{"uid":"cap_D4BcyqSaRqqvOUJRQdhNj","slug":"simulation-caches-numeric-interval-filter-adjacent-row-changes-eb7a1ca9","name":"Simulation Caches — Numeric Interval Filter + Adjacent Row Changes","description":"Simulation caches — Numeric interval filter + Adjacent row changes: Numeric interval filter + Adjacent row changes for supplied simulation caches records (cache_gb, simulation_seconds). 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-creative-08-127?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","cache_gb","simulation_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"cache_gb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"asset_group":{"type":"string","default":"","maxLength":80},"simulation_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","cache_gb":10,"asset_group":"group-a","simulation_seconds":1},{"date":"2026-10-02","row_id":"row-2","cache_gb":20,"asset_group":"group-b","simulation_seconds":2},{"date":"2026-10-03","row_id":"row-3","cache_gb":15,"asset_group":"group-a","simulation_seconds":3},{"date":"2026-10-04","row_id":"row-4","cache_gb":30,"asset_group":"group-b","simulation_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["cache_gb","simulation_seconds"],"type":"string","default":"cache_gb"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_hK3X2QjYWTnMNggqh3GOo","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":"Filters simulation cache rows by a numeric interval on cache_gb or simulation_seconds, and computes adjacent row changes, returning two analytical reports for up to 200 supplied rows.","exampleAgentPrompt":"I have a list of simulation cache records with cache_gb and simulation_seconds values — can you filter for rows where cache_gb is between 10 and 50, and also show me the adjacent row changes for that field? Here are up to 200 rows with row_id, asset_group, and date included.","exampleUseCases":[{"title":"Identify oversized simulation cache entries","prompt":"I've got simulation cache records for our asset groups and I need to find all entries where cache_gb falls between 20 and 100, plus I want to see how cache_gb changes from one row to the next. Here are the rows — row_id, asset_group, date, cache_gb, and simulation_seconds all included."},{"title":"Spot simulation runtime outliers in range","prompt":"Can you filter these simulation cache rows so I only see the ones where simulation_seconds is between 5 and 60, and also give me the adjacent row changes for simulation_seconds so I can see where big jumps happen?"},{"title":"Cross-group cache delta analysis","prompt":"I have simulation cache data across group-a and group-b for October 2026 and I want two things: filter the rows to only those with cache_gb between 0 and 25, and show me the row-over-row difference in cache_gb so I can track how it's growing."}],"resultDescription":"Returns two analytical reports: (1) rows from the input dataset whose specified numeric field (cache_gb or simulation_seconds) falls within the provided minimum–maximum interval, and (2) adjacent row changes (deltas) for that same numeric field across all supplied rows. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Input array is empty or exceeds 200 rows — validation error","Minimum value is greater than maximum value — invalid interval error","Required row fields (row_id, date, cache_gb, simulation_seconds, asset_group) missing — schema validation error","Field enum value not recognized (must be cache_gb or simulation_seconds) — invalid field error","Numeric values outside allowed range (-1e12 to 1e12) — validation error","Date field does not match YYYY-MM-DD pattern — format error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 simulation cache records with cache_gb and simulation_seconds columns and need both numeric interval filtering and adjacent row delta analysis in a single call. It is ideal when you want to identify which simulation entries fall within a specific size or duration range while simultaneously tracking row-over-row changes, without any live data lookup or external enrichment. Prefer this over general-purpose analytics tools when your data fits the simulation caches schema and you want a low-cost ($0.01 USDC), fast, self-contained dual-report output.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T18:55:45.950Z","isFirstParty":false,"canonicalSlug":"simulation-caches-numeric-interval-filter-adjacent-row-changes-eb7a1ca9"}