{"uid":"cap_mBT8xaMPdKIlAk7Lx5JmD","slug":"product-feature-telemetry-iqr-outlier-flags-ef4530c4","name":"Product Feature Telemetry – IQR Outlier Flags","description":"Product feature telemetry - IQR outlier flags: IQR outlier flags for Product feature telemetry. 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 iqr outlier flags report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-feature-telemetry-outliers?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","feature","date","events","unique_users"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"events":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"feature":{"type":"string","default":"","maxLength":80},"unique_users":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","events":10,"row_id":"row-1","feature":"group-a","unique_users":1},{"date":"2026-10-02","events":20,"row_id":"row-2","feature":"group-b","unique_users":2},{"date":"2026-10-03","events":15,"row_id":"row-3","feature":"group-a","unique_users":3},{"date":"2026-10-04","events":30,"row_id":"row-4","feature":"group-b","unique_users":4}],"maxItems":200,"minItems":1},"field":{"enum":["events","unique_users"],"type":"string","default":"events"}}},"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_-Bah9lph7MQYUNmQykJjH","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":"Detects IQR-based outliers in product feature telemetry rows (events or unique_users) and returns a bounded outlier flags report for up to 200 records.","exampleAgentPrompt":"Can you flag the IQR outliers in this product feature telemetry data? I have 20 rows with row_id, feature, date, events, and unique_users — please check the events field for any outliers.","exampleUseCases":[{"title":"Spike detection in feature rollout","prompt":"I just ran a feature rollout and have 50 rows of daily telemetry with event counts per feature group. Can you flag any IQR outliers in the events field so I know which days had abnormal spikes?"},{"title":"Unusual user activity by feature","prompt":"Here's 30 rows of product telemetry — each row has a feature name, date, and unique_users count. Flag any rows where unique_users is an IQR outlier so I can investigate anomalies before my report."},{"title":"QA check on ingested telemetry batch","prompt":"Before I archive this batch of 120 feature telemetry records, can you run an IQR outlier check on the events column and tell me which row_ids are flagged as outliers?"}],"resultDescription":"A bounded report listing which of the supplied telemetry rows are flagged as IQR outliers for the chosen field (events or unique_users), based on local descriptive statistics computed over the submitted batch — no external enrichment or forecasting.","failureModes":["Empty or missing rows array returns a validation error","row_id missing or exceeds 80 characters causes schema rejection","date field not matching YYYY-MM-DD pattern fails validation","field enum value not 'events' or 'unique_users' returns error","Submitting more than 200 rows exceeds maxItems limit","Numeric values outside ±1,000,000,000,000 fail schema bounds"],"whenToPreferThis":"Choose this endpoint when you need fast, local IQR-based outlier detection on a batch of up to 200 product feature telemetry records without requiring external data enrichment or forecasting. It is ideal for QA pipelines, pre-archive checks, and quick anomaly flagging on events or unique_users metrics grouped by feature and date.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T00:52:33.588Z","isFirstParty":false,"canonicalSlug":"product-feature-telemetry-iqr-outlier-flags-ef4530c4"}