASE WHEN "Is Latest Available Date" = TRUE THEN "Monthly Revenue" END) AS "Current MRR"
FROM booking_snapshot_grain
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.