| Last active | User | First match | Questions | Cost | Feedback |
|---|---|---|---|---|---|
| 2026-09-24 13:38 | pawel.chwieros@dext.com | Is there a measure for number of clients or subscriptions on a partner account, and a measure for account total MRR or a size band? I want to split client limit upsell by partner size and calculate revenue per client added. | 1 | $0.3279 | — |
| 2026-09-08 14:57 | pawel.chwieros@dext.com | How is AI Assist usage measured? Which fields track whether an account has AI Assist access versus actually using AI Assist? | 1 | $0.0143 | — |
| 2026-08-27 11:43 | pawel.chwieros@dext.com | Is there any field that identifies practice consolidation or M&A, for example an acquired by, merged into, parent account, or group account field on accounts? Also what values does churn_reason take? | 1 | $0.0164 | — |
| 2026-08-27 09:29 | pawel.chwieros@dext.com | Is there a churn reason or cancellation reason dimension available for accounts? Also is there an account tenure or customer age dimension, and an MRR size band or segment dimension? | 1 | $0.0228 | — |
| 2026-08-27 08:11 | pawel.chwieros@dext.com | What bookings MRR change amount measures exist besides the prepare one? Is there a commerce bookings MRR change, a precision bookings MRR change, and a combined total across all three product lines? | 2 | $0.0473 | — |
| 2026-08-26 11:37 | pawel.chwieros@dext.com | UK partner upsell MRR broken down by upsell type for May 2026 to July 2026 | 5 | $1.9707 | — |
| 2026-08-25 09:01 | pawel.chwieros@dext.com | Is there an ARR snowball dataset with a Scenario dimension containing values like "1+11", "2+10", "3+9" and sub-metrics like "ARR Opening", "Attrition (£)", "New Logo", "Upsell", "Price (£)"? If so, what is the topic/model called and what scenarios are available? | 1 | $0.0195 | — |
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.