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Trading Journal Observations — Record Quality Audit + String Normalisation + Exact Row Deduplication
x402
Trading Journal Observations — Record Quality Audit + String Normalisation + Exact Row Deduplication 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).
Audits data quality, normalises strings, and deduplicates rows for trading journal observation records containing entry and exit prices.
Price / call$0.01
Success—
StatusUnknown
How this service works
Trading journal observations — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication 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 independent reports for up to 200 supplied trading journal rows: (1) a record quality audit flagging data issues in entry_price and exit_price fields, (2) a string normalisation report standardising text fields such as instrument_group, and (3) an exact row deduplication report identifying identical records. All analysis is performed locally on the supplied data with no external lookups or predictions.
Example use cases
Pre-analysis trading data cleanup
“Before I run my performance analysis, can you check my trading journal for bad data quality, normalise the instrument group names, and remove any duplicate entries? I have 80 trade rows with row IDs, dates, and entry and exit prices.”
Deduplication of imported trade records
“I just imported 150 trading journal rows from two different sources and I'm worried there are duplicates. Can you run an exact deduplication check on these records and also audit them for quality issues and standardise the string fields?”
Data quality review for trade log audit
“I need a formal data quality audit of my trading log — 120 rows with entry price, exit price, instrument group, and date — including string normalisation and a duplicate row report, so I can clean it up before sharing it with my compliance team.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-09-191?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined data quality audit, string normalisation, and exact deduplication pass over trading journal records (entry/exit prices) in a single call for up to 200 rows. It is ideal for pre-processing trade data before analytics, compliance review, or importing into a clean dataset. It does not perform live market lookups, predictions, or external enrichment — prefer it when you want fast, local, offline data hygiene on structured trade records.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds maximum batch size
- Missing required fields (row_id, instrument_group, date, entry_price, or exit_price) — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Numeric price values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejected
- Malformed JSON body — parse error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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