Chandler · usage
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Prompt

Which Omni field tracks document extraction usage that counts toward an account's "prepare" plan limit? I'm seeing options like Volume of Receipts, Volume of Items Submitted, and Volume of Items Extracted - which one is the correct field for usage against the prepare limit?

Outcome
success
Cost
$0.0275
excludes embeddings
Latency
14.1 s
Query attempts
0
Rows returned
—
Tokens
3,934 / 650
in / out

Request

request_id
067d9b7c-732e-4434-9d0b-5301da202adb
When
2026-09-10 10:31
Tool
ask
User
yordan@dext.com · Yordan Todorov Ivanov
Identity
google
Session
ac099fa3-f528-4968-8a64-d1d9640ce920
Model
gpt-5.6-sol

Route taken

Topic
—
Omni model
—
Match method
agent loop
Nudge shown
disclaimer
Question shape
not classified
Caveat raised
—
Sharper question offered
—
Shown to user
Chandler is still young and makes mistakes in his calculations sometimes — reach out to the Data & Analytics team in #analytics-questions-and-alerts if you have questions.

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.

Feedback

No feedback linked to this request.

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.