{"uid":"cap_4ELyDDCswr-AyXr8uJOgd","slug":"api-usage-string-normalisation-5f73c96f","name":"API Usage String Normalisation","description":"API usage - String normalisation: String normalisation for API usage. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded string normalisation deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-analytics-api-usage-normalise?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","endpoint","date","requests","latency_ms"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"endpoint":{"type":"string","default":"","maxLength":80},"requests":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"latency_ms":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","endpoint":"group-a","requests":10,"latency_ms":1},{"date":"2026-10-02","row_id":"row-2","endpoint":"group-b","requests":20,"latency_ms":2},{"date":"2026-10-03","row_id":"row-3","endpoint":"group-a","requests":15,"latency_ms":3},{"date":"2026-10-04","row_id":"row-4","endpoint":"group-b","requests":30,"latency_ms":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_6UQTAGeyKmBiw1ar0S8g6","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 string fields (endpoint names, dates) across up to 200 API usage records for consistent, clean analytics","exampleAgentPrompt":"Can you normalise the string fields in my API usage records? I have about 50 rows with endpoint names like 'group-a' and 'group-b', dates in YYYY-MM-DD format, plus request counts and latency values — they need to be cleaned up and standardised before I run my analytics.","exampleUseCases":[{"title":"Cleaning messy endpoint labels before reporting","prompt":"I've got 120 rows of API usage logs where the endpoint names are inconsistent — some are camelCase, some have trailing spaces, some use hyphens — can you normalise all the string fields so I can get a clean breakdown by endpoint?"},{"title":"Preprocessing API data for dashboard ingestion","prompt":"Before I load my API usage data into the dashboard, I need to normalise the string values across all 180 records — endpoint names and dates especially — can you run the string normalisation on them?"},{"title":"Standardising API logs from multiple sources","prompt":"I've merged API usage records from three different services and the endpoint name strings are all over the place. Can you normalise the strings across my 90 rows so the endpoint labels are consistent and the dates are all in a standard format?"}],"resultDescription":"Returns up to 200 API usage records with string fields (endpoint names, dates) normalised and cleaned — standardised casing, trimmed whitespace, consistent formatting — ready for downstream analytics or reporting pipelines.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, endpoint, date, requests, latency_ms) causes record rejection","Invalid date format (not YYYY-MM-DD) may result in processing error","Numeric fields outside allowed range trigger validation failure","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you have API usage records with inconsistent or messy string fields — particularly endpoint names and dates — and need a lightweight, local normalisation pass before analytics. It handles up to 200 records per call at very low cost ($0.01 USDC) and performs no external enrichment, making it ideal for deterministic, repeatable data cleaning steps in an analytics pipeline.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:52.577Z","isFirstParty":false,"canonicalSlug":"api-usage-string-normalisation-5f73c96f"}