{"uid":"cap_IBn1W44G1v_GkuUZZioLx","slug":"cache-observations-date-by-category-pivot-8a064403","name":"Cache Observations – Date by Category Pivot","description":"Cache observations - Date by category pivot: Date by category pivot for Cache 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 date by category pivot report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-cache-observations-pivot?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","cache","date","hits","misses"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"hits":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"cache":{"type":"string","default":"","maxLength":80},"misses":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1}},"additionalProperties":false},"default":[{"date":"2026-10-01","hits":10,"cache":"group-a","misses":1,"row_id":"row-1"},{"date":"2026-10-02","hits":20,"cache":"group-b","misses":2,"row_id":"row-2"},{"date":"2026-10-03","hits":15,"cache":"group-a","misses":3,"row_id":"row-3"},{"date":"2026-10-04","hits":30,"cache":"group-b","misses":4,"row_id":"row-4"}],"maxItems":200,"minItems":1},"field":{"enum":["hits","misses"],"type":"string","default":"hits"}}},"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_nDSUttMu7bJ-OwwZOuCKZ","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":"Pivots up to 200 cache observation records (hits/misses) by date and cache category, returning a local descriptive analytics summary table.","exampleAgentPrompt":"Can you pivot my cache observation data by date and cache group, using hits as the metric? I have records for group-a and group-b across several dates in October 2026 — up to 200 rows total.","exampleUseCases":[{"title":"Daily cache hit breakdown by group","prompt":"I have a list of cache observation rows with dates, cache group names, and hit counts — can you pivot them so I can see hits for each cache group per day? Use 'hits' as the field."},{"title":"Cache miss trend analysis across categories","prompt":"Take my cache observation records for the past week — each row has a date, a cache name, and miss counts — and give me a date-by-category pivot using misses so I can spot which cache is underperforming on which days."},{"title":"QA report on cache performance data","prompt":"I've got up to 150 cache observation records tagged with dates and cache group labels, and I want a pivot table showing misses per cache category per date so my team can review performance patterns locally."}],"resultDescription":"A date-by-category pivot report summarizing the chosen metric (hits or misses) across all supplied cache observation records, organized with dates as one axis and cache category names as the other. The report is purely local descriptive analytics with no enrichment or forecasting.","failureModes":["Fewer than 1 row supplied — minimum items constraint violated","More than 200 rows supplied — maxItems constraint exceeded","Missing required fields (row_id, cache, date, hits, misses) on any row","Date field not matching YYYY-MM-DD format","Invalid field enum value (must be 'hits' or 'misses')","Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000)","Payment not completed — x402 payment required at $0.01 USDC"],"whenToPreferThis":"Choose this endpoint when you have raw cache observation records (hits and misses) already on hand and need a fast, cheap local pivot table grouped by date and cache category — without any external enrichment, forecasting, or complex transformation. It's ideal for quick descriptive analytics on cache performance data when you want a structured cross-tab output for up to 200 rows at minimal cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T18:57:20.752Z","isFirstParty":false,"canonicalSlug":"cache-observations-date-by-category-pivot-8a064403"}