{"uid":"cap_3zlR0MZwd7bQfNHv4nJv2","slug":"subscription-billing-credits-string-normalisation-147cd1cd","name":"Subscription Billing Credits – String Normalisation","description":"Subscription billing credits - String normalisation: String normalisation for Subscription billing credits. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded string normalisation report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-billing-credits-normalise?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","provider","date","invoiced_amount","credited_amount"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"provider":{"type":"string","default":"","maxLength":80},"credited_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"invoiced_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","provider":"group-a","credited_amount":1,"invoiced_amount":10},{"date":"2026-10-02","row_id":"row-2","provider":"group-b","credited_amount":2,"invoiced_amount":20},{"date":"2026-10-03","row_id":"row-3","provider":"group-a","credited_amount":3,"invoiced_amount":15},{"date":"2026-10-04","row_id":"row-4","provider":"group-b","credited_amount":4,"invoiced_amount":30}],"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_AouOJyMAUxnsYT71HrhVu","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 (provider names, dates, etc.) across up to 200 subscription billing credit records and returns a local descriptive analytics report.","exampleAgentPrompt":"Can you normalise the string fields in my subscription billing credits data? I have 4 records with providers 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, invoiced amounts of 10, 20, 15, and 30, and credited amounts of 1, 2, 3, and 4.","exampleUseCases":[{"title":"Cleaning messy SaaS vendor names","prompt":"I've got 150 subscription billing credit rows where provider names are inconsistent — things like 'AWS', 'Amazon Web Services', 'amazon-ws' all meaning the same thing. Can you run string normalisation on them so I get a clean, standardised report? Dates are in YYYY-MM-DD format and I have invoiced and credited amounts for each row."},{"title":"Pre-analytics data prep for finance team","prompt":"Before my finance team runs their monthly billing reconciliation, I need the provider and date strings in our 80 subscription credit records cleaned up and normalised. Can you process these rows — each has a row_id, provider, date, invoiced_amount, and credited_amount — and give me a descriptive analytics report?"},{"title":"Auditing credits from multiple billing providers","prompt":"We receive subscription credits from about 12 different providers and the naming is all over the place across our 200 records. Can you normalise all the string fields and give me a bounded normalisation report so I can see what's been standardised?"}],"resultDescription":"A bounded string normalisation report covering up to 200 billing credit records, with standardised provider names, cleaned date strings, and local descriptive analytics summarising the normalised dataset. No external enrichment or forecasting is included.","failureModes":["Fewer than 1 row supplied — validation error","More than 200 rows supplied — exceeds maxItems limit","Date field does not match YYYY-MM-DD pattern — schema validation failure","Missing required fields (row_id, provider, date, invoiced_amount, credited_amount) — request rejected","Amounts outside allowed range (±1,000,000,000,000) — schema validation failure","Payment of 0.01 USDC not settled — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you have raw subscription billing credit records with inconsistent or dirty string fields (especially provider names and dates) and need a quick, cheap local normalisation report without external enrichment or forecasting. Ideal for pre-analytics data cleaning pipelines in accounts receivable workflows handling up to 200 records at a time.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-14T00:37:28.710Z","isFirstParty":false,"canonicalSlug":"subscription-billing-credits-string-normalisation-147cd1cd"}