{"uid":"cap_Am7oBiinwZKbt9TDJi-Dc","slug":"validator-uptime-record-quality-audit-string-normalisation-exact-row-849fd85f","name":"Validator Uptime — Record Quality Audit + String Normalisation + Exact Row Deduplication","description":"Validator uptime — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication for supplied validator uptime records (online_minutes, observed_minutes). 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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-finance-12-191?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","instrument_group","date","online_minutes","observed_minutes"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"online_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"instrument_group":{"type":"string","default":"","maxLength":80},"observed_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","online_minutes":10,"instrument_group":"group-a","observed_minutes":1},{"date":"2026-10-02","row_id":"row-2","online_minutes":20,"instrument_group":"group-b","observed_minutes":2},{"date":"2026-10-03","row_id":"row-3","online_minutes":15,"instrument_group":"group-a","observed_minutes":3},{"date":"2026-10-04","row_id":"row-4","online_minutes":30,"instrument_group":"group-b","observed_minutes":4}],"maxItems":200,"minItems":1}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_p4UpLSPs_WIYL7oeQNTVD","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Audits record quality, normalises strings, and deduplicates exact rows for up to 200 validator uptime records (online_minutes, observed_minutes), returning 3 independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and exact row deduplication on these validator uptime records? I have up to 50 rows with fields like row_id, instrument_group, date, online_minutes, and observed_minutes — I want all three reports back.","exampleUseCases":[{"title":"Validator fleet uptime data cleanse","prompt":"I've got 120 rows of daily validator uptime logs — each row has a row_id, instrument_group, date, online_minutes, and observed_minutes. Can you run a full quality audit, normalise the string fields, and flag any exact duplicate rows so I can clean the dataset before reporting?"},{"title":"Staking pool uptime deduplication check","prompt":"Before I aggregate our staking pool validator performance, can you check these 80 uptime records for exact duplicate rows and also audit them for data quality issues? Fields are row_id, instrument_group, date, online_minutes, and observed_minutes."},{"title":"Instrument group string consistency audit","prompt":"Our uptime export has inconsistent instrument_group naming and possibly some dirty records — can you normalise those strings and run a record quality audit across these 60 validator uptime rows so we know what needs fixing?"}],"resultDescription":"Three independent analytical reports covering: (1) a record quality audit identifying missing, malformed, or out-of-range values across all row fields; (2) a string normalisation report detailing transformations applied to text fields such as instrument_group; and (3) an exact row deduplication report identifying and removing wholly duplicate rows. All analysis is performed locally with no external lookups or predictions.","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, instrument_group, date, online_minutes, observed_minutes) cause row-level rejection","Invalid date format (not YYYY-MM-DD) causes parsing failure","Numeric values outside the allowed range trigger field-level errors","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you need three bundled data-quality operations — quality auditing, string normalisation, and exact deduplication — on validator uptime records in a single low-cost call. It is ideal for pre-processing uptime datasets (up to 200 rows) before aggregation or reporting, and when no live lookup, prediction, or external data enrichment is required.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:33:31.434Z","isFirstParty":false,"canonicalSlug":"validator-uptime-record-quality-audit-string-normalisation-exact-row-849fd85f"}