{"uid":"cap__on-OcUR89bmJNB8hPfki","slug":"code-review-data-quality-suite-record-audit-string-normalisation-96184acb","name":"Code Review Data Quality Suite: Record Audit + String Normalisation + Numeric Row Ordering","description":"Code review — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied code review records (pull_requests, review_hours). 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-software-11-196?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","component","date","pull_requests","review_hours"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"component":{"type":"string","default":"","maxLength":80},"review_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"pull_requests":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","component":"group-a","review_hours":1,"pull_requests":10},{"date":"2026-10-02","row_id":"row-2","component":"group-b","review_hours":2,"pull_requests":20},{"date":"2026-10-03","row_id":"row-3","component":"group-a","review_hours":3,"pull_requests":15},{"date":"2026-10-04","row_id":"row-4","component":"group-b","review_hours":4,"pull_requests":30}],"maxItems":200,"minItems":1},"field":{"enum":["pull_requests","review_hours"],"type":"string","default":"pull_requests"}}},"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_nlE5MrnEqyoHcMzvuwL3S","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 local analytical reports on code review records (pull requests, review hours): record quality audit, string normalisation, and numeric row ordering — no external lookups or predictions.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and numeric row ordering on my code review data? I have rows with pull_requests and review_hours fields — here's a sample: row-1, group-a, 2026-10-01, 10 pull requests, 1 review hour; row-2, group-b, 2026-10-02, 20 pull requests, 2 review hours. Sort by pull_requests.","exampleUseCases":[{"title":"Pre-merge code review data cleanup","prompt":"I've got a CSV of our team's weekly code review stats — component names, dates, pull request counts, and review hours. Can you audit the record quality, normalise the component strings, and order the rows by review_hours so I can spot outliers before importing it into our dashboard?"},{"title":"Engineering metrics QA for sprint report","prompt":"Before I send out our sprint report, can you run all three checks — quality audit, string normalisation, and numeric ordering by pull_requests — on these 80 rows of code review data I'm pasting in? The fields are row_id, component, date, pull_requests, and review_hours."},{"title":"Detect bad records in PR tracking sheet","prompt":"Our pull request tracking sheet has some messy entries — inconsistent component names and possibly missing review hours. Can you do a record quality audit and string normalisation on up to 150 rows, ordered by pull_requests, so I know which rows need fixing?"}],"resultDescription":"Returns three independent analytical reports for the submitted code review rows: (1) a record quality audit flagging issues per row, (2) a string normalisation report for the component field, and (3) a numeric row ordering report ranked by the chosen field (pull_requests or review_hours). All processing is local with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, component, date, pull_requests, review_hours) cause rejection","Invalid date format (not YYYY-MM-DD) triggers a schema error","Numeric values outside allowed range cause validation failure","Empty rows array is rejected","Payment not included or insufficient USDC causes x402 payment error"],"whenToPreferThis":"Choose this endpoint when you need a bundled, affordable ($0.01) set of three data quality operations — audit, string normalisation, and numeric ordering — on up to 200 code review records in a single call, without needing live data lookups, ML predictions, or external integrations. Ideal for pre-import data cleaning or sprint reporting pipelines.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:32:16.393Z","isFirstParty":false,"canonicalSlug":"code-review-data-quality-suite-record-audit-string-normalisation-96184acb"}