Chandler · usage
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Session

User
chris.scott@dext.com · Chris Scott
Started
2026-09-24 18:07
Last activity
2026-09-24 18:34
Questions
16
Grouping
time_gap — inferred — consecutive questions from this user with no long gap
session_id
67cf914d-9500-4868-80a9-322430d351e9

Transcript

  1. 2026-09-24 18:09 ask success $17.4917 126.5 s full detail →
    For account CRN 7132303002 (Pitcher Partners SA Pty Ltd), what was its MRR on 2026-05-01 versus its current MRR?
    Data answer — see full detail.
    1 row Bookings
  2. 2026-09-24 18:10 ask success $0.3628 36.4 s full detail →
    For account CRN 6391632953 (Pangea Advisory Pty Ltd), what was its MRR on 2026-07-01 versus its current MRR?
    Data answer — see full detail.
    1 row
  3. 2026-09-24 18:10 ask success $0.3691 40.4 s full detail →
    For account CRN 6305188881 (The BlueRock), what was its MRR on 2026-06-01 versus its current MRR?
    Data answer — see full detail.
    1 row
  4. 2026-09-24 18:13 ask success $12.7777 177.6 s full detail →
    For account CRN 8307087859 (Sparrow Advisory Pty Ltd), what was its MRR on 2026-04-25 versus its current MRR?
    Data answer — see full detail.
    18 rows Bookings
  5. 2026-09-24 18:14 ask success $0.3440 24.7 s full detail →
    For account CRN 8307087859, what was its MRR on 2026-04-25 versus its current MRR?
    Data answer — see full detail.
    18 rows
  6. 2026-09-24 18:16 ask success $17.4488 121.5 s full detail →
    What is the current MRR (most recent snapshot) for account CRN 8307087859?
    Data answer — see full detail.
    1 row Bookings
  7. 2026-09-24 18:19 ask success $24.0199 205.5 s full detail →
    For account CRN 9925868674 (GKP Accounts), what was its MRR on 2026-04-25 versus its current MRR?
    Data answer — see full detail.
    14 rows Bookings
  8. 2026-09-24 18:20 ask success $0.3566 28.4 s full detail →
    What is the current MRR (most recent snapshot) for account CRN 9925868674?
    Data answer — see full detail.
    1 row
  9. 2026-09-24 18:24 ask success $39.2114 226.7 s full detail →
    For account CRN 8647576055 (Services Comptables Cateva Inc.), what was its MRR on 2026-05-03 versus its current MRR?
    Data answer — see full detail.
    1 row Bookings
  10. 2026-09-24 18:27 ask success $30.5349 168.9 s full detail →
    What is the current MRR (most recent snapshot) for account CRN 8647576055?
    Data answer — see full detail.
    1 row Bookings
  11. 2026-09-24 18:27 ask success $0.3862 35.8 s full detail →
    For account CRN 8760469001 (FG EXPERTISE COMPTABLE), what was its MRR on 2026-05-13 versus its current MRR?
    Data answer — see full detail.
    1 row
  12. 2026-09-24 18:28 ask success $0.3663 29.6 s full detail →
    For account CRN 6232467381 (Mon Expert-Comptable), what was its MRR on 2026-05-29 versus its current MRR?
    Data answer — see full detail.
    61 rows
  13. 2026-09-24 18:30 ask success $23.2107 127.3 s full detail →
    For account CRN 6232467381, compare its MRR on 2026-05-29 to its current MRR, give me just those two numbers
    Data answer — see full detail.
    1 row Bookings
  14. 2026-09-24 18:33 ask success $12.6531 149.3 s full detail →
    For account CRN 9508803467, compare its MRR on 2026-06-19 to its current MRR, give me just those two numbers
    Data answer — see full detail.
    1 row Bookings
  15. 2026-09-24 18:33 ask success $0.3645 39.2 s full detail →
    For account CRN 6148532298, compare its MRR on 2026-07-20 to its current MRR, give me just those two numbers
    Data answer — see full detail.
    1 row
  16. 2026-09-24 18:34 ask success $0.3712 39.2 s full detail →
    For account CRN 7422886334, compare its MRR on 2026-06-01 to its current MRR, give me just those two numbers
    Data answer — see full detail.
    1 row

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.