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Session

User
chris.scott@dext.com · Chris Scott
Started
2026-09-20 12:19
Last activity
2026-09-20 12:32
Questions
6
Grouping
time_gap — inferred — consecutive questions from this user with no long gap
session_id
cac0ec37-e788-48e9-979d-e0c4e28613a6

Transcript

  1. 2026-09-20 12:22 ask success $23.4935 148.8 s full detail →
    For account CRN 5327143919 (Goldwells), what was its MRR on 2026-07-12 versus its current MRR?
    Data answer — see full detail.
    1 row Bookings
  2. 2026-09-20 12:23 ask success $0.3926 48.7 s full detail →
    For account CRN 7232648478 (BK Plus), what was its MRR on 2026-06-01 versus its current MRR?
    Data answer — see full detail.
    1 row
  3. 2026-09-20 12:28 ask success $17.7907 186.1 s full detail →
    For account CRN 7331228738 (Smooth Accounting), what was its MRR on 2026-08-02 versus its current MRR?
    Data answer — see full detail.
    2 rows Bookings
  4. 2026-09-20 12:31 ask success $17.5368 156.8 s full detail →
    For account CRN 6205277086 (Ascendant), what was its MRR on 2026-09-14 versus its current MRR?
    Data answer — see full detail.
    1 row Bookings
  5. 2026-09-20 12:32 ask success $0.4101 47.7 s full detail →
    For account CRN 6205277086 (Ascendant), what was its MRR on 2026-09-07 versus its current MRR?
    Data answer — see full detail.
    1 row
  6. 2026-09-20 12:35 ask success $23.9906 205.9 s full detail →
    For account CRN 6398392312 (Affinia), what was its MRR on 2026-09-08 versus its current MRR?
    Data answer — see full detail.
    1 row Bookings

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.