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Edge Agents AI – Data Quality Stale Series Detector
x402
Edge Agents AI – Data Quality Stale Series Detector is a paid API for AI agents from pay.edge-agents.ai, paid per call via x402, $0.1/call, status unknown (last checked 2026-10-30).
Detects and reports on stale or outdated data series across cross-market financial and macro datasets, returning a confidence-scored freshness assessment with evidence provenance.
Price / call$0.1
Success—
StatusUnknown
How this service works
Stale Series Detector for official macro evidence tracked by Edge Agents, with explicit baseline and persistence limitations. Purpose: identify tracked series whose observation pipeline has exceeded a frequency-aware freshness threshold 24-hour freshness target; missing evidence is reported explicitly rather than invented.
Output
Returns a JSON object containing a data quality status (e.g. 'strong'), a confidence level (e.g. 'high'), a cross-market analysis summary identifying stale series, a list of evidence assets, policy and source provenance, a signed issuer record, generation timestamp, schema version, and a disclaimer that findings are general market research and not investment advice.
Example use cases
Pre-trade data freshness check
“Before I run my macro momentum strategy today, can you check whether any of the underlying market data series are stale or have gaps, and give me a confidence rating on the overall data quality?”
Investment committee data audit
“I need to present to the investment committee tomorrow — can you run a stale series check on our cross-market inputs and summarize which sources are fresh versus outdated with evidence?”
Automated pipeline data quality gate
“My AI agent pipeline is about to consume macro data for a decision model — can you validate whether the input series are current and flag any stale or low-confidence data before we proceed?”
Technical details
Endpoint
GEThttps://pay.edge-agents.ai/v1/services/data-quality-stale-series?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need an evidence-backed, confidence-scored assessment of whether specific financial or macro data series are current before consuming them in analytical pipelines, investment decisions, or agent workflows. It is specifically suited for cross-market data freshness validation with signed provenance, making it preferable to generic data checks when auditability and source traceability matter.
Side effects
- Missing or malformed required parameters returns an error with no quality assessment
- Data series not found or not covered results in empty evidence assets and a note on coverage limitations
- Upstream source unavailability may lower confidence rating or return partial results
- Stale or uncached series may trigger a 'complete' dataStatus but with low-confidence findings
- Payment not processed (x402) results in 402 response and no report delivered
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| required | string | |
| properties | string |
Output
Schema · Response
{
"type": "json",
"example": {
"quality": {
"status": "strong",
"confidence": "high"
},
"analysis": {
"family": "cross-market",
"intents": [
"evidence"
],
"summary": "Fresh Stale Series Detector findings appear here."
},
"evidence": {
"assets": [],
"policy": "mixed",
"sources": "Reported from the actual live report; never inferred from this example."
},
"serviceId": "data-quality-stale-series",
"dataStatus": "complete",
"disclaimer": "General, impersonal market research; not investment advice or a buy, sell or hold recommendation.",
"provenance": {
"issuer": "https://edge-agents.ai",
"signed": true
},
"generatedAt": "2026-08-31T00:00:00.000Z",
"limitations": [
"Coverage, source freshness and unavailable evidence are stated in every paid report."
],
"schemaVersion": "2.0"
}
}Tags
x402
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