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Endpoint Telemetry Analyzer — Record Quality Audit + String Normalisation + Trailing Mean Series
x402
Endpoint Telemetry Analyzer — Record Quality Audit + String Normalisation + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).
Runs three analytical reports (record quality audit, string normalisation, and trailing mean series) on supplied endpoint telemetry rows with agent_count and reporting_agents fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Endpoint telemetry — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series for supplied endpoint telemetry records (agent_count, reporting_agents). 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 completeness, validity, and anomalies in the telemetry rows; (2) string normalisation output cleaning and standardizing string fields like control_group; and (3) a trailing mean series showing rolling averages over the specified window for the chosen numeric field (agent_count or reporting_agents).
Example use cases
Telemetry data quality check
“I have a batch of endpoint telemetry rows with agent_count and reporting_agents values and I want to know if there are any record quality issues or messy string fields — can you run a full quality audit and string normalisation on these 50 rows using a window of 3 on agent_count?”
Rolling average for agent reporting trend
“Can you compute a trailing mean series with a window of 5 on the reporting_agents field for my telemetry dataset? I have about 120 daily rows across multiple control groups and want to spot trends.”
Clean and validate control group labels
“My endpoint telemetry records have inconsistent control_group labels and I need them normalised — can you run the string normalisation and record quality audit on these 30 rows so I can trust the data before analysis?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-security-15-199?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously audit data quality, normalise string fields, and compute a rolling/trailing mean on time-series telemetry records for agent monitoring in a single low-cost call. It is best when your data is already collected (no live lookup needed) and you want three analytical passes in one request at $0.01 USDC for up to 200 rows.
Side effects
- Missing required fields (row_id, date, agent_count, reporting_agents, control_group) causes validation error
- Exceeding 200 rows returns an error or truncation
- Window size outside range 2–200 is rejected
- Date fields not matching YYYY-MM-DD pattern fail schema validation
- Null-only numeric columns may produce empty trailing mean output
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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