{"uid":"cap_IJYwb00pd0d-S7z302Ct4","slug":"request-latency-string-normalisation-and-exact-row-deduplication-ebc1e47b","name":"Request Latency String Normalisation and Exact Row Deduplication","description":"Request latency — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied request latency records (latency_ms, request_count). 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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-software-03-020?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","component","date","latency_ms","request_count"],"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},"latency_ms":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"request_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","component":"group-a","latency_ms":10,"request_count":1},{"date":"2026-10-02","row_id":"row-2","component":"group-b","latency_ms":20,"request_count":2},{"date":"2026-10-03","row_id":"row-3","component":"group-a","latency_ms":15,"request_count":3},{"date":"2026-10-04","row_id":"row-4","component":"group-b","latency_ms":30,"request_count":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_HikurFtPzSGHctvMo0hP_","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":"Normalises strings and deduplicates exact rows in request latency records (latency_ms, request_count), returning 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you clean up these 50 request latency records — normalise the component name strings and remove any exact duplicate rows — and give me both analytical reports? Here's the data with row_id, component, date, latency_ms, and request_count fields.","exampleUseCases":[{"title":"Deduplicate repeated latency log entries","prompt":"I have a batch of 120 request latency log rows from our API monitoring system and I suspect there are exact duplicates. Can you normalise the component strings and strip out the duplicate rows, then give me the two reports showing what changed?"},{"title":"Standardise component names across services","prompt":"Our latency data has inconsistent component names like 'Group-A', 'group-a', and 'GROUP-A' all meaning the same thing — can you run string normalisation and exact deduplication on these 80 rows and return both analytical reports?"},{"title":"Pre-pipeline data quality check on latency metrics","prompt":"Before I load this request latency dataset into our dashboard, can you normalise the strings and deduplicate the rows? There are about 150 records with latency_ms and request_count fields — I need both quality reports back."}],"resultDescription":"Two analytical reports covering the results of string normalisation and exact row deduplication applied to the submitted latency records. Reports reflect the cleaned dataset with duplicates removed and string fields standardised, processed locally without external lookups or predictions.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, component, date, latency_ms, request_count) cause validation errors","Malformed date strings not matching YYYY-MM-DD pattern cause schema rejection","Null numeric values for latency_ms or request_count may affect deduplication logic","Payment not fulfilled — x402 payment required before processing"],"whenToPreferThis":"Choose this endpoint when you have raw request latency records (up to 200 rows) that need string normalisation and exact duplicate removal before further analysis or storage, and you want two independent summary reports at minimal cost. Prefer this over general-purpose data cleaning tools when your data specifically contains latency_ms and request_count fields organised by component and date, and you need deterministic local processing with no external API calls or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:37:30.113Z","isFirstParty":false,"canonicalSlug":"request-latency-string-normalisation-and-exact-row-deduplication-ebc1e47b"}