{"uid":"cap_DFE9V60smPr_PKs_55PY6","slug":"service-availability-observations-string-normalisation-ccfecfa4","name":"Service Availability Observations – String Normalisation","description":"Service availability observations - String normalisation: String normalisation for Service availability observations. 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-service-availability-normalise?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","service","date","observed_minutes","outage_minutes"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"service":{"type":"string","default":"","maxLength":80},"outage_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"observed_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","service":"group-a","outage_minutes":1,"observed_minutes":10},{"date":"2026-10-02","row_id":"row-2","service":"group-b","outage_minutes":2,"observed_minutes":20},{"date":"2026-10-03","row_id":"row-3","service":"group-a","outage_minutes":3,"observed_minutes":15},{"date":"2026-10-04","row_id":"row-4","service":"group-b","outage_minutes":4,"observed_minutes":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_SlqJ0MQ02-9u8lWkRlbOf","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 (service names, dates) across up to 200 service availability observation records for local descriptive analytics.","exampleAgentPrompt":"Can you normalise the service name and date strings in my availability dataset? I have 4 records: row-1 on 2026-10-01 for group-a with 1 outage minute out of 10 observed, row-2 on 2026-10-02 for group-b with 2 outage minutes out of 20 observed, row-3 on 2026-10-03 for group-a with 3 out of 15, and row-4 on 2026-10-04 for group-b with 4 out of 30.","exampleUseCases":[{"title":"SLA Report Data Cleanup","prompt":"I've collected daily uptime observations for our two services 'Prod-API' and 'prod_api' and they're showing up as different groups — can you normalise the service name strings across these 12 records so they all match before I run my SLA report? Dates are formatted as 2026-11-01 through 2026-11-12, observed minutes around 1440 daily, and outage minutes range from 0 to 45."},{"title":"Incident Log Pre-processing","prompt":"Before I analyse last month's outage data, can you clean up the string fields in these 50 service availability records? The service names have inconsistent casing and spacing like 'Auth Service', 'auth-service', and 'AUTH_SERVICE' — I need them standardised. Dates are in YYYY-MM-DD format and outage minutes are all filled in."},{"title":"Multi-team Availability Data Merge","prompt":"We merged availability logs from three teams and the service name strings are a mess — things like 'payments', 'Payments', and 'payment-svc' all mean the same service. Can you run string normalisation on these 80 records so I can pivot and aggregate properly? Each row has a date, service name, observed minutes, and outage minutes."}],"resultDescription":"Returns a bounded string normalisation report covering up to 200 service availability records, with standardised service name strings and date fields ready for local descriptive analytics. No forecasting or external enrichment is included.","failureModes":["Exceeds 200-row limit — request rejected with validation error","Missing required fields (row_id, service, date, observed_minutes, outage_minutes) — row-level validation failure","Date strings not matching YYYY-MM-DD pattern — schema validation error","Numeric fields out of allowed range — schema rejection","Empty rows array — minimum items violation"],"whenToPreferThis":"Choose this endpoint when you need lightweight, cost-effective string normalisation specifically for service availability observation records (uptime/outage minute data) and want a local descriptive report without enrichment or forecasting. Ideal for pre-processing before analytics pipelines or SLA reporting when batch size is 200 records or fewer.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-14T11:57:28.026Z","isFirstParty":false,"canonicalSlug":"service-availability-observations-string-normalisation-ccfecfa4"}