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Brayo Bounty Intelligence Dataset Audit
x402
Brayo Bounty Intelligence Dataset Audit is a paid API for AI agents from brayo-bounty-intelligence.floot.app, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-11).
Analyzes a submitted dataset of rows for bounty competition quality and viability using a JSON-quality methodology, returning field structure, row/column counts, and duplicate detection.
Price / call$0.01
Success—
StatusUnknown
How this service works
Machine-readable bounty competition and viability analysis.
Output
Returns a JSON object containing: a list of detected fields, total row count, column count, number of duplicate rows, and the methodology label used (e.g. 'top-level-json-quality-v1') — giving a machine-readable quality and structure assessment of the submitted dataset.
Example use cases
Pre-submission bounty dataset check
“I've got 500 rows of JSON data I want to submit to a bounty competition — can you audit them with Brayo Bounty Intelligence to check for duplicates, see what columns were detected, and tell me if the quality looks good enough to compete?”
Duplicate detection in scraped data
“I scraped about 200 records and I'm worried there are duplicates in there — can you send them through the Brayo dataset audit and tell me how many rows are actually unique?”
Validating dataset structure before upload
“Before I upload this dataset to the bounty platform, can you run it through Brayo Bounty Intelligence and confirm how many fields and columns it detected, and what methodology was used to score it?”
Technical details
Endpoint
POSThttps://brayo-bounty-intelligence.floot.app/_api/v1/dataset-audit?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, machine-readable quality audit of a JSON dataset specifically in the context of bounty competition viability — particularly when you need duplicate detection, field enumeration, and a structured quality score in a single call. Prefer this over generic data profiling tools when working within the Brayo bounty ecosystem.
Side effects
- Empty rows array (minItems:1 violated) returns validation error
- Rows array exceeding 1000 items (maxItems:1000 violated) returns error
- Malformed JSON objects in rows array may cause parsing failures
- Non-object items in the rows array may produce unexpected field detection results
- Network timeout if dataset processing takes too long
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Output
Schema · Response
{
"type": "json",
"example": {
"fields": [],
"rowCount": 2,
"columnCount": 2,
"methodology": "top-level-json-quality-v1",
"duplicateRows": 0
}
}Tags
x402
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