Chandler · usage
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Prompt

Which partner account has a paid Precision subscription and a paid Commerce subscription but no paid Prepare subscription, as of the 2026-09-30 snapshot? Show the partner account ID, account name, and any useful details (country, Salesforce account, products).

Outcome
success
Cost
$31.5529
excludes embeddings
Latency
154.4 s
Query attempts
2
Rows returned
1
Tokens
3,769,588 / 27,423
in / out

Request

request_id
69f91c9e-bdc2-472a-bf2e-d8d920384160
When
2026-10-01 09:26
Tool
ask
User
mihail.iliev@dext.com · Mihail Iliev
Identity
google
Session
f625c317-5c7d-4e6e-8148-303004f8af81
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
lookup
Caveat raised
—
Sharper question offered
—
Shown to user
Basis: Partner accounts with paid Precision and Commerce subscriptions and explicitly no paid Prepare subsc, snapshot of 30 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
    omni_dbt__eds_all_accounts."DERIVED_ACCOUNT_ID" AS "Partner Account ID Internal",
    omni_dbt__eds_all_accounts."ACCOUNT_CRN" AS "Partner Account ID",
    omni_dbt__eds_all_accounts."ACCOUNT_NAME" AS "Account Name",
    omni_dbt__eds_all_accounts."FINANCE_COUNTRY_GROUPING" AS "Country",
    omni_dbt__eds_all_accounts."SALESFORCE_ACCOUNT_ID" AS "Salesforce Account",
    omni_dbt__eds_all_accounts."ACCOUNT_PLATFORM" AS "Platform",
    omni_dbt__eds_bookings."PRIMARY_KEY" AS "Booking Primary Key",
    MAX(omni_dbt__eds_bookings."HAS_PRECISION_PAID_SUBSCRIPTION") AS "Has Precision Paid Subscription",
    MAX(omni_dbt__eds_bookings."HAS_COMMERCE_PAID_SUBSCRIPTION") AS "Has Commerce Paid Subscription",
    MAX(omni_dbt__eds_bookings."HAS_PREPARE_PAID_SUBSCRIPTION") AS "Has Prepare Paid Subscription",
    MAX(omni_dbt__eds_bookings."PRECISION_BOOKINGS_PRODUCT_NAME") AS "Precision Product Name",
    MAX(omni_dbt__eds_bookings."COMMERCE_BOOKINGS_PRODUCT_NAME") AS "Commerce Product Name"
  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 omni_dbt__eds_calendar_day."DATE_DAY" = DATE_FROM_PARTS(2026, 9, 30)
    AND omni_dbt__eds_calendar_day."DATE_DAY" = DATE_TRUNC('month', omni_dbt__eds_calendar_day."DATE_DAY" + INTERVAL '1 month') - INTERVAL '1 day'
    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)
  GROUP BY
    omni_dbt__eds_all_accounts."DERIVED_ACCOUNT_ID",
    omni_dbt__eds_all_accounts."ACCOUNT_CRN",
    omni_dbt__eds_all_accounts."ACCOUNT_NAME",
    omni_dbt__eds_all_accounts."FINANCE_COUNTRY_GROUPING",
    omni_dbt__eds_all_accounts."SALESFORCE_ACCOUNT_ID",
    omni_dbt__eds_all_accounts."ACCOUNT_PLATFORM",
    omni_dbt__eds_bookings."PRIMARY_KEY"
),
partner_snapshot AS (
  SELECT
    "Partner Account ID Internal" AS "Partner Account ID Internal",
    "Partner Account ID" AS "Partner Account ID",
    "Account Name" AS "Account Name",
    "Country" AS "Country",
    "Salesforce Account" AS "Salesforce Account",
    "Platform" AS "Platform",
    LISTAGG(DISTINCT "Precision Product Name", ', ') WITHIN GROUP (ORDER BY "Precision Product Name") AS "Precision Product Name",
    LISTAGG(DISTINCT "Commerce Product Name", ', ') WITHIN GROUP (ORDER BY "Commerce Product Name") AS "Commerce Product Name"
  FROM booking_snapshot_grain
  GROUP BY
    "Partner Account ID Internal",
    "Partner Account ID",
    "Account Name",
    "Country",
    "Salesforce Account",
    "Platform"
  HAVING MAX(CASE WHEN "Has Precision Paid Subscription" = TRUE THEN 1 ELSE 0 END) = 1
    AND MAX(CASE WHEN "Has Commerce Paid Subscription" = TRUE THEN 1 ELSE 0 END) = 1
    AND MAX(CASE WHEN "Has Prepare Paid Subscription" = TRUE THEN 1 ELSE 0 END) = 0
    AND MAX(CASE WHEN "Has Prepare Paid Subscription" = FALSE THEN 1 ELSE 0 END) = 1
)
SELECT
  "Partner Account ID" AS "Partner Account ID",
  "Account Name" AS "Account Name",
  "Country" AS "Country",
  "Salesforce Account" AS "Salesforce Account",
  'Precision, Commerce' AS "Paid Products",
  "Precision Product Name" AS "Precision Product Name",
  "Commerce Product Name" AS "Commerce Product Name",
  "Platform" AS "Platform"
FROM partner_snapshot
ORDER BY "Account Name"
LIMIT 100

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.