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Token Supply Snapshots — Record Quality Audit, String Normalisation & Exact Row Deduplication
x402
Token Supply Snapshots — 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 2026-10-26).
Audits, normalises, and deduplicates up to 200 rows of token supply snapshot data (circulating_units, total_units), producing 3 independent analytical reports locally without any external lookups.
Price / call$0.01
Success—
StatusUnknown
How this service works
Token supply snapshots — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication for supplied token supply snapshots records (circulating_units, total_units). 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 analytical reports for the submitted token supply snapshot rows: (1) a record quality audit flagging missing, malformed, or out-of-range values in circulating_units and total_units; (2) a string normalisation report standardising instrument_group and other text fields; and (3) an exact row deduplication report identifying and removing identical rows. All analysis is performed locally with no external data lookups.
Example use cases
Token supply data pipeline hygiene
“I'm loading daily token supply snapshots into our data warehouse — can you audit the record quality, normalise the instrument_group strings, and find any exact duplicate rows across these 120 entries before I commit them?”
Crypto index rebalancing data validation
“Before our monthly rebalancing, I need to validate our token supply data. Can you run a quality audit, string normalisation, and deduplication check on these 80 token supply snapshot rows covering circulating_units and total_units?”
Research dataset deduplication for token metrics
“I'm preparing a research dataset of token supply snapshots for a report — can you check these 200 rows for record quality issues, normalise any inconsistent strings in instrument_group, and flag any exact duplicate rows so I can clean it up?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-11-191?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three combined data-quality operations — record auditing, string normalisation, and exact deduplication — applied to token supply snapshot data (circulating_units and total_units) in a single $0.01 call covering up to 200 rows. It is ideal when you want offline, local analytical processing with no external data enrichment or predictions, and when cost efficiency for batch data cleaning is a priority.
Side effects
- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, instrument_group, date, circulating_units, total_units) on any row — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric values outside ±1,000,000,000,000 range — schema rejection
- Payment of 0.01 USDC not completed — 402 Payment Required response
- Empty rows array (minItems: 1 not met) — request rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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