{"uid":"cap_v_5EuR5p1cKbpyabYF-Su","slug":"simulation-caches-numeric-distribution-iqr-outlier-flags-eecdc353","name":"Simulation Caches — Numeric Distribution + IQR Outlier Flags","description":"Simulation caches — Numeric distribution + IQR outlier flags: Numeric distribution + IQR outlier flags 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-08-080?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"}}},"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_R9vUtWak7dU8Q2r0Jqjwt","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":"Computes numeric distribution statistics and IQR-based outlier flags for simulation cache records (cache_gb and simulation_seconds) across up to 200 supplied rows.","exampleAgentPrompt":"Analyze my simulation cache records for outliers — here are 4 rows with cache_gb and simulation_seconds values (row-1: 10 GB / 1s, row-2: 20 GB / 2s, row-3: 15 GB / 3s, row-4: 300 GB / 4s) and give me the numeric distribution plus IQR outlier flags for cache_gb.","exampleUseCases":[{"title":"Detecting bloated simulation caches","prompt":"I have 50 simulation records with cache_gb and simulation_seconds for different asset groups — can you run the numeric distribution and IQR outlier detection on cache_gb so I can find which simulations are using abnormally large caches?"},{"title":"QA check on simulation runtimes","prompt":"Here are 120 rows of simulation logs with row IDs, asset groups, dates, cache sizes, and runtimes — flag any simulation_seconds values that are IQR outliers and give me the full distribution stats so I can catch runaway jobs."},{"title":"Asset group cache size audit","prompt":"I need to audit our simulation infrastructure — I've got 80 records across two asset groups with cache_gb values. Can you compute the numeric distribution and mark which rows are outliers using IQR for cache_gb?"}],"resultDescription":"Returns two independent analytical reports (one per numeric field): descriptive distribution statistics (min, max, mean, median, quartiles, etc.) and IQR-based outlier flags identifying which rows fall outside the interquartile range bounds, covering up to 200 input rows.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — exceeds batch limit","Missing required fields (row_id, date, cache_gb, simulation_seconds) — validation error","Malformed date format (not YYYY-MM-DD) — schema validation failure","Non-numeric values in cache_gb or simulation_seconds where number expected — type error","Payment of 0.01 USDC not attached or fails — 402 Payment Required"],"whenToPreferThis":"Choose this endpoint when you have a batch of simulation cache records (up to 200 rows) and need both distribution statistics and IQR-based outlier detection for cache_gb and/or simulation_seconds in a single low-cost call. It is purpose-built for simulation infrastructure data with the specific fields cache_gb, simulation_seconds, asset_group, and date — prefer it over generic stats APIs when your data matches this schema exactly.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T00:48:44.483Z","isFirstParty":false,"canonicalSlug":"simulation-caches-numeric-distribution-iqr-outlier-flags-eecdc353"}