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Accessibility Findings — Trailing Mean Series + Two-Measure Correlation
x402
Accessibility Findings — Trailing Mean Series + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Computes a trailing mean time series and a two-measure (findings vs resolved_findings) correlation report for up to 200 accessibility findings records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Accessibility findings — Trailing mean series + Two-measure correlation: Trailing mean series + Two-measure correlation for supplied accessibility findings records (findings, resolved_findings). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two statistical reports computed locally on the supplied data: (1) a trailing mean time series for the specified field (findings or resolved_findings) using the configured window size, and (2) a Pearson or similar correlation between the findings and resolved_findings measures across all rows. No external lookup or prediction is performed.
Example use cases
Game accessibility audit trend analysis
“I have 50 rows of daily accessibility findings for two game areas across the last two months, each with a findings count and resolved_findings count. Can you compute a trailing mean series with a window of 7 days on the findings field and also run the two-measure correlation between findings and resolved_findings?”
Sprint-level resolved issues correlation
“We track open and resolved accessibility issues per sprint area — I've got about 80 records with dates, row IDs, game areas, findings, and resolved_findings. Please run the trailing mean with a window of 4 on the resolved_findings field and show me the two-measure correlation between the two metrics.”
Accessibility regression detection across game zones
“I need to spot regressions in our accessibility findings data across four game zones over the past quarter — 120 rows total. Compute the trailing mean series using a window of 5 for the findings field, and give me the correlation between findings and resolved_findings.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-17-150?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 timestamped accessibility findings records and need both a rolling/trailing mean time series and a cross-measure correlation between findings and resolved_findings in a single $0.01 call. Prefer it over generic stats APIs when your data fits the specific schema (row_id, game_area, date, findings, resolved_findings) and you want two reports bundled together without external data lookups.
Side effects
- Fewer than 2 rows provided — minimum 1 row required but trailing mean needs at least window-size rows
- Window size larger than number of rows — trailing mean series will have insufficient data points
- Invalid date format — must match YYYY-MM-DD pattern
- Row count exceeds 200 — request will be rejected
- Null values in findings or resolved_findings may reduce effective sample size for correlation
- Invalid field enum value — must be 'findings' or 'resolved_findings'
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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