{"uid":"cap_7Lq72kbwSfwVtV_ktWrm3","slug":"staking-supplied-rewards-record-quality-audit-string-normalisation-acd9a3ea","name":"Staking Supplied Rewards — Record Quality Audit + String Normalisation + Adjacent Row Changes","description":"Staking supplied rewards — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied staking supplied rewards records (reward_units, staked_units). 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-15-200?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","instrument_group","date","reward_units","staked_units"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"reward_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"staked_units":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"instrument_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","reward_units":10,"staked_units":1,"instrument_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","reward_units":20,"staked_units":2,"instrument_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","reward_units":15,"staked_units":3,"instrument_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","reward_units":30,"staked_units":4,"instrument_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["reward_units","staked_units"],"type":"string","default":"reward_units"}}},"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_H-90J5A7_syQ8rOXnQ3zg","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":"Runs three analytical reports (record quality audit, string normalisation, and adjacent row changes) on up to 200 rows of staking reward/staked-units data, all processed locally without external lookups.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation check, and adjacent row changes report on my staking rewards data? I have rows with fields row_id, instrument_group, date, reward_units, and staked_units — up to 50 rows — and I want to analyse the reward_units field.","exampleUseCases":[{"title":"Staking reward data quality check","prompt":"I have 120 rows of daily staking reward records with instrument groups and reward_units values — can you run a record quality audit, string normalisation, and adjacent row changes analysis on them so I can spot any bad data or formatting issues?"},{"title":"Detect row-over-row reward changes","prompt":"I need to find where my staked_units values changed significantly between adjacent rows in my staking dataset — can you run the adjacent row changes report on these 80 records and focus on the staked_units field?"},{"title":"Normalise instrument group strings in staking data","prompt":"My staking reward records have inconsistent instrument_group labels across 150 rows — can you run the string normalisation report on this data so I can see which entries need cleaning?"}],"resultDescription":"Three independent analytical reports returned in a single response: (1) a record quality audit flagging missing, null, or out-of-range values in reward_units and staked_units; (2) a string normalisation report highlighting inconsistencies in text fields like instrument_group; and (3) an adjacent row changes report showing row-over-row differences in the selected numeric field (reward_units or staked_units). All analysis is performed on the supplied data with no external data sources.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, instrument_group, date, reward_units, staked_units) causes rejection","Invalid date format (not YYYY-MM-DD) triggers a schema validation error","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array (minItems:1 not met) causes a bad request error","Payment failure via x402 protocol blocks the request"],"whenToPreferThis":"Choose this endpoint when you have tabular staking reward records (up to 200 rows) and need three complementary data-quality perspectives in a single call at minimal cost ($0.01 USDC). It is ideal for offline/local analysis of supplied data without any external API calls, live price lookups, or predictions. Prefer it over single-report endpoints when you need quality audit, string normalisation, and adjacent-row change detection simultaneously on the same dataset.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T12:54:01.155Z","isFirstParty":false,"canonicalSlug":"staking-supplied-rewards-record-quality-audit-string-normalisation-acd9a3ea"}