All 4 distinct users (11016, 11032, 11048, 11064) appear in both checked sets, confirming the two result sets match exactly.

Show the same checked IDs for the corporate CT cli...

System: CT

client

System: CT

SELECT user_id FROM (SELECT a.id AS user_id, 1 AS set_no FROM public.accounts AS a JOIN public.clients AS c ON c.user_id = a.id WHERE a.role = 'User' AND NOT a.skip_commission_calculations IS TRUE AND NOT c.type IS NULL AND c.type <> 'PersonalAccount' AND NOT c.completed_registration_at IS NULL AND NOT EXISTS(SELECT 1 FROM public.trade_bookings AS tb WHERE tb.user_id = a.id AND tb.status <> 'closed' AND tb.deleted_at IS NULL) UNION ALL SELECT a.id AS user_id, 2 AS set_no FROM public.accounts AS a JOIN public.clients AS c ON c.user_id = a.id WHERE a.role = 'User' AND NOT a.skip_commission_calculations IS TRUE AND NOT c.type IS NULL AND c.type <> 'PersonalAccount' AND NOT c.completed_registration_at IS NULL AND NOT EXISTS(SELECT 1 FROM public.trade_bookings AS tb WHERE tb.user_id = a.id AND tb.status <> 'closed' AND tb.deleted_at IS NULL)) AS u ORDER BY u.set_no ASC, CASE WHEN u.set_no = 1 THEN u.user_id ELSE -u.user_id END ASC LIMIT 10000

SELECT
  user_id
FROM (
  SELECT
    a.id AS user_id,
    1 AS set_no
  FROM public.accounts AS a
  JOIN public.clients AS c
    ON c.user_id = a.id
  WHERE
    a.role = 'User'
    AND NOT a.skip_commission_calculations IS TRUE
    AND NOT c.type IS NULL
    AND c.type <> 'PersonalAccount'
    AND NOT c.completed_registration_at IS NULL
    AND NOT EXISTS(
      SELECT
        1
      FROM public.trade_bookings AS tb
      WHERE
        tb.user_id = a.id AND tb.status <> 'closed' AND tb.deleted_at IS NULL
    )
  UNION ALL
  SELECT
    a.id AS user_id,
    2 AS set_no
  FROM public.accounts AS a
  JOIN public.clients AS c
    ON c.user_id = a.id
  WHERE
    a.role = 'User'
    AND NOT a.skip_commission_calculations IS TRUE
    AND NOT c.type IS NULL
    AND c.type <> 'PersonalAccount'
    AND NOT c.completed_registration_at IS NULL
    AND NOT EXISTS(
      SELECT
        1
      FROM public.trade_bookings AS tb
      WHERE
        tb.user_id = a.id AND tb.status <> 'closed' AND tb.deleted_at IS NULL
    )
) AS u
ORDER BY
  u.set_no ASC,
  CASE WHEN u.set_no = 1 THEN u.user_id ELSE -u.user_id END ASC
LIMIT 10000

Corporate CT means client type is not null and not PersonalAccount, with completed_registration_at set.

'No booking' means no non-deleted trade_booking with a status other than closed, and excludes accounts flagged skip_commission_calculations.

The 8 rows are 4 user_ids each returned twice — one row per set in the union — so the two original queries agree on every member.

All rows share client_type cfx (corporate); each user_id maps to one client (Fictional Company 16, Fictional Company 32, Fictional Company 48, Fictional Company 64).

Show the same checked IDs for the corporate CT client records with completed registration who have no non-deleted, non-closed booking from the first result, this time in descending user_id order. Keep every member and show only user_id.

Each row of accounts is matched to clients by user_id, keeping only accounts with role 'User' and where skip_commission_calculations is not true.

Client rows are kept only if type is not null and not 'PersonalAccount', and completed_registration_at is not null.

For each such account, a lookup in trade_bookings excludes the account if any booking exists for it with status other than 'closed' and deleted_at null.

This same selection is produced twice, tagged set_no 1 and set_no 2, and combined one after the other.

Results are sorted by set_no first; within set_no 1 by ascending user_id, within set_no 2 by the negated user_id (so descending user_id order).

Only the user_id column is output, capped at 10,000 rows.

Summary: Lists user IDs of 'User' role accounts joined to non-personal clients with completed registration and no active bookings, duplicated as two identical sets, with the second set ordered by descending user ID, limited to 10,000 rows.


Independent synthetic fixture values, complete membership and required field types; not production or human usefulness.

4 corporate CT clients with completed registration have no non-deleted, non-closed booking membership.

Generation confidence; semantic correctness is only verified by the listed checks.

Generation confidence is not an answer certificate.

The entire question interpretation has not been independently verified.

Keep the corporate CT client records with complete...

Onboarding/client dimension keyed by user_id (= accounts.id). Declared (not traded) currencies live here.

Direct user_id; one row per user_id already. Project user_id first.

System: CT

client

Metric match

No predefined metrics are configured for this connection — scored on time clarity, query complexity and column visibility instead

Query complexity

Moderate complexity: 1 JOINs, subqueries

High confidence (85%) — moderate complexity

SELECT COUNT(DISTINCT a.id) AS client_count FROM public.accounts a JOIN public.clients c ON c.user_id = a.id WHERE a.role = 'User' AND NOT a.skip_commission_calculations IS TRUE AND c.type IS NOT NULL AND c.type <> 'PersonalAccount' AND c.completed_registration_at IS NOT NULL AND NOT EXISTS (SELECT 1 FROM public.trade_bookings tb WHERE tb.user_id = a.id AND tb.status <> 'closed' AND tb.deleted_at IS NULL)

SELECT
  COUNT(DISTINCT a.id) AS client_count
FROM public.accounts AS a
JOIN public.clients AS c
  ON c.user_id = a.id
WHERE
  a.role = 'User'
  AND NOT a.skip_commission_calculations IS TRUE
  AND NOT c.type IS NULL
  AND c.type <> 'PersonalAccount'
  AND NOT c.completed_registration_at IS NULL
  AND NOT EXISTS(
    SELECT
      1
    FROM public.trade_bookings AS tb
    WHERE
      tb.user_id = a.id AND tb.status <> 'closed' AND tb.deleted_at IS NULL
  )

Corporate CT means client type is non-null and not 'PersonalAccount'

Commission calculations excluded accounts with skip_commission_calculations set to true

Reading this as the registration-form funnel — started the signup wizard vs finished it (clients.completed_registration_at). If you meant activation (verified & ready to trade), say so.

Which 4 clients are these — list their IDs and names?

The NOT EXISTS check excludes closed bookings only by status and deleted bookings by deleted_at — bookings in any other status (e.g. awaiting_funds) still count as membership.

activation-definition activation-definition-gold onboarding-duration declared-currency-intent client-type-sti-classes

Keep the corporate CT client records with completed registration who have no non-deleted, non-closed booking membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.

Reads accounts joined to clients by matching clients.user_id to accounts.id, keeping only rows where both sides match.

Keeps only accounts where role = 'User', skip_commission_calculations is not TRUE, the client type is filled in and is not 'PersonalAccount', and completed_registration_at is filled in.

Excludes any account that has a row in trade_bookings with the same user_id where status is not 'closed' and deleted_at is empty (i.e., must have no such booking).

Returns the count of distinct remaining account IDs as client_count; if none remain, the count is zero.

Summary: Count distinct account IDs that are regular user accounts with non-personal client records, completed registration, commission calculations not skipped, and no active (non-closed, non-deleted) trade booking.


6 results — first client: Fictional Company 62

Keyed merge and authoritative-source checks.

Keys, merge grain, and source membership were checked.

Show the same checked IDs for the CT client record...

System: CT

client

System: CT

client type

The trade's PAYMENT/LIQUIDITY PARTNER — CT calls this the BROKER (live names include Corpay, Corpay Offline, Currencycloud, Clear Treasury, Moneycorp, Verto, iBan First, Central FX). Resolve the partner NAME by joining: JOIN public.broker_accounts ba ON ba.id = tb.broker_account_id JOIN public.brokers b ON b.id = ba.broker_id, then use b.name as the partner dimension (GROUP BY b.name for a by-partner breakdown; every trade_bookings row carries broker_account_id). NEVER use trade_bookings.platform for a partner/provider/broker breakdown — platform is the booking CHANNEL (web/ios/system/nexus), not a partner — and never alias platform AS payment_partner.

Direct user_id; group trade rows to one per user_id (COUNT(*) FILTER (WHERE status <> 'closed') for the default booked trade count; a settled-gated count ONLY when the user explicitly says settled). Window REALIZED money metrics (settled commission/revenue, daily run-rate, realized QoQ) on completed_at with status='settled' — NOT settlement_at (the deadline) and NOT traded_at (booking date). Use traded_at only for booking-date questions.

System: CT

broker

System: CT

Medium confidence (69%) — implicit time period, moderate complexity

Query times are separate. Source refresh time is unknown unless supplied.

SELECT user_id FROM ct.client_360 WHERE COALESCE(client_type, '') = '' AND EXISTS(SELECT 1 FROM ct.accounts AS a WHERE a.user_id = ct.client_360.user_id) GROUP BY 1 ORDER BY 1 DESC LIMIT 10000

SELECT a.id AS user_id FROM public.accounts AS a JOIN public.clients AS c ON c.user_id = a.id WHERE a.role = 'User' AND NOT a.skip_commission_calculations IS TRUE AND c.type IS NULL AND EXISTS(SELECT 1 FROM public.broker_accounts AS ba WHERE ba.user_id = a.id) ORDER BY a.id DESC NULLS LAST LIMIT 10000

CT-realized and Pipedrive pipeline measures are kept separate; not summed across sources.

churn-tier-definitions declared-currency-intent trade-existence-default-booked settlement-is-ct-trade-lifecycle activation-definition-gold client-type-sti-classes trade-existence-gold-booked

Show the same checked IDs for the CT client records whose client type is unknown and who have at least one broker account from the first result, this time in descending user_id order. Keep every member and show only user_id.

[Gold / Pipedrive] Reads ct.client_360, keeping rows where client_type is empty or missing (COALESCE(client_type,'')='') and where a matching row exists in ct.accounts on user_id.

[Gold / Pipedrive] Groups by user_id, orders them descending, and keeps at most 10000.

[CT Ledger] Joins public.accounts to public.clients on client's user_id matching the account id.

[CT Ledger] Keeps accounts with role 'User', where skip_commission_calculations is not true, where the client's type is missing (excluded when set), and where at least one public.broker_accounts row exists for that user.

[CT Ledger] Orders by account id descending (nulls last) and keeps at most 10000.

Both halves are merged by matching user_id, and only user_id is shown.

Summary: Both sources list user IDs of CT client records with an unset client type that have at least one broker account, merged per user, sorted by user_id descending, showing only user_id.


System: CT

client

System: CT

client type

System: CT

broker

Semantic: The query could not preserve the requested meaning or scope. Try the query again in a few moments

```json
{
  "sql": "",
  "explanation": "Cannot generate: the request depends on a 'third result' not provided here, and the required ct.client_360 view with columns (user_id, client_type) is not defined in the available schema.",
  "confidence": "uncertain",
  "warnings": [
    "The referenced 'thi

Keep the CT client records whose client type is unknown and who have at least one broker account membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.

The query failed to run. This could be due to a database issue or invalid data in your query.


accounts IS the canonical CT user table: accounts.id EQUALS user_id. Carries relationship_manager_id and latest_pipedrive_activity_at. A REFERRER is an account referenced by another account's affiliate_id (refer-and-earn referrer when referrer.role='User'; 'referrer(s)' is a CT concept, NEVER the Pipedrive cf_referrer custom field — same suppression as 'partners'). NAME EXPOSURE (ruling 2026-07-08): individual first/last name and company name MAY be SHOWN in result rows to anyone with vault access (the vault boundary IS the authorization) — they are filled server-side post-execution as a display column (client_name / first_name / last_name / company_name placeholders), NEVER read via model-generated SQL (the CT-leg gate rejects a physical read; the model projects `NULL AS <col>`). CONTACT PII stays intentionally NOT exposed: email, telephone/phone and IPs are never shown in results (they remain WHERE-only filters where already allowed).

Project `id AS user_id` (accounts.id is the user key); one row per user already.

System: CT

CT accounts

Quote-level rows with DIRECT user_id (= accounts.id). No account_id column. type is by_client/admin_ping/rate_alert/rsi_alert — a quote a user MADE = type 'by_client' only (rate-alert/RSI/admin pings are system rows, ~40% of the table). status booked/pending; a booked quote converted to a trade (trade_bookings.quote_id = quotes.id).

Direct user_id; group quote metrics to one row per user_id before merge.

System: CT

quotes

System: CT

System: PD

person ID

Schema: The query refers to a table or column that is unavailable on the selected connection. Try the query again in a few moments

SELECT a.id AS user_id FROM public.accounts AS a WHERE EXISTS(SELECT 1 FROM public.quotes AS q WHERE q.user_id = a.id AND q.type <> 'by_client') AND NOT EXISTS(SELECT 1 FROM public.quotes AS q2 WHERE q2.user_id = a.id AND q2.type = 'by_client') GROUP BY a.id ORDER BY 1 LIMIT 10000

SELECT COALESCE(c.user_id, pd.id) AS user_id FROM ct.client_360 AS c LEFT JOIN pipedrive.persons AS pd ON pd.id = c.pipedrive_person_id WHERE c.system_quote_count > 0 AND COALESCE(c.client_quote_count, 0) = 0 GROUP BY 1 ORDER BY 1 LIMIT 10000

List every distinct CT accounts of any role that have system-generated quotes and no user-requested quote. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.


45 results — first client: Fictional Company 3

List every distinct CT accounts of any role whose ...

System: CT

CT accounts

System: CT

quote

System: CT

quote ID

System: CT

System: PD

person ID

SELECT c.user_id FROM ct.client_360 AS c GROUP BY 1 ORDER BY 1 ASC LIMIT 10000

SELECT DISTINCT q.user_id AS user_id FROM public.quotes AS q JOIN public.trade_bookings AS tb ON tb.quote_id = q.id WHERE tb.status <> 'closed' AND tb.deleted_at IS NULL ORDER BY 1 LIMIT 10000

List every distinct CT accounts of any role whose own quote converted to a non-deleted, non-closed booking through the quote ID link. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.

[Gold / Pipedrive] Reads ct.client_360 and returns each user_id once (grouped), sorted ascending, capped at 10,000 rows.

[CT Ledger] Reads public.quotes and keeps each distinct user_id, sorted ascending, capped at 10,000 rows.

[CT Ledger] Joins each quote to public.trade_bookings by matching trade_bookings.quote_id to quotes.id, so only quotes with a linked booking count.

[CT Ledger] Excludes bookings whose status is 'closed', and requires that the booking's deleted_at is empty (not deleted).

[Merged] The two results are combined per user_id, with client and client_type coming from the Pipedrive side.

Summary: The Pipedrive half lists each user's client info from client_360; the CT Ledger half finds users whose quote is linked to a booking that isn't closed and hasn't been deleted; the halves are matched per user_id.


System: CT

CT accounts

System: CT

quotes

System: CT

client

```json
{
  "sql": "",
  "explanation": "The 'federation gold leg' instruction requires projecting only from ct.client_360, but that table is not in the provided schema (no columns defined for any listed table), so the requested user_id projection cannot be generated.",
  "confidence": "uncertain",

For exactly the CT accounts of any role that have system-generated quotes and no user-requested quote in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


System: CT

CT accounts

System: CT

quote

System: CT

quote ID

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request cannot be satisfied: the schema provides no column details for trade_bookings' deleted/closed flags, and the instructions conflict (a single client_count vs. one row per user_id from ct.client_360, which is not in the provided schema).",
  "confid

For exactly the CT accounts of any role whose own quote converted to a non-deleted, non-closed booking through the quote ID link in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


System: CT

CT accounts

System: CT

quote

System: CT

quote ID

System: CT

```json
{
  "sql": "",
  "explanation": "The request depends on a prior result's checked IDs and requires quote-to-booking conversion via ct.client_360, but no columns for ct.client_360 (or any quote/booking link fields within it) are provided in the schema, so I cannot build a valid query.",
  "con

Show the same checked IDs for the CT accounts of any role whose own quote converted to a non-deleted, non-closed booking through the quote ID link from the first result, this time in descending user_id order. Keep every member and show only user_id.


System: CT

CT accounts

System: CT

quote

System: CT

quote ID

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request references ct.client_360, pipedrive tables, a 'third result' link membership, and column-level details (roles, quote_id links, deleted/closed flags) that are not present in the provided schema, so I cannot generate a valid query.",
  "confidence":

Keep the CT accounts of any role whose own quote converted to a non-deleted, non-closed booking through the quote ID link membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.


45 results — first client: Fictional Company 64

Show the same checked IDs for the CT accounts of a...

System: CT

CT accounts

System: CT

quotes

System: CT

0 matching rows — a filter likely did not bind; verify filters. High confidence (85%) — moderate complexity

SELECT user_id FROM ct.client_360 GROUP BY user_id ORDER BY user_id DESC LIMIT 10000

SELECT a.id AS user_id FROM public.accounts AS a WHERE EXISTS(SELECT 1 FROM public.quotes AS q WHERE q.user_id = a.id AND q.type <> 'by_client') AND NOT EXISTS(SELECT 1 FROM public.quotes AS q2 WHERE q2.user_id = a.id AND q2.type = 'by_client') ORDER BY a.id DESC NULLS LAST LIMIT 10000

Show the same checked IDs for the CT accounts of any role that have system-generated quotes and no user-requested quote from the first result, this time in descending user_id order. Keep every member and show only user_id.

Gold / Pipedrive: Reads from client_360.

Gold / Pipedrive: Groups the results by user_id.

CT Ledger: Reads from accounts and quotes.

CT Ledger: Keeps only rows matching filters on user_id, id, and type.

Summary: Merges 2 sources joined per user. Gold / Pipedrive: Reads rows from client_360 grouped by user_id. CT Ledger: Reads rows from accounts and quotes.


System: CT

CT accounts

System: CT

quotes

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request cannot be translated: it depends on a nonexistent 'third result' and a ct.client_360 table not present in the provided schema (all tables list no columns).",
  "confidence": "uncertain",
  "warnings": [
    "Refers to an undefined 'third result' a

Keep the CT accounts of any role that have system-generated quotes and no user-requested quote membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.


System: CT

CT accounts

System: CT

quote

System: CT

broker

System: CT

System: PD

person ID

churn-tier-definitions trade-existence-default-booked settlement-is-ct-trade-lifecycle activation-definition-gold trade-existence-gold-booked

```json
{
  "sql": "",
  "explanation": "The provided schema lists table names only, with no columns for quotes, broker_accounts, or any pipedrive/person table, so the quote timestamp, earliest broker verification timestamp, and Pipedrive person ID cannot be referenced confidently.",
  "confidence":

List every distinct CT accounts of any role whose user-requested quote predates their earliest known broker verification timestamp. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.


System: CT

CT accounts

System: CT

System: PD

person ID

```json
{
  "sql": "",
  "explanation": "The request requires booking-status columns (deleted/settled flags) on ct.client_360, but the provided schema lists no columns for any table, so no faithful SELECT can be generated.",
  "confidence": "uncertain",
  "warnings": ["No column inventory exists for

List every distinct CT accounts of any role with a non-deleted booking but no settled booking. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.


System: CT

CT accounts

System: CT

quote

System: CT

broker

System: CT

client

churn-tier-definitions declared-currency-intent trade-existence-default-booked settlement-is-ct-trade-lifecycle client-type-sti-classes

```json
{
  "sql": "",
  "explanation": "The request requires ct.client_360 and pipedrive.* sources plus broker verification timestamps, none of which are present in the provided schema (all tables list no columns), so no valid query can be generated.",
  "confidence": "uncertain",
  "warnings": ["R

```json
{
  "sql": "",
  "explanation": "public.quotes has no timestamp column (only id, user_id, type, status, amount, buy_currency, sell_currency), so a 'quote predates first broker verification' comparison cannot be expressed in SQL.",
  "confidence": "uncertain",
  "warnings": ["The schema provi

For exactly the CT accounts of any role whose user-requested quote predates their earliest known broker verification timestamp in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


System: CT

CT accounts

System: CT

client

SELECT COUNT(DISTINCT a.id) AS client_count FROM public.accounts AS a WHERE EXISTS(SELECT 1 FROM public.trade_bookings AS tb WHERE tb.user_id = a.id AND (tb.status <> 'closed' AND tb.deleted_at IS NULL)) AND NOT EXISTS(SELECT 1 FROM public.trade_bookings AS tb2 WHERE tb2.user_id = a.id AND tb2.status = 'settled')

SELECT user_id, COUNT(DISTINCT CASE WHEN has_non_deleted_booking AND NOT has_settled_booking THEN user_id END) AS client_count FROM ct.client_360 GROUP BY 1

```json
{
  "sql": "",
  "explanation": "No query generated: the gold catalog exposes only ct.client_360's per-client rollups, and booking-level status (non-deleted vs settled) needed for this cohort predicate is not available in any gold relation, so the membership condition cannot be expressed in

For exactly the CT accounts of any role with a non-deleted booking but no settled booking in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


System: CT

CT accounts

System: CT

quote

System: CT

broker

System: CT

```json
{
  "sql": "",
  "explanation": "This request depends on a prior ('first') result and requires comparing user-requested quote timestamps against earliest broker verification timestamps, but no columns are provided for the tables and the gold-source ct.client_360 alone does not carry broker v

Show the same checked IDs for the CT accounts of any role whose user-requested quote predates their earliest known broker verification timestamp from the first result, this time in descending user_id order. Keep every member and show only user_id.


System: CT

CT accounts

System: CT

quote

System: CT

broker

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request cannot be translated: it references a 'third result' join set, broker verification timestamps, and CT account roles, but no such columns exist in the provided schema (all tables list no columns), and the federation constraint forbids any raw ct.*

Keep the CT accounts of any role whose user-requested quote predates their earliest known broker verification timestamp membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.


System: CT

CT accounts

System: CT

SELECT a.id AS user_id FROM public.accounts AS a WHERE EXISTS(SELECT 1 FROM public.trade_bookings AS tb WHERE tb.user_id = a.id AND (tb.status <> 'closed' AND tb.deleted_at IS NULL)) AND NOT EXISTS(SELECT 1 FROM public.trade_bookings AS tbs WHERE tbs.user_id = a.id AND tbs.status = 'settled') ORDER BY a.id DESC NULLS LAST LIMIT 10000

SELECT user_id FROM ct.client_360 WHERE has_non_deleted_booking = TRUE AND COALESCE(has_settled_booking, FALSE) = FALSE GROUP BY user_id ORDER BY user_id DESC LIMIT 10000

```json
{
  "sql": "",
  "explanation": "The gold catalog (ct.client_360 plus pipedrive relations) exposes no columns distinguishing non-deleted vs settled bookings, so this cohort cannot be computed in this leg.",
  "confidence": "uncertain",
  "warnings": ["Previous failure confirmed has_non_delet

Show the same checked IDs for the CT accounts of any role with a non-deleted booking but no settled booking from the first result, this time in descending user_id order. Keep every member and show only user_id.


System: CT

CT accounts

System: CT

System: PD

person ID

```json
{
  "sql": "",
  "explanation": "The required sources (ct.client_360 with booking status flags such as invoiced/closed/settled/deleted) are not present in the provided schema, so a correct query cannot be generated.",
  "confidence": "uncertain",
  "warnings": [
    "Schema lists tables but

List every distinct CT accounts of any role with an invoiced booking record that is neither closed nor settled, including records marked deleted. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.


System: CT

CT accounts

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request depends on an undefined prior result ('the third result') and requires ct.client_360 / pipedrive.* tables that are not present in the provided schema, so no valid SELECT can be generated.",
  "confidence": "uncertain",
  "warnings": [
    "Referen

Keep the CT accounts of any role with a non-deleted booking but no settled booking membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.


System: CT

CT accounts

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request requires a ct.client_360 view and invoice/settlement status columns that are not present in the provided schema (all tables list zero columns), so no valid SELECT can be generated.",
  "confidence": "uncertain",
  "warnings": ["Referenced source c

For exactly the CT accounts of any role with an invoiced booking record that is neither closed nor settled, including records marked deleted in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


System: CT

CT accounts

System: CT

```json
{
  "sql": "",
  "explanation": "The question references ct.client_360, booking records with invoiced/closed/settled status, and deleted flags, but no such tables or columns exist in the provided schema (all tables list no columns, and 'this time'/'same checked IDs' implies prior context I d

Show the same checked IDs for the CT accounts of any role with an invoiced booking record that is neither closed nor settled, including records marked deleted from the first result, this time in descending user_id order. Keep every member and show only user_id.


System: CT

CT accounts

System: CT

client

```json
{
  "sql": "",
  "explanation": "The requested query depends on tables (ct.client_360, pipedrive.*) and columns not present in the provided schema, so it cannot be generated safely.",
  "confidence": "uncertain",
  "warnings": [
    "The schema lists tables with no columns, and the required

Keep the CT accounts of any role with an invoiced booking record that is neither closed nor settled, including records marked deleted membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.


41 results — first client: Fictional Company 3

List every distinct CT accounts of any role with p...

System: CT

CT accounts

System: CT

System: PD

person ID

SELECT user_id FROM ct.client_360 WHERE NOT last_traded IS NULL GROUP BY 1 ORDER BY 1 LIMIT 10000

SELECT DISTINCT a.id AS user_id FROM public.trade_bookings AS tb JOIN public.trade_details AS td ON td.trade_booking_id = tb.id JOIN public.accounts AS a ON a.id = tb.user_id WHERE (tb.status <> 'closed' AND tb.deleted_at IS NULL) AND NOT tb.traded_at IS NULL AND tb.invoice_at IS NULL AND NOT tb.sell_currency_to_gbp_rate IS NULL AND NOT a.skip_commission_calculations IS TRUE ORDER BY 1 LIMIT 10000

List every distinct CT accounts of any role with pre-billable bookings that qualify for the CT statistics filters. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.

[Gold / Pipedrive] Reads ct.client_360 and keeps rows where last_traded is not null (excludes clients with no last_traded value), takes one row per user_id, sorts ascending.

[CT Ledger] Joins trade_bookings to trade_details on trade_booking_id, then to accounts on tb.user_id = a.id, so each booking brings in its account row.

[CT Ledger] Keeps bookings where status is not 'closed' and deleted_at is null (excludes closed and deleted bookings).

[CT Ledger] Requires traded_at to be set and invoice_at to be null — so it excludes anything already invoiced.

[CT Ledger] Requires sell_currency_to_gbp_rate to be set (excludes bookings missing that exchange rate) and excludes accounts where skip_commission_calculations is true.

[CT Ledger] Returns distinct account ids as user_id, sorted ascending.

Summary: Merges two lists of user IDs per user: one from Pipedrive/Gold listing clients who have a last_traded date, and one from the CT Ledger listing accounts with not-yet-invoiced, traded bookings that pass commission filters; output columns are user_id, client, client_type.


System: CT

CT accounts

System: CT

System: PD

person ID

SELECT DISTINCT a.id AS user_id FROM public.accounts AS a JOIN public.trade_bookings AS tb ON tb.user_id = a.id WHERE tb.status = 'closed' ORDER BY 1 ASC LIMIT 10000

SELECT user_id FROM ct.client_360 WHERE COALESCE(account_deleted, FALSE) = FALSE AND COALESCE(has_deleted_booking, FALSE) = TRUE GROUP BY user_id ORDER BY user_id ASC LIMIT 10000

List every distinct CT accounts of any role whose account is not deleted but who have a deleted booking. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.


System: CT

CT accounts

System: CT

client

```json
{
  "sql": "",
  "explanation": "Cannot generate: the request references a prior 'first checked result' and a conversation-carried reading that are not present, and the federation context requires ct.client_360 and pipedrive.* tables which are not in the provided schema (all tables have no l

For exactly the CT accounts of any role with pre-billable bookings that qualify for the CT statistics filters in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


System: CT

CT accounts

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request depends on an undefined prior result ('first checked result') and requires tables/columns (e.g. ct.client_360) not present in the provided schema, so no query can be generated.",
  "confidence": "uncertain",
  "warnings": [
    "No schema columns

For exactly the CT accounts of any role whose account is not deleted but who have a deleted booking in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


System: CT

CT accounts

System: CT

SELECT a.id AS user_id FROM public.trade_bookings AS tb JOIN public.trade_details AS td ON td.trade_booking_id = tb.id JOIN public.accounts AS a ON a.id = tb.user_id WHERE (tb.status <> 'closed' AND tb.deleted_at IS NULL) AND NOT tb.traded_at IS NULL AND tb.invoice_at IS NULL AND NOT a.skip_commission_calculations IS TRUE AND NOT tb.sell_currency_to_gbp_rate IS NULL GROUP BY a.id ORDER BY 1 DESC NULLS LAST LIMIT 10000

SELECT user_id FROM ct.client_360 WHERE COALESCE(prebillable_commission, 0) > 0 ORDER BY user_id DESC LIMIT 10000

Show the same checked IDs for the CT accounts of any role with pre-billable bookings that qualify for the CT statistics filters from the first result, this time in descending user_id order. Keep every member and show only user_id.


System: CT

CT accounts

System: CT

```json
{
  "sql": "",
  "explanation": "The request depends on an unspecified prior result ('checked IDs', 'deleted booking from the first result') and references ct.client_360 / pipedrive tables that are not present in the provided schema (which lists only empty ct.* table stubs), so no query can

Show the same checked IDs for the CT accounts of any role whose account is not deleted but who have a deleted booking from the first result, this time in descending user_id order. Keep every member and show only user_id.


System: CT

CT accounts

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request depends on a prior 'third result' membership and the ct.client_360 / pipedrive.* federation sources, none of which are present in the provided schema (all tables list no columns), so a trustworthy query cannot be built.",
  "confidence": "uncertai

Keep the CT accounts of any role with pre-billable bookings that qualify for the CT statistics filters membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.


System: CT

CT accounts

System: CT

client

```json
{
  "sql": "",
  "explanation": "Cannot generate: the question depends on ct.trade_bookings / booking membership columns and deleted-account flags, but the federation gold leg restricts queries to ct.client_360 only, and no schema columns are available to identify deletion status or 'third r

```json
{
  "sql": "",
  "explanation": "The request depends on 'the third result' and 'deleted booking membership' concepts that do not exist in the CT-production schema (accounts has no deleted flag, and there is no booking-membership table).",
  "confidence": "uncertain",
  "warnings": [
    "No

Keep the CT accounts of any role whose account is not deleted but who have a deleted booking membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.


System: CT

CT accounts

GBP conversion rate for the sell leg. CT-report stats filter excludes trades where this IS NULL (commission cannot be converted to GBP).

System: CT

sell-currency-to-GBP rate

System: CT

System: PD

person ID

```json
{
  "sql": "",
  "explanation": "The request requires identifying accounts with a specific settled trade booking that lacks a sell-currency-to-GBP rate, but the gold-leg rule forbids referencing raw ct.* trade tables and no column in ct.client_360 exposing per-booking rate coverage is docume

List every distinct CT accounts of any role with a settled booking that has no sell-currency-to-GBP rate. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.


5 results — first client: Fictional Company 11

System: CT

CT accounts

CT realized commission in GBP — THE canonical CT revenue measure. SUM(commission) over trades whose trade_bookings.status='settled', grouped by trade_bookings.user_id. NEVER use settlement/sell/buy amount as revenue.

Join trade_booking_id -> trade_bookings.id, then GROUP BY trade_bookings.user_id. Realized GBP revenue = SUM(commission) where trade_bookings.status='settled'. Date realized-revenue windows on trade_bookings.completed_at (actual settlement date), NOT settlement_at (deadline) or traded_at (booking).

System: CT

commission

System: CT

System: PD

person ID

SELECT a.id AS user_id FROM public.accounts a JOIN public.trade_bookings tb ON tb.user_id = a.id JOIN public.trade_details td ON td.trade_booking_id = tb.id GROUP BY a.id HAVING SUM(td.commission) FILTER (WHERE tb.status = 'settled') < 0 ORDER BY 1

SELECT
  a.id AS user_id
FROM public.accounts AS a
JOIN public.trade_bookings AS tb
  ON tb.user_id = a.id
JOIN public.trade_details AS td
  ON td.trade_booking_id = tb.id
GROUP BY
  a.id
HAVING
  SUM(td.commission) FILTER(WHERE
    tb.status = 'settled') < 0
ORDER BY
  1

churn-tier-definitions settlement-is-ct-trade-lifecycle activation-definition-gold trade-existence-gold-booked

List every distinct CT accounts of any role whose sum of known realized commission is negative. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.

Start from the accounts table and attach trade bookings by matching each booking's user_id to the account's id, then attach trade details by matching each detail's trade_booking_id to the booking's id.

For each account, add up the commission from trade details, counting only rows whose booking status is 'settled'.

Keep only accounts where that sum is negative.

Return the account's id as user_id, sorted in ascending order.

Summary: List every distinct account ID that has at least one trade booking and trade detail, where the summed commission of settled bookings for that account is negative, sorted ascending by ID.


System: CT

CT accounts

System: CT

sell-currency-to-GBP rate

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request depends on a prior result ('first checked result') and a ct.client_360 view plus a sell-currency-to-GBP rate field that are not present in the provided schema, so no safe query can be generated.",
  "confidence": "uncertain",
  "warnings": ["Requi

For exactly the CT accounts of any role with a settled booking that has no sell-currency-to-GBP rate in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


System: CT

CT accounts

System: CT

sell-currency-to-GBP rate

System: CT

```json
{
  "sql": "",
  "explanation": "The request refers to 'the same checked IDs from the first result', which is not available in this conversation, and the provided schema lists table names without columns, so I cannot construct a valid query.",
  "confidence": "uncertain",
  "warnings": ["Ref

Show the same checked IDs for the CT accounts of any role with a settled booking that has no sell-currency-to-GBP rate from the first result, this time in descending user_id order. Keep every member and show only user_id.


5 clients have a negative total realized commission on settled trades

For exactly the CT accounts of any role whose sum ...

System: CT

CT accounts

System: CT

commission

System: CT

client

SELECT COUNT(*) AS client_count FROM (SELECT tb.user_id FROM public.trade_bookings AS tb JOIN public.trade_details AS td ON td.trade_booking_id = tb.id WHERE tb.status = 'settled' AND NOT tb.user_id IN (SELECT id FROM public.accounts WHERE id = 1 OR email ILIKE '%@currencytransfer.com') GROUP BY tb.user_id HAVING SUM(td.commission) < 0) AS negative_commission_clients

SELECT
  COUNT(*) AS client_count
FROM (
  SELECT
    tb.user_id
  FROM public.trade_bookings AS tb
  JOIN public.trade_details AS td
    ON td.trade_booking_id = tb.id
  WHERE
    tb.status = 'settled'
    AND NOT tb.user_id IN (
      SELECT
        id
      FROM public.accounts
      WHERE
        id = 1 OR email ILIKE '%@currencytransfer.com'
    )
  GROUP BY
    tb.user_id
  HAVING
    SUM(td.commission) < 0
) AS negative_commission_clients

Realized commission = sum of trade_details.commission on settled bookings only; non-settled trades excluded

Excludes CurrencyTransfer staff/internal accounts (id 1 and @currencytransfer.com email addresses)

List those 5 clients and their total commission

How negative is each client's commission in total?

Which trades drove the largest negative commission for these clients?

This counts clients whose summed commission across settled trades is below zero, i.e. net negative commission rather than a single losing trade.

With only one aggregate value there is no breakdown to gauge how negative these positions are.

For exactly the CT accounts of any role whose sum of known realized commission is negative in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.

Reads trades from trade_bookings joined to trade_details on the booking's id, keeping only trades with status 'settled'.

Excludes any user who is account id 1 or whose account email contains '@currencytransfer.com'.

Groups the trades by user and keeps only users whose summed commission across their settled trades is below zero.

Counts those users and reports the number as client_count — an empty set would yield zero.

Summary: Count the distinct users whose settled trades have a negative total commission, excluding the internal account (id 1) and any account with a currencytransfer.com email address.


System: CT

CT accounts

System: CT

sell-currency-to-GBP rate

System: CT

client

```json
{
  "sql": "",
  "explanation": "Cannot generate a valid query: the request depends on an unspecified prior result ('the third result'), references a rate-membership concept not present in the schema, and the provided tables expose no columns.",
  "confidence": "uncertain",
  "warnings": ["'

Keep the CT accounts of any role with a settled booking that has no sell-currency-to-GBP rate membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.


5 results — first client: Fictional Company 55

System: CT

CT accounts

System: CT

commission

System: CT

SELECT tb.user_id FROM public.trade_bookings AS tb JOIN public.trade_details AS td ON td.trade_booking_id = tb.id WHERE tb.status = 'settled' AND NOT tb.user_id IN (SELECT id FROM public.accounts WHERE id = 1 OR email ILIKE '%@currencytransfer.com') GROUP BY tb.user_id HAVING SUM(td.commission) < 0 ORDER BY tb.user_id DESC NULLS LAST

SELECT
  tb.user_id
FROM public.trade_bookings AS tb
JOIN public.trade_details AS td
  ON td.trade_booking_id = tb.id
WHERE
  tb.status = 'settled'
  AND NOT tb.user_id IN (
    SELECT
      id
    FROM public.accounts
    WHERE
      id = 1 OR email ILIKE '%@currencytransfer.com'
  )
GROUP BY
  tb.user_id
HAVING
  SUM(td.commission) < 0
ORDER BY
  tb.user_id DESC NULLS LAST

Show the same checked IDs for the CT accounts of any role whose sum of known realized commission is negative from the first result, this time in descending user_id order. Keep every member and show only user_id.

Reads trade_bookings joined to trade_details on trade_booking_id = booking id.

Keeps only bookings with status 'settled'.

Excludes users whose ID is 1 or whose account email contains '@currencytranslate.com' — here '@currencytransfer.com' — from the accounts table.

Groups rows by user and keeps only groups where the summed commission is negative.

Returns only user_id, ordered from highest to lowest, with any missing ID placed last.

Summary: From settled trade bookings, group by user, keep only users excluded from internal accounts whose total commission is negative, and list their IDs in descending order.


System: CT

CT accounts

System: CT

commission

System: CT

System: PD

person ID

```json
{
  "sql": "",
  "explanation": "The request requires raw trade-level commission data (trade_details.commission IS NULL for all of a user's bookings) but the gold-leg constraint forbids referencing anything other than ct.client_360 and pipedrive.*, which expose no commission-null signal.",

List every distinct CT accounts of any role with booking records, including closed and deleted records, whose commission inputs are all unknown. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.


System: CT

CT accounts

System: CT

commission

System: CT

client

```json
{
  "sql": "",
  "explanation": "The provided schema lists tables with no columns, and the question references 'commission inputs all unknown' and ct.client_360, none of which exist in the available schema, so no safe query can be generated.",
  "confidence": "uncertain",
  "warnings": ["Sch

For exactly the CT accounts of any role with booking records, including closed and deleted records, whose commission inputs are all unknown in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


5 distinct client accounts have a negative sum of known realized commission on settled trades.

Keep the CT accounts of any role whose sum of know...

System: CT

CT accounts

System: CT

commission

System: CT

client

Medium confidence (58%) — implicit time period, complex query

SELECT COUNT(*) AS client_count FROM (SELECT tb.user_id FROM public.trade_bookings AS tb JOIN public.trade_details AS td ON td.trade_booking_id = tb.id JOIN public.accounts AS a ON a.id = tb.user_id WHERE tb.status = 'settled' AND NOT tb.user_id IN (SELECT id FROM public.accounts WHERE id = 1 OR email ILIKE '%@currencytransfer.com') GROUP BY tb.user_id HAVING SUM(td.commission) < 0) AS negative_commission_users

SELECT
  COUNT(*) AS client_count
FROM (
  SELECT
    tb.user_id
  FROM public.trade_bookings AS tb
  JOIN public.trade_details AS td
    ON td.trade_booking_id = tb.id
  JOIN public.accounts AS a
    ON a.id = tb.user_id
  WHERE
    tb.status = 'settled'
    AND NOT tb.user_id IN (
      SELECT
        id
      FROM public.accounts
      WHERE
        id = 1 OR email ILIKE '%@currencytransfer.com'
    )
  GROUP BY
    tb.user_id
  HAVING
    SUM(td.commission) < 0
) AS negative_commission_users

Realized commission taken as SUM of td.commission over settled trade bookings only.

Excludes the account with id 1 and any accounts with an email matching '%@currencytransfer.com' (internal CurrencyTransfer accounts).

List those 5 client accounts with their total commission and trade counts.

Which individual settled trades drove the negative commission for these clients?

This counts accounts, not individual trades — the negativity is the net across each account's settled trade bookings.

Keep the CT accounts of any role whose sum of known realized commission is negative membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.

Read trade_bookings joined to trade_details on the booking ID, and joined to accounts on the booking's user ID.

Keep only bookings with status 'settled'.

Exclude any user whose account ID is 1 or whose email contains '@currencytransfer.com'.

Group the remaining bookings by user ID.

Keep only users whose summed commission across their settled bookings is below zero.

Count those users — the result is a single number called client_count, zero if none qualify.

Summary: Count how many distinct user IDs have settled trade bookings whose total commission across those bookings is negative, excluding internal CurrencyTransfer accounts.


System: CT

CT accounts

System: CT

commission

System: CT

```json
{
  "sql": "",
  "explanation": "The request depends on a prior 'first result' (checked IDs) that is not available in this conversation, and it requires columns from ct.client_360 / pipedrive tables that are not present in the provided schema, so a correct query cannot be generated.",
  "con

Show the same checked IDs for the CT accounts of any role with booking records, including closed and deleted records, whose commission inputs are all unknown from the first result, this time in descending user_id order. Keep every member and show only user_id.


System: CT

CT accounts

System: CT

commission

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request is too ambiguous to translate: 'commission inputs are all unknown membership from the third result' refers to an undefined prior result and an unclear membership condition, so no reliable CT-leg query can be generated.",
  "confidence": "uncertain

```json
{
  "sql": "",
  "explanation": "The request requires ct.client_360 and pipedrive.* tables plus commission fields, but the provided schema lists no columns for any table and does not include ct.client_360 or pipedrive tables, so no query can be confidently generated.",
  "confidence": "uncer

Keep the CT accounts of any role with booking records, including closed and deleted records, whose commission inputs are all unknown membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.


8 results — first client: Fictional Company 7

List every distinct CT accounts of any role with a...

System: CT

CT accounts

System: CT

commission

System: CT

System: PD

person ID

SELECT tb.user_id AS user_id FROM public.trade_bookings AS tb JOIN public.trade_details AS td ON td.trade_booking_id = tb.id JOIN public.accounts AS a ON a.id = tb.user_id WHERE ((tb.status <> 'closed' AND tb.deleted_at IS NULL) AND NOT a.skip_commission_calculations IS TRUE AND NOT tb.sell_currency_to_gbp_rate IS NULL AND NOT td.commission IS NULL) AND NOT tb.user_id IN (SELECT id FROM public.accounts WHERE id = 1 OR email ILIKE '%@currencytransfer.com') GROUP BY tb.user_id HAVING SUM(td.commission) = 0 ORDER BY tb.user_id

SELECT
  tb.user_id AS user_id
FROM public.trade_bookings AS tb
JOIN public.trade_details AS td
  ON td.trade_booking_id = tb.id
JOIN public.accounts AS a
  ON a.id = tb.user_id
WHERE
  (
    (
      tb.status <> 'closed' AND tb.deleted_at IS NULL
    )
    AND NOT a.skip_commission_calculations IS TRUE
    AND NOT tb.sell_currency_to_gbp_rate IS NULL
    AND NOT td.commission IS NULL
  )
  AND NOT tb.user_id IN (
    SELECT
      id
    FROM public.accounts
    WHERE
      id = 1 OR email ILIKE '%@currencytransfer.com'
  )
GROUP BY
  tb.user_id
HAVING
  SUM(td.commission) = 0
ORDER BY
  tb.user_id

List every distinct CT accounts of any role with at least one known booked commission input and a booked commission total of exactly zero. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.

Reads trade_bookings joined to trade_details on trade_booking_id = id, then joined to accounts on accounts.id = trade_bookings.user_id.

Keeps only bookings that are not 'closed' and have no deleted_at value (not deleted).

Requires the account not to have skip_commission_calculations set to true, the sell_currency_to_gbp_rate to be filled in, and the commission on each detail row to be filled in.

Excludes any user_id that appears in a list of internal accounts: the account with id = 1 or any account whose email ends in '@currencytransfer.com' (case-insensitive).

Groups rows by user_id and keeps only groups where the sum of td.commission is exactly zero.

Returns just user_id, sorted in ascending order.

Summary: Finds each distinct user_id whose trade bookings, after all filters, have commissions that sum to exactly zero, listing the IDs in ascending order.


System: CT

CT accounts

When the trade completed/settled. Date column for the realized (settled) commission reading.

System: CT

completion date

The client's settlement DEADLINE (the must-settle-by date so the payment firm honours delivery) — NOT when revenue is realized. It is populated even on trades that have not settled yet (e.g. awaiting_funds). Do NOT date realized/settled money on this; use completed_at.

System: CT

settlement deadline

System: CT

System: PD

person ID

Simple single-table query with basic aggregation

SELECT user_id FROM ct.client_360 WHERE NOT user_id IS NULL ORDER BY 1 LIMIT 10000

SELECT DISTINCT tb.user_id AS user_id FROM public.trade_bookings AS tb WHERE tb.status = 'settled' AND NOT tb.completed_at IS NULL AND NOT tb.settlement_at IS NULL AND CAST(((tb.completed_at AT TIME ZONE 'UTC') AT TIME ZONE 'Europe/London') AS DATE) <> CAST(((tb.settlement_at AT TIME ZONE 'UTC') AT TIME ZONE 'Europe/London') AS DATE) ORDER BY 1 LIMIT 10000

List every distinct CT accounts of any role with a settled booking whose actual completion date differs from its settlement deadline date in Europe/London, treating raw timestamps as UTC. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.

[Gold / Pipedrive] Reads ct.client_360 and returns user_id for every row where user_id is not missing, ordered ascending, capped at 10,000 rows.

[CT Ledger] Reads public.trade_bookings and keeps only rows with status = 'settled' where both completed_at and settlement_at are filled in.

[CT Ledger] Converts completed_at and settlement_at from UTC to Europe/London time and keeps only rows where the two calendar dates differ.

[CT Ledger] Returns the distinct matching user_id values, ordered ascending, capped at 10,000 rows.

[Merged] The two lists are joined per user_id, and the merged answer returns user_id along with client and client_type.

Summary: Two sources merged per user: Pipedrive provides a list of client IDs, and the CT Ledger provides IDs of users with settled bookings whose completion date and settlement date differ when converted from UTC to Europe/London; only user_id is returned in ascending order.


System: CT

CT accounts

System: CT

completion date

System: CT

settlement deadline

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request cannot be satisfied: the required settlement fields (trade_details.status, completed_at, settlement_at) live in raw ct.trade_details, but the federation gold leg forbids any raw ct.* table except ct.client_360, whose column list is not provided, s

For exactly the CT accounts of any role with a settled booking whose actual completion date differs from its settlement deadline date in Europe/London, treating raw timestamps as UTC in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


8 non-internal accounts have non-null booked commission inputs but a booked commission total of exactly zero.

For exactly the CT accounts of any role with at le...

System: CT

CT accounts

System: CT

commission

System: CT

client

SELECT COUNT(*) AS client_count FROM (SELECT tb.user_id FROM public.trade_bookings AS tb JOIN public.trade_details AS td ON td.trade_booking_id = tb.id JOIN public.accounts AS a ON a.id = tb.user_id WHERE ((tb.status <> 'closed' AND tb.deleted_at IS NULL) AND NOT a.skip_commission_calculations IS TRUE AND NOT tb.sell_currency_to_gbp_rate IS NULL AND NOT td.commission IS NULL) AND NOT tb.user_id IN (SELECT id FROM public.accounts WHERE id = 1 OR email ILIKE '%@currencytransfer.com') GROUP BY tb.user_id HAVING SUM(td.commission) = 0) AS z

SELECT
  COUNT(*) AS client_count
FROM (
  SELECT
    tb.user_id
  FROM public.trade_bookings AS tb
  JOIN public.trade_details AS td
    ON td.trade_booking_id = tb.id
  JOIN public.accounts AS a
    ON a.id = tb.user_id
  WHERE
    (
      (
        tb.status <> 'closed' AND tb.deleted_at IS NULL
      )
      AND NOT a.skip_commission_calculations IS TRUE
      AND NOT tb.sell_currency_to_gbp_rate IS NULL
      AND NOT td.commission IS NULL
    )
    AND NOT tb.user_id IN (
      SELECT
        id
      FROM public.accounts
      WHERE
        id = 1 OR email ILIKE '%@currencytransfer.com'
    )
  GROUP BY
    tb.user_id
  HAVING
    SUM(td.commission) = 0
) AS z

Excludes CT internal accounts (account id 1 and any email containing @currencytransfer.com).

Qualifying bookings are non-closed, non-deleted trades with a sell-to-GBP conversion rate present and commission recorded; accounts flagged skip_commission_calculations are excluded.

Which 8 clients are these — list their names and zero-net commission booking details?

For these clients, what is the total notional traded on the zero-commission bookings?

Do any of these 8 clients also hold bookings with non-zero commission in the same period?

These are accounts with at least one qualifying trade booking where commission was recorded, yet the values net to zero — worth distinguishing from accounts with no commission inputs at all.

All figures count accounts, not trades; an account appears once regardless of how many zero-net bookings it has.

For exactly the CT accounts of any role with at least one known booked commission input and a booked commission total of exactly zero in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.

Reads trade_bookings joined to trade_details on trade_booking_id and to accounts on the booking's user_id.

Keeps bookings where status is not 'closed', deleted_at is empty, the GBP conversion rate and the commission are both present, and the account's skip_commission_calculations flag is not true.

Excludes any user whose account id is 1 or whose email contains '@currencytranslate.com' style domain match — specifically excludes ids in the subquery where id = 1 OR email contains '@currencytransfer.com'.

Groups rows per user and keeps only users whose commissions add up to exactly zero.

Counts those distinct users and returns the number as client_count; if none qualify, the count is zero.

Summary: Counts clients whose CT trade bookings all have non-null commissions but those commissions sum to exactly zero, after keeping only active, non-deleted, non-closed bookings on accounts not excluded from commission calculations.


System: CT

CT accounts

System: CT

completion date

System: CT

settlement deadline

System: CT

```json
{
  "sql": "",
  "explanation": "The request requires comparing a settled trade's actual completion date against its settlement deadline date, but no such settlement-deadline/completion columns are documented in the provided schema (table column lists are empty and the curated knowledge for

Show the same checked IDs for the CT accounts of any role with a settled booking whose actual completion date differs from its settlement deadline date in Europe/London, treating raw timestamps as UTC from the first result, this time in descending user_id order. Keep every member and show only user_id.


8 results — first client: Fictional Company 56

System: CT

CT accounts

System: CT

commission

System: CT

SELECT a.id AS user_id FROM public.accounts AS a WHERE NOT a.skip_commission_calculations IS TRUE AND EXISTS(SELECT 1 FROM public.trade_bookings AS tb JOIN public.trade_details AS td ON td.trade_booking_id = tb.id WHERE tb.user_id = a.id AND (tb.status <> 'closed' AND tb.deleted_at IS NULL) AND NOT tb.sell_currency_to_gbp_rate IS NULL AND NOT td.commission IS NULL) AND 0 = (SELECT COALESCE(SUM(td.commission), 0) FROM public.trade_bookings AS tb JOIN public.trade_details AS td ON td.trade_booking_id = tb.id WHERE tb.user_id = a.id AND tb.status <> 'closed' AND NOT tb.sell_currency_to_gbp_rate IS NULL) ORDER BY a.id DESC NULLS LAST

SELECT
  a.id AS user_id
FROM public.accounts AS a
WHERE
  NOT a.skip_commission_calculations IS TRUE
  AND EXISTS(
    SELECT
      1
    FROM public.trade_bookings AS tb
    JOIN public.trade_details AS td
      ON td.trade_booking_id = tb.id
    WHERE
      tb.user_id = a.id
      AND (
        tb.status <> 'closed' AND tb.deleted_at IS NULL
      )
      AND NOT tb.sell_currency_to_gbp_rate IS NULL
      AND NOT td.commission IS NULL
  )
  AND 0 = (
    SELECT
      COALESCE(SUM(td.commission), 0)
    FROM public.trade_bookings AS tb
    JOIN public.trade_details AS td
      ON td.trade_booking_id = tb.id
    WHERE
      tb.user_id = a.id
      AND tb.status <> 'closed'
      AND NOT tb.sell_currency_to_gbp_rate IS NULL
  )
ORDER BY
  a.id DESC NULLS LAST

Show the same checked IDs for the CT accounts of any role with at least one known booked commission input and a booked commission total of exactly zero from the first result, this time in descending user_id order. Keep every member and show only user_id.

Reads the accounts table and returns only the id column, renamed user_id, ordered from highest to lowest id with empty ids last.

Keeps only accounts where skip_commission_calculations is not set to true.

Requires at least one match: a trade booking belonging to that account, joined to its trade details, where the booking isn't 'closed', has no deletion timestamp, has a sell-to-GBP exchange rate present, and the detail's…

Also requires that the sum of commission over that account's bookings (again excluding 'closed' ones and ones missing the exchange rate) equals exactly zero, treating missing values as zero in the sum.

Summary: Lists account IDs that have at least one commission detail row and whose total commission across open bookings is exactly zero, sorted by ID descending.


System: CT

CT accounts

System: CT

completion date

System: CT

settlement deadline

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request requires comparing trade settlement dates (trade_details.status/completed_at/settlement_at), but the federation leg forbids referencing any raw ct.* table other than ct.client_360, which is not present in the provided schema, so no compliant query

Keep the CT accounts of any role with a settled booking whose actual completion date differs from its settlement deadline date in Europe/London, treating raw timestamps as UTC membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.


8 clients have at least one booked commission input yet a booked commission total of exactly zero.

Keep the CT accounts of any role with at least one...

System: CT

CT accounts

System: CT

commission

System: CT

client

SELECT COUNT(DISTINCT a2.id) AS client_count FROM public.accounts AS a2 WHERE a2.id IN (SELECT a.id FROM public.accounts AS a WHERE NOT a.skip_commission_calculations IS TRUE AND EXISTS(SELECT 1 FROM public.trade_bookings AS tb JOIN public.trade_details AS td ON td.trade_booking_id = tb.id WHERE tb.user_id = a.id AND (tb.status <> 'closed' AND tb.deleted_at IS NULL) AND NOT tb.sell_currency_to_gbp_rate IS NULL AND NOT td.commission IS NULL) AND 0 = (SELECT COALESCE(SUM(td.commission), 0) FROM public.trade_bookings AS tb JOIN public.trade_details AS td ON td.trade_booking_id = tb.id WHERE tb.user_id = a.id AND tb.status <> 'closed' AND NOT tb.sell_currency_to_gbp_rate IS NULL))

SELECT
  COUNT(DISTINCT a2.id) AS client_count
FROM public.accounts AS a2
WHERE
  a2.id IN (
    SELECT
      a.id
    FROM public.accounts AS a
    WHERE
      NOT a.skip_commission_calculations IS TRUE
      AND EXISTS(
        SELECT
          1
        FROM public.trade_bookings AS tb
        JOIN public.trade_details AS td
          ON td.trade_booking_id = tb.id
        WHERE
          tb.user_id = a.id
          AND (
            tb.status <> 'closed' AND tb.deleted_at IS NULL
          )
          AND NOT tb.sell_currency_to_gbp_rate IS NULL
          AND NOT td.commission IS NULL
      )
      AND 0 = (
        SELECT
          COALESCE(SUM(td.commission), 0)
        FROM public.trade_bookings AS tb
        JOIN public.trade_details AS td
          ON td.trade_booking_id = tb.id
        WHERE
          tb.user_id = a.id
          AND tb.status <> 'closed'
          AND NOT tb.sell_currency_to_gbp_rate IS NULL
      )
  )

Counts non-closed trades only (excluding closed trades), including those deleted_at is set on.

Booked commission input means a trade with a non-null sell-to-GBP rate and a non-null commission line.

List the 8 client accounts with their commission totals and trade counts.

How much gross commission sits on those 8 clients' non-closed trades?

This covers accounts not flagged to skip commission calculations, so any exclusion policy on that flag is respected.

The zero-total check treats null commissions as no contribution via COALESCE, and includes non-closed trades only.

Keep the CT accounts of any role with at least one known booked commission input and a booked commission total of exactly zero membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.

From the accounts table, keep accounts where skip_commission_calculations is not set to TRUE (rows where it's FALSE or NULL are kept).

Require at least one matching row in trade_bookings joined to trade_details on trade_booking_id where the booking's user_id is the account, status is not 'closed', deleted_at is NULL, sell_currency_to_gbp_rate is not NU…

Also require that the sum of commission over that account's non-closed bookings with a known sell_currency_to_gbp_rate equals exactly zero; NULL sums are treated as 0, so accounts with no such bookings also count.

Count the distinct account IDs meeting all conditions and report that number as client_count; if none match, the count is zero.

Summary: Count distinct account IDs that have at least one non-closed booking with a known commission and FX rate, yet whose total commission across such bookings is exactly zero.


System: CT

CT accounts

System: CT

broker

System: CT

System: PD

person ID

```json
{
  "sql": "",
  "explanation": "The question requires comparing first non-deleted/non-closed booking timestamps against first broker verification dates via ct.client_360, but the provided schema lists no columns for any table, so the required fields cannot be identified.",
  "confidence": "

List every distinct CT accounts of any role whose first non-deleted, non-closed booking predates their first broker verification. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.


System: CT

accounts

System: CT

System: PD

person ID

SELECT a.id AS user_id FROM public.accounts AS a JOIN public.clients AS c ON c.user_id = a.id WHERE a.role = 'User' AND NOT a.skip_commission_calculations IS TRUE AND DATE_TRUNC('MONTH', (a.created_at AT TIME ZONE 'UTC') AT TIME ZONE 'Europe/London') = CAST('2026-09-01' AS DATE) ORDER BY 1 LIMIT 10000

SELECT user_id FROM (SELECT c.user_id FROM ct.client_360 AS c WHERE c.created_at >= CAST('2026-09-01 00:00:00+00' AS TIMESTAMPTZ) AND c.created_at < CAST('2026-10-01 00:00:00+00' AS TIMESTAMPTZ) AND COALESCE(c.is_ordinary_user, TRUE) UNION SELECT p.id AS user_id FROM pipedrive.persons_enriched AS p WHERE p.add_time >= CAST('2026-09-01 00:00:00+00' AS TIMESTAMPTZ) AND p.add_time < CAST('2026-10-01 00:00:00+00' AS TIMESTAMPTZ) AND NOT EXISTS(SELECT 1 FROM ct.client_360 AS c2 WHERE c2.user_id = p.id)) AS u GROUP BY user_id ORDER BY user_id ASC LIMIT 10000

churn-tier-definitions activation-definition-gold trade-existence-gold-booked calendar-window-defaults

List every distinct ordinary CT user accounts created during September 2026 in Europe/London, interpreting raw timestamps as UTC. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.


System: CT

accounts

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request requires tables (ct.client_360, pipedrive.*) and columns (user_id, account creation timestamps) that are not present in the provided schema, so no valid SELECT can be generated.",
  "confidence": "uncertain",
  "warnings": ["No columns are defined

For exactly the ordinary CT user accounts created during September 2026 in Europe/London, interpreting raw timestamps as UTC in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


System: CT

CT accounts

System: CT

broker

System: CT

client

```json
{
  "sql": "",
  "explanation": "Cannot generate: the request requires ct.client_360 and pipedrive.* tables, but no columns exist in the provided schema for any table, so the required fields cannot be resolved.",
  "confidence": "uncertain",
  "warnings": ["Schema lists table names with no c

For exactly the CT accounts of any role whose first non-deleted, non-closed booking predates their first broker verification in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


System: CT

CT accounts

System: CT

broker

System: CT

```json
{
  "sql": "",
  "explanation": "Cannot generate: the referenced tables (ct.client_360, pipedrive.*, trade booking/verification columns) have no columns in the provided schema, and the 'same checked IDs from the first result' prior query is unavailable.",
  "confidence": "uncertain",
  "warn

Show the same checked IDs for the CT accounts of any role whose first non-deleted, non-closed booking predates their first broker verification from the first result, this time in descending user_id order. Keep every member and show only user_id.


4 results — first client: Fictional Company 59

Show the same checked IDs for the ordinary CT user...

System: CT

accounts

System: CT

Time clarity

Explicit time period specified: 'september'

High confidence (85%) — clear time period, moderate complexity

SELECT user_id FROM ct.client_360 WHERE created_at >= CAST('2026-09-01 00:00:00+00' AS TIMESTAMPTZ) AND created_at < CAST('2026-10-01 00:00:00+00' AS TIMESTAMPTZ) GROUP BY user_id ORDER BY user_id DESC LIMIT 10000

SELECT a.id AS user_id FROM public.accounts AS a JOIN public.clients AS c ON c.user_id = a.id WHERE a.role = 'User' AND NOT a.skip_commission_calculations IS TRUE AND DATE_TRUNC('MONTH', (a.created_at AT TIME ZONE 'UTC') AT TIME ZONE 'Europe/London') = CAST('2026-09-01' AS DATE) ORDER BY user_id DESC NULLS LAST LIMIT 10000

Show the same checked IDs for the ordinary CT user accounts created during September 2026 in Europe/London, interpreting raw timestamps as UTC from the first result, this time in descending user_id order. Keep every member and show only user_id.

[Gold / Pipedrive] Reads ct.client_360 and keeps rows whose created_at falls on or after 1 September 2026 00:00 UTC and before 1 October 2026 00:00 UTC.

[Gold / Pipedrive] Groups by user_id (so each ID appears once), orders them from largest to smallest, and caps the list at 10,000 rows.

[CT Ledger] Reads public.accounts joined to public.clients by matching clients.user_id to accounts.id, keeping only accounts that have at least one matching client row.

[CT Ledger] Keeps only rows where role = 'User' and where skip_commission_calculations is not set to true (rows where it's false or null are kept).

[CT Ledger] Takes created_at, treats it as UTC, converts it to the Europe/London clock, truncates to the calendar month, and keeps only rows where that month equals 1 September 2026.

[CT Ledger] Orders user_id from largest to smallest (nulls last) and caps the list at 10,000 rows.

Summary: The answer combines two lists of user IDs for accounts created in September 2026: the Gold/Pipedrive source picks IDs from client_360 by creation timestamp in UTC, and the CT Ledger source picks account IDs whose London-calendar-month creation date is September 2026, filtered to ordinary user accounts; the two halves…


System: CT

CT accounts

System: CT

broker

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request references a 'third result' from a prior multi-step query chain and tables (ct.client_360, pipedrive.*) that are not present in the provided schema, so no valid SELECT can be generated.",
  "confidence": "uncertain",
  "warnings": [
    "Schema li

Keep the CT accounts of any role whose first non-deleted, non-closed booking predates their first broker verification membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.


System: CT

accounts

System: CT

client

```json
{
  "sql": "",
  "explanation": "The request requires tables (ct.client_360, pipedrive.*) and columns that are not present in the provided schema, so no valid SELECT can be generated.",
  "confidence": "uncertain",
  "warnings": ["Referenced tables ct.client_360 and pipedrive.* do not exist

Keep the ordinary CT user accounts created during September 2026 in Europe/London, interpreting raw timestamps as UTC membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.


List every distinct CT client records referred by ...

System: CT

customer

System: CT

referrer

System: CT

System: PD

person ID

SELECT DISTINCT a.id AS user_id FROM public.accounts AS a JOIN public.accounts AS ref ON ref.id = a.affiliate_id JOIN public.reward_events AS re ON re.user_id = a.affiliate_id AND re.referred_user_id = a.id WHERE ref.role = 'User' ORDER BY 1 LIMIT 10000

churn-tier-definitions declared-currency-intent activation-definition-gold client-type-sti-classes trade-existence-gold-booked

List every distinct CT client records referred by a customer account where that referrer has a reward event for the same client. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.


32 results — first client: Fictional Company 2

System: CT

client

Matview over public.affiliate_details. AFFILIATE-keyed dimension (keyed by affiliate_id), NOT a per-user/client fact table. It bridges to a client via client.affiliate_id = affiliate_details.affiliate_id, where client.affiliate_id -> accounts.id of the referrer (NOT the account_id bridge). One affiliate maps to many clients, so it CANNOT merge on the federation user_id; route it as an affiliate-dimension lookup (fail-safe), never fanned out or summed per user, until a hand-tuned attribution bridge exists. Refer-and-earn referrers are accounts.role='User' (accounts.role values include User 89179, Affiliate 442, Partner 50, AffiliateManager 11); commission_rate > 0 marks a professional affiliate. SECURITY: bank/PII columns (iban, account_number, sort_code, bic_swift, aba, bsb, address, bank_account_country) are never exposed in a CT federation leg.

System: CT

professional affiliate

Affiliate commission rate; commission_rate > 0 marks a professional affiliate.

System: CT

commission rate

System: CT

System: PD

person ID

SELECT DISTINCT a.id AS user_id FROM public.accounts AS a JOIN public.accounts AS referrer ON referrer.id = a.affiliate_id WHERE NOT a.affiliate_id IS NULL AND referrer.role IN ('Affiliate', 'AffiliateManager', 'Partner') ORDER BY 1 LIMIT 10000

refer-and-earn-earnings-disambiguation affiliate-cohort-designator settlement-is-ct-trade-lifecycle churn-tier-definitions declared-currency-intent activation-definition-gold client-type-sti-classes trade-existence-gold-booked

List every distinct CT client records referred by a professional affiliate whose commission rate is zero. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.

Reads the public.accounts table twice: once as the client records (a) and once as the referrer (referrer).

Joins each account to its referrer by matching the referrer's id to the account's affiliate_id column.

Keeps only accounts where affiliate_id is not NULL — records with no referrer are excluded.

Keeps only rows where the referrer's role is 'Affiliate', 'AffiliateManager', or 'Partner'.

Returns each matching id once (duplicates removed), labeled user_id, sorted in ascending order, capped at 10,000 rows.

Summary: From the accounts table, list distinct account IDs that have a referrer account whose role is Affiliate, AffiliateManager, or Partner, sorted ascending.


No CT client records match the referral-and-reward-event criteria, so client_count is 0.

For exactly the CT client records referred by a cu...

System: CT

customer

System: CT

referrer

SELECT COUNT(DISTINCT a.id) AS client_count FROM public.accounts AS a JOIN public.accounts AS ref ON ref.id = a.affiliate_id JOIN public.reward_events AS re ON re.user_id = a.affiliate_id AND re.referred_user_id = a.id WHERE ref.role = 'User'

A referrer counts only when its account role is exactly 'User' — staff, admin or other roles are excluded.

A qualifying referral requires a reward event on the referrer naming that same client as the referred user.

Re-derived the cohort from your previous question — the exact set from that answer was not available to carry.

How many CT client records have an affiliate referrer with role 'User' regardless of whether a reward event exists?

The zero reflects no rows satisfying the join between accounts, referrers with role 'User', and matching reward events — not an absence of data in the underlying tables.

If client records were expected here, the most likely gap is a missing reward event linking the referrer to that specific referred client (referred_user_id must equal the client's account id).

For exactly the CT client records referred by a customer account where that referrer has a reward event for the same client in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.

From the accounts table (a), join each account to its referrer account (ref) by matching ref.id = a.affiliate_id.

Join reward_events (re) where the event's user_id equals the referrer's id and the event's referred_user_id equals the client's id.

Keep only rows where the referrer's role is exactly 'User'.

Return the count of distinct client ids as client_count.

Summary: Count the distinct client accounts whose referrer is a 'User' account and has a matching reward event for that same client.


32 distinct client records are counted as referred by professional affiliates, per the SQL as executed.

For exactly the CT client records referred by a pr...

System: CT

client

System: CT

professional affiliate

System: CT

commission rate

SELECT COUNT(DISTINCT a.id) AS client_count FROM public.accounts a JOIN public.accounts referrer ON referrer.id = a.affiliate_id WHERE a.affiliate_id IS NOT NULL AND referrer.role IN ('Affiliate','AffiliateManager','Partner')

SELECT
  COUNT(DISTINCT a.id) AS client_count
FROM public.accounts AS a
JOIN public.accounts AS referrer
  ON referrer.id = a.affiliate_id
WHERE
  NOT a.affiliate_id IS NULL
  AND referrer.role IN ('Affiliate', 'AffiliateManager', 'Partner')

client_count = all referred accounts with referrer roles Affiliate, AffiliateManager or Partner — no CT-type or zero-commission-rate filter was applied

commission rate was not checked in this query, so referrers may include non-zero-rate affiliates

Assuming "revenue" = booked trading revenue (commission on all non-cancelled trades) — includes open/forward trades not yet settled — say 'settled', 'realized', or 'billable' to narrow.

List the 32 referred client records with their referrer name and commission rate so the zero-commission membership can be verified

How many of these 32 clients are CT type specifically?

The SQL does not filter for CT client records or for zero commission rates — it counts every distinct referred account whose referrer role is Affiliate, AffiliateManager or Partner, so 32 may be broader than the membership described in the question.

The WHERE clause only requires a non-null referrer; there is no check on the referrer's commission rate, so whether the 'zero commission' condition holds is unverified here.

refer-and-earn-earnings-disambiguation affiliate-cohort-designator settlement-is-ct-trade-lifecycle declared-currency-intent client-type-sti-classes

For exactly the CT client records referred by a professional affiliate whose commission rate is zero in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.

Reads the accounts table twice: once as the client records (a) and once as their referrer (referrer), matching referrer.id to each client's affiliate_id (an inner join, so clients without a matching referrer are dropped…

Keeps only clients whose affiliate_id is filled in — clients with no referrer attached are excluded.

Keeps only clients whose referrer's role is 'Affiliate', 'AffiliateManager', or 'Partner' — any other role is excluded.

Counts the distinct client ids among the rows that pass both filters and reports that number as client_count (the count is naturally zero if no rows qualify).

Summary: Counts the distinct client records that have a referrer attached, where that referrer's role is Affiliate, AffiliateManager, or Partner.


System: CT

customer

System: CT

referrer

System: CT

SELECT DISTINCT a.id AS user_id FROM public.accounts AS a JOIN public.accounts AS ref ON ref.id = a.affiliate_id JOIN public.reward_events AS re ON re.user_id = a.affiliate_id AND re.referred_user_id = a.id WHERE ref.role = 'User' ORDER BY 1 DESC NULLS LAST LIMIT 10000

Show the same checked IDs for the CT client records referred by a customer account where that referrer has a reward event for the same client from the first result, this time in descending user_id order. Keep every member and show only user_id.


No CT clients referred by a customer account have a matching reward event — client_count is 0.

Keep the CT client records referred by a customer ...

System: CT

customer

System: CT

referrer

Referrer is defined as the account in the affiliate_id field with role = 'User' (customer account), not staff or other roles.

A matching reward event requires the same referrer and referred client pairing in both the accounts join and reward_events.

How many CT clients were referred by customer accounts regardless of reward events?

Which referrer–client pairs have reward events where the referrer's role is not 'User'?

With a single-row result of zero, the joins found no overlap between customer-account referrals and reward events for the same referred client.

Keep the CT client records referred by a customer account where that referrer has a reward event for the same client membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.

Reads from public.accounts twice: once as 'a' (the client record) and once as 'ref' (the account whose id matches a's affiliate_id).

Joins public.reward_events where the event's user_id equals a.affiliate_id and its referred_user_id equals a.id, so only records with a matching reward event for that same referrer-client pair survive.

Filters to referrer accounts whose role is exactly 'User'.

Counts the distinct a.id values as client_count; no matching rows means the count is zero.

Summary: Count distinct account IDs whose referrer account has role 'User' and has a reward event linking that referrer to that account as the referred user.


32 results — first client: Fictional Company 62

System: CT

client

System: CT

professional affiliate

System: CT

commission rate

System: CT

SELECT DISTINCT a.id AS user_id FROM public.accounts AS a JOIN public.accounts AS referrer ON referrer.id = a.affiliate_id WHERE NOT a.affiliate_id IS NULL AND referrer.role IN ('Affiliate', 'AffiliateManager', 'Partner') ORDER BY 1 DESC NULLS LAST LIMIT 10000

Show the same checked IDs for the CT client records referred by a professional affiliate whose commission rate is zero from the first result, this time in descending user_id order. Keep every member and show only user_id.

Reads the accounts table twice: once as 'a' (the referred account) and once as 'referrer' (matched by a.affiliate_id = referrer.id).

Keeps only rows where a.affiliate_id is not NULL, i.e. accounts that actually have a referrer.

Keeps only rows where the referrer's role is one of 'Affiliate', 'AffiliateManager', or 'Partner'.

Returns each matching ID once (removes duplicates), sorted from highest to lowest, capped at 10,000 rows.

Summary: List the distinct account IDs that were referred by another account with an affiliate-type role, sorted by ID from highest to lowest.


3 results — first client: Fictional Partner 2

List every distinct professional CT partner accoun...

System: CT

partner

System: CT

accounts

System: CT

System: PD

person ID

SELECT s.affiliate_id AS user_id FROM public.affiliate_commission_statements s JOIN public.accounts a ON a.id = s.affiliate_id WHERE a.role IN ('Affiliate','AffiliateManager','Partner') GROUP BY s.affiliate_id HAVING COUNT(*) FILTER (WHERE s.paid_at IS NOT NULL) > 0 AND COUNT(*) FILTER (WHERE s.paid_at IS NULL) > 0 ORDER BY 1

SELECT
  s.affiliate_id AS user_id
FROM public.affiliate_commission_statements AS s
JOIN public.accounts AS a
  ON a.id = s.affiliate_id
WHERE
  a.role IN ('Affiliate', 'AffiliateManager', 'Partner')
GROUP BY
  s.affiliate_id
HAVING
  COUNT(*) FILTER(WHERE
    NOT s.paid_at IS NULL) > 0
  AND COUNT(*) FILTER(WHERE
    s.paid_at IS NULL) > 0
ORDER BY
  1

refer-and-earn-earnings-disambiguation affiliate-cohort-designator settlement-is-ct-trade-lifecycle churn-tier-definitions activation-definition-gold trade-existence-gold-booked calendar-window-defaults

List every distinct professional CT partner accounts with both paid and unpaid monthly affiliate statements. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.

Reads rows from the affiliate_commission_statements table, calling the affiliate_id column user_id.

Joins each statement to the accounts table by matching accounts.id to the statement's affiliate_id, so only affiliates that exist as accounts are kept.

Keeps only accounts whose role is exactly 'Affiliate', 'AffiliateManager', or 'Partner'; any other role is excluded.

Groups the rows by affiliate so each affiliate appears once.

Keeps only affiliates that have at least one statement where paid_at is filled in (a paid statement) and at least one where paid_at is empty (an unpaid statement).

Sorts the resulting user_id values in ascending order.

Summary: Finds each affiliate that has at least one paid and at least one unpaid commission statement, and lists their affiliate IDs in ascending order.


3 distinct affiliates have both paid and unpaid monthly statements among the checked professional CT partner accounts.

For exactly the professional CT partner accounts w...

System: CT

partner

System: CT

accounts

System: CT

client

SELECT COUNT(DISTINCT s.affiliate_id) AS client_count FROM public.affiliate_commission_statements s JOIN public.accounts a ON a.id = s.affiliate_id WHERE a.role IN ('Affiliate','AffiliateManager','Partner') AND EXISTS (SELECT 1 FROM public.affiliate_commission_statements p WHERE p.affiliate_id = s.affiliate_id AND p.paid_at IS NOT NULL) AND EXISTS (SELECT 1 FROM public.affiliate_commission_statements u WHERE u.affiliate_id = s.affiliate_id AND u.paid_at IS NULL)

SELECT
  COUNT(DISTINCT s.affiliate_id) AS client_count
FROM public.affiliate_commission_statements AS s
JOIN public.accounts AS a
  ON a.id = s.affiliate_id
WHERE
  a.role IN ('Affiliate', 'AffiliateManager', 'Partner')
  AND EXISTS(
    SELECT
      1
    FROM public.affiliate_commission_statements AS p
    WHERE
      p.affiliate_id = s.affiliate_id AND NOT p.paid_at IS NULL
  )
  AND EXISTS(
    SELECT
      1
    FROM public.affiliate_commission_statements AS u
    WHERE
      u.affiliate_id = s.affiliate_id AND u.paid_at IS NULL
  )

'Paid' is defined as paid_at IS NOT NULL; 'unpaid' as paid_at IS NULL on the statement record.

Professional CT partner accounts are taken to be those with role in Affiliate, AffiliateManager or Partner.

List the 3 affiliates and their paid vs unpaid statement counts.

How much commission value sits in the unpaid statements for these affiliates?

Counts distinct affiliate_ids, so affiliates with multiple statements are counted once.

The account role filter includes Affiliate, AffiliateManager and Partner roles — the set is not limited to a single role.

For exactly the professional CT partner accounts with both paid and unpaid monthly affiliate statements in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.

Reads affiliate_commission_statements joined to accounts on accounts.id = statements.affiliate_id.

Keeps only rows where the account role is 'Affiliate', 'AffiliateManager', or 'Partner'.

Requires the affiliate to have at least one statement where paid_at is filled in (paid).

Requires the affiliate to have at least one statement where paid_at is empty (unpaid).

Returns the number of distinct affiliate IDs meeting all conditions as client_count.

Summary: Count distinct affiliate IDs from commission statements whose account role is Affiliate, AffiliateManager, or Partner and who have at least one paid statement and at least one unpaid statement.


32 client records have an affiliated referrer in a professional affiliate role (Affiliate, AffiliateManager or Partner).

Keep the CT client records referred by a professio...

System: CT

client

System: CT

professional affiliate

System: CT

commission rate

Query complexity

Complex query: 2 JOINs, window functions

SELECT a.id AS user_id, COUNT(*) OVER () AS client_count FROM public.accounts AS a JOIN public.clients AS c ON c.user_id = a.id JOIN public.accounts AS ref ON ref.id = a.affiliate_id WHERE NOT a.affiliate_id IS NULL AND ref.role IN ('Affiliate', 'AffiliateManager', 'Partner') GROUP BY a.id ORDER BY a.id DESC NULLS LAST

Referrer is taken from accounts.affiliate_id with the referrer's role in Affiliate, AffiliateManager or Partner; no commission-rate or client-type filter appears in the query, so any CT or zero-commission condition was not applied here.

Counts distinct client user_ids; accounts with no affiliate_id are excluded.

How many of these 32 are CT client records specifically?

Which of these clients have had activity in the last 90 days?

client_count is a windowed row count across the whole result, so every row shows 32; the true figure is the 32 distinct user_ids returned.

The referrer filter is applied to the referrer's role, not to any commission rate, so no zero-commission condition is visible in this query.

Rows are one per client user_id, ordered by id descending; the sample shows only the first 12 rows.

Keep the CT client records referred by a professional affiliate whose commission rate is zero membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.

Reads the accounts table twice (as a and as ref) and the clients table once.

Joins clients to accounts by matching clients.user_id to accounts.id, and attaches the referring account ref by matching accounts.affiliate_id to ref.id.

Keeps only rows where affiliate_id is filled in (excludes rows where it is empty).

Keeps only rows where the referring account's role is 'Affiliate', 'AffiliateManager', or 'Partner'.

Returns each account's id as user_id, grouped by that id.

client_count is the total number of rows in the result (the same number on every row); if there are no rows, the count is zero.

Summary: List every account that has a referring account with an affiliate-style role, and count how many such accounts exist in total.


3 results — first client: Fictional Partner 4

Show the same checked IDs for the professional CT ...

System: CT

partner

System: CT

accounts

System: CT

SELECT acs.affiliate_id AS user_id FROM public.affiliate_commission_statements AS acs JOIN public.accounts AS a ON a.id = acs.affiliate_id WHERE a.role IN ('Affiliate', 'AffiliateManager', 'Partner') GROUP BY acs.affiliate_id HAVING COUNT(*) FILTER(WHERE NOT acs.paid_at IS NULL) > 0 AND COUNT(*) FILTER(WHERE acs.paid_at IS NULL) > 0 ORDER BY acs.affiliate_id DESC NULLS LAST

Show the same checked IDs for the professional CT partner accounts with both paid and unpaid monthly affiliate statements from the first result, this time in descending user_id order. Keep every member and show only user_id.

Joins affiliate_commission_statements to accounts by matching the statement's affiliate_id to the account's id.

Keeps only accounts whose role is 'Affiliate', 'AffiliateManager', or 'Partner' — accounts with any other role are excluded.

Keeps a group only if it has at least one statement where paid_at is filled in (paid) AND at least one where paid_at is empty (unpaid).

Returns the affiliate_id labeled as user_id, ordered from largest to smallest, with any empty IDs placed last.

Summary: Lists affiliate IDs that have at least one paid and at least one unpaid commission statement, keeping only accounts whose role is Affiliate, AffiliateManager, or Partner, sorted from highest to lowest ID.


System: CT

accounts

Owning salesperson id (account-level). Used alongside relationship_manager_id to assign a client's sales 'stream'/team.

System: CT

salesperson

Owning relationship manager id (account-level).

System: CT

relationship manager

System: PD

people

System: CT

System: PD

person ID

SELECT DISTINCT a.id AS user_id FROM public.accounts AS a WHERE a.role = 'User' AND NOT a.salesperson_id IS NULL AND NOT a.relationship_manager_id IS NULL AND a.salesperson_id <> a.relationship_manager_id ORDER BY 1 LIMIT 10000

SELECT user_id FROM ct.client_360 WHERE NOT salesperson_person_id IS NULL AND NOT relationship_manager_person_id IS NULL AND salesperson_person_id <> relationship_manager_person_id GROUP BY user_id ORDER BY user_id ASC LIMIT 10000

List every distinct ordinary CT user accounts whose salesperson and relationship manager are both known and are different people. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.


3 affiliate accounts have both a paid and an unpaid monthly commission statement.

Keep the professional CT partner accounts with bot...

System: CT

partner

System: CT

accounts

System: CT

client

SELECT COALESCE(x.client_count, 0) AS client_count FROM (SELECT COUNT(*) AS client_count FROM (SELECT acs.affiliate_id FROM public.affiliate_commission_statements acs JOIN public.accounts a ON a.id = acs.affiliate_id WHERE a.role IN ('Affiliate','AffiliateManager','Partner') GROUP BY acs.affiliate_id HAVING COUNT(*) FILTER (WHERE acs.paid_at IS NOT NULL) > 0 AND COUNT(*) FILTER (WHERE acs.paid_at IS NULL) > 0) p) x

SELECT
  COALESCE(x.client_count, 0) AS client_count
FROM (
  SELECT
    COUNT(*) AS client_count
  FROM (
    SELECT
      acs.affiliate_id
    FROM public.affiliate_commission_statements AS acs
    JOIN public.accounts AS a
      ON a.id = acs.affiliate_id
    WHERE
      a.role IN ('Affiliate', 'AffiliateManager', 'Partner')
    GROUP BY
      acs.affiliate_id
    HAVING
      COUNT(*) FILTER(WHERE
        NOT acs.paid_at IS NULL) > 0
      AND COUNT(*) FILTER(WHERE
        acs.paid_at IS NULL) > 0
  ) AS p
) AS x

'Professional CT partner accounts' interpreted as accounts with role in ('Affiliate','AffiliateManager','Partner')

'Paid' means paid_at is not null and 'unpaid' means paid_at is null on affiliate_commission_statements

List the 3 affiliate accounts and their counts of paid vs unpaid statements

What is the total unpaid commission value outstanding for those 3 accounts?

Each account must have at least one statement with a non-null paid_at and one with a null paid_at, so these are accounts with a settled and an outstanding statement.

Accounts counted are those with role in ('Affiliate','AffiliateManager','Partner') — the question's 'professional CT partner' framing maps to these three roles, which may be broader than partner-only.

Keep the professional CT partner accounts with both paid and unpaid monthly affiliate statements membership from the third result and count those distinct IDs as client_count. An empty result counts as zero.

Read commission statements from affiliate_commission_statements and attach the matching account from accounts on matching id.

Keep only accounts whose role is 'Affiliate', 'AffiliateManager', or 'Partner'.

Require each affiliate to have at least one statement where paid_at is filled in and at least one where paid_at is empty.

Count the affiliates that pass both checks.

If nothing passes, the count is replaced with zero.

Summary: Count how many affiliates with a partner/affiliate/manager role have at least one paid and at least one unpaid commission statement, reporting zero if none exist.


System: CT

accounts

System: CT

salesperson

System: CT

relationship manager

System: PD

people

System: CT

client

```json
{
  "sql": "",
  "explanation": "The schema provides no column definitions for ct.client_360 (or any table), so the columns identifying the salesperson and relationship manager needed to test 'both known and different people' cannot be reliably referenced.",
  "confidence": "uncertain",
  "w

For exactly the ordinary CT user accounts whose salesperson and relationship manager are both known and are different people in the first checked result, return their distinct count as client_count. Keep that membership and return zero if it is empty.


System: CT

accounts

System: CT

salesperson

System: CT

relationship manager

System: PD

people

System: CT

```json
{
  "sql": "",
  "explanation": "The request references ct.client_360 and pipedrive tables with salesperson/relationship manager fields that are not present in the provided schema, and it depends on an undefined 'first result' context.",
  "confidence": "uncertain",
  "warnings": [
    "No c

Show the same checked IDs for the ordinary CT user accounts whose salesperson and relationship manager are both known and are different people from the first result, this time in descending user_id order. Keep every member and show only user_id.


At least 43 distinct CT accounts are assigned to a campaign and have a known web referral domain.

List every distinct CT accounts of any role assign...

System: CT

CT accounts

System: CT

System: PD

person ID

SELECT DISTINCT a.id AS user_id FROM public.accounts AS a JOIN public.user_analytics AS ua ON ua.user_id = a.id WHERE NOT a.campaign_id IS NULL AND NOT ua.came_from_domain IS NULL ORDER BY 1 LIMIT 10000

'CT account' was matched by the account rows themselves; any account role was accepted since the query does not filter on role.

Only accounts with both a non-null campaign_id and a non-null came_from_domain are included.

Show these accounts grouped by campaign and referral domain to see which sources dominate.

List the client names and types for all 43 accounts.

How many campaign-assigned accounts have no known referral domain?

43 rows were returned but the sample shows only the first 12, ordered by user_id, so no pattern beyond these rows can be inferred.

In the sample shown, most accounts share client type cfx (corporate), with pfx (private) appearing twice.

List every distinct CT accounts of any role assigned to a campaign and with a known web referral domain. Return only user_id, in ascending order; use the person ID for a Pipedrive-only person.

Looks at the accounts table and the user_analytics table, matching rows where user_analytics.user_id equals the account's id.

Keeps only accounts where campaign_id is not empty/null — accounts with no campaign assigned are dropped.

Also requires that came_from_domain is not empty/null, so accounts with no known referral domain are dropped.

Returns each qualifying id once (no duplicates), sorted from smallest to largest, with at most 10,000 results.

Summary: Finds each distinct account that has a campaign assigned and a known web referral domain, returning only the account IDs in ascending order.