Chandler · usage
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Prompt

How many Clients have Payments access?

Outcome
internal_error
Cost
unpriced
LiteLLM could not price this model
Latency
10.4 s
Query attempts
0
Rows returned
—
Tokens
0 / 0
in / out

Request

request_id
f08f15ff-2f37-444b-88c6-baf100d10f80
When
2026-08-28 14:32
Tool
ask
User
oliver.paterson@dext.com · Oliver Paterson
Identity
google
Session
2695be16-a9ac-488a-a622-d6ce49b84670
Model
not recorded

Route taken

Topic
—
Omni model
—
Match method
agent loop
Nudge shown
—
Question shape
not classified
Caveat raised
—
Sharper question offered
—

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.

Error

Error calling tool 'ask': RetryError[<Future at 0xe192f85facd0 state=finished raised RateLimitError>]

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.