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Trading Journal Observations — Record Quality Audit + String Normalisation + Numeric Distribution
x402
Trading Journal Observations — Record Quality Audit + String Normalisation + Numeric Distribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).
Runs three local analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 trading journal rows containing entry_price and exit_price fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Trading journal observations — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution for supplied trading journal observations records (entry_price, exit_price). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three structured analytical reports: (1) a record quality audit flagging nulls, missing fields, and anomalies across rows; (2) a string normalisation report standardising text fields like instrument_group and date formatting; and (3) a numeric distribution report for the selected price field (entry_price or exit_price), including statistical summaries across up to 200 supplied rows. All analysis is performed locally with no external lookups.
Example use cases
Pre-analysis trading data cleanup
“I have a CSV of 150 trade records with columns row_id, date, instrument_group, entry_price, and exit_price — can you run a full quality audit, string normalisation check, and numeric distribution on the entry_price field so I can spot problems before I do any backtesting?”
Daily trade log validation
“Every evening I export my trading journal with up to 50 rows — run the three standard reports (quality audit, string normalisation, numeric distribution for exit_price) so I can see if there are any bad records or outliers from today's session.”
Instrument group data profiling
“I'm comparing trade data across instrument groups like 'crypto', 'equities', and 'commodities' in my journal — can you audit the record quality, normalise the string fields, and show the numeric distribution of entry_price across these 80 rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-09-193?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a bundled, low-cost ($0.01 USDC) set of three data profiling reports — quality audit, string normalisation, and numeric distribution — on a batch of up to 200 trading journal records. It is ideal for pre-processing pipelines where you want to validate and profile raw trade data (entry_price, exit_price) before downstream analysis, without requiring any external data sources, predictions, or professional assessments. Prefer it over building custom profiling logic when the specific combination of these three report types covers your needs.
Side effects
- Rows array is empty or exceeds 200 items — validation error returned
- Required fields (row_id, date, entry_price, exit_price, instrument_group) missing from one or more rows — schema validation failure
- Date field does not match YYYY-MM-DD pattern — row rejected or flagged
- Price values outside the allowed range (±1,000,000,000,000) — schema rejection
- Invalid field selector (not 'entry_price' or 'exit_price') — enum validation error
- Payment of 0.01 USDC not completed — 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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