Chandler · usage
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Session

User
suzannah.weinfass@dext.com · Suzannah Weinfass
Started
2026-09-11 13:09
Last activity
2026-09-11 14:37
Questions
11 (15 calls recorded — the difference is calls whose log write did not land)
Grouping
client — exact — the caller echoed the session id back to us
session_id
ea54ccfc-654f-4b4a-91d9-7388f4f3c6d2

Transcript

  1. 2026-09-11 13:22 ask success $0.0126 3.8 s full detail →
    What does the metric NECE mean?
    The metric **NECE** is not defined in the provided documentation. Please contact the Analytics team for its approved definition. - **Definition available:** No - **AI warning:** This answer was generated by AI and should be double-checked.
    Negative
  2. 2026-09-11 13:24 ask success $1.1418 248.5 s full detail →
    What is NECE and how has it changed over the last 6 complete months (monthly)?
    NECE is not defined in the provided documentation, and no corresponding field or view is available. Therefore, I cannot explain the metric or calculate its monthly change without inventing a definition. Please contact the Analytics team for the authoritative definition and data source. - **Metric definition:** Not documented - **Monthly results:** No data available - **Intended period:** March–August 2026, the last six complete months - **Required information:** NECE definition and its source field/view **Warning:** This answer was generated by AI and should be double-checked.
    Product Usage - Accounts
  3. 2026-09-11 13:41 feedback success unpriced 5 ms full detail →
    —
    No answer recorded.
  4. 2026-09-11 13:41 ask success $0.0143 7.5 s full detail →
    How has NECE changed over the last 6 complete months (monthly)?
    Data answer — see full detail.
    7 rows
  5. 2026-09-11 13:47 ask success $0.0142 10.0 s full detail →
    Give me the exact definition, description, and any filters/criteria for the NECE field as defined in Product Usage - Accounts.topic.yaml
    The provided documentation does not include the **NECE** field or the contents of `Product Usage - Accounts.topic.yaml`, so its exact definition, description, and filters/criteria cannot be determined. - **Missing:** NECE field-level description and AI context - **Required source:** `Product Usage - Accounts.topic.yaml` - **Next step:** Provide the relevant topic/field excerpt or contact the Analytics team. **Warning:** This answer was generated by AI and should be double-checked.
    Negative
  6. 2026-09-11 13:49 feedback success unpriced 3 ms full detail →
    —
    No answer recorded.
  7. 2026-09-11 13:56 feedback success unpriced 3 ms full detail →
    —
    No answer recorded.
  8. 2026-09-11 13:56 feedback success unpriced 2 ms full detail →
    —
    No answer recorded.
  9. 2026-09-11 14:13 ask success $1.4802 152.0 s full detail →
    How many engaged clients of type 'Solo' do we have?
    Data answer — see full detail.
    1 row Product Usage - Accounts
  10. 2026-09-11 14:37 ask success $2.5222 163.3 s full detail →
    How many Solo-type clients have had usage in the last 90 days (active/engaged filter: number of days since last usage <= 90), using the same base filters as before (Corporate finance account type, has Dext parent, not demo, not suspended, not reseller)?
    This cannot be calculated accurately from the provided documentation. The topic includes fields to identify Solo accounts and Corporate finance account type, but it does not document the required usage-recency measure or all requested base-filter fields. I will not approximate or substitute fields. - **Result:** No count available - **Available:** `intercom_user_accounts.hmrc_individual_id` identifies accounts that exist on Solo - **Available:** `intercom_user_accounts.finance_account_type = 'Corporate'` - **Missing:** Number of days since last usage, Dext-parent status, demo status, suspension status, and a documented reseller-exclusion field - **Logic required:** Count Solo client accounts where days since last usage ≤ 90, after applying all listed base filters and the topic’s default filters - **Next step:** Ask the Analytics team to provide the relevant usage field, account identifier, filter fields, joins, and topic default filters Possible follow-ups: - Which topic contains the documented “days since last usage” field? - Can the Analytics team confirm the standard fields for demo, suspended, and reseller exclusions? **Warning:** This answer was generated by AI and should be double-checked.
    Product Usage - Users
  11. 2026-09-11 14:37 ask success $0.0245 10.0 s full detail →
    Using the eds_all_accounts topic (same as the Solo client count query), is there a field for days since last usage or last activity date? I want to filter Solo, Corporate finance-type accounts to only those active/used in the last 90 days.
    The provided documentation does not list a “days since last usage,” “last activity date,” or exact 90-day engagement field in the `eds_all_accounts` view. Therefore, I cannot accurately define this filter using the available fields. - **Solo count field:** `omni_dbt__eds_all_accounts.total_distinct_dext_solo_accounts` - **Solo identifier counted:** `omni_dbt__eds_all_accounts.hmrc_individual_id` - **Corporate filter:** `eds_all_accounts.finance_account_type = 'Corporate'` - **Required activity window:** last **90 days** - **Missing:** a documented activity-date field or exact “Is Engaged” field name in this topic The model defines engagement as at least one qualifying action within 90 days, but the applicable field is not documented here. Please contact the Analytics team to confirm whether that field is available in **Product Usage - Users** and how it should be filtered. **Warning:** This answer was generated by AI and should be double-checked.

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.