{"uid":"cap_4PTJymHktlLB3jHorYWrH","slug":"metadata-completeness-numeric-distribution-iqr-outlier-flags-85237c0e","name":"Metadata Completeness — Numeric Distribution + IQR Outlier Flags","description":"Metadata completeness — Numeric distribution + IQR outlier flags: Numeric distribution + IQR outlier flags for supplied metadata completeness records (present_fields, expected_fields). 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-web-05-080?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","site_group","date","present_fields","expected_fields"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"site_group":{"type":"string","default":"","maxLength":80},"present_fields":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"expected_fields":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","site_group":"group-a","present_fields":10,"expected_fields":1},{"date":"2026-10-02","row_id":"row-2","site_group":"group-b","present_fields":20,"expected_fields":2},{"date":"2026-10-03","row_id":"row-3","site_group":"group-a","present_fields":15,"expected_fields":3},{"date":"2026-10-04","row_id":"row-4","site_group":"group-b","present_fields":30,"expected_fields":4}],"maxItems":200,"minItems":1},"field":{"enum":["present_fields","expected_fields"],"type":"string","default":"present_fields"}}},"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_rqlA8A6HpA2969yuc_vbv","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 metadata completeness records (present_fields, expected_fields) across up to 200 rows, producing 2 independent analytical reports.","exampleAgentPrompt":"Analyze the distribution and flag IQR outliers for these metadata completeness records — I have 50 rows each with a row_id, site_group, date, present_fields, and expected_fields, and I want the report focused on the present_fields column.","exampleUseCases":[{"title":"Audit metadata completeness across site groups","prompt":"I have 120 daily metadata completeness records for three site groups, each with present_fields and expected_fields counts. Can you run a numeric distribution analysis and flag any IQR outliers in the present_fields column so I can spot which records are anomalous?"},{"title":"Detect expected_fields outliers in pipeline output","prompt":"My data pipeline produces completeness snapshots — row_id, site_group, date, present_fields, expected_fields — for about 80 rows this week. Run the IQR outlier detection on the expected_fields column and give me the distribution report."},{"title":"QA check on metadata records before reporting","prompt":"Before I publish my metadata quality report, I want to sanity-check 200 rows of completeness data. Can you compute the numeric distribution and flag IQR outliers for the present_fields values across all those records?"}],"resultDescription":"Returns 2 independent analytical reports covering: numeric distribution statistics (e.g. min, max, mean, median, quartiles) and IQR-based outlier flags for the selected field (present_fields or expected_fields) across the supplied rows, with no external data lookup or prediction involved.","failureModes":["Input array exceeds 200 rows — request will be rejected or truncated","Missing required fields (row_id, site_group, date, present_fields, expected_fields) cause validation errors","Null values in the selected numeric field may affect distribution calculations","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Submitting fewer than 1 row causes a minItems constraint error"],"whenToPreferThis":"Choose this endpoint when you have a batch of up to 200 metadata completeness records and need both distribution statistics and IQR outlier detection in a single call, without requiring external data sources or live lookups. It is ideal for data quality audits, pipeline QA checks, and periodic completeness monitoring where the data is already available client-side.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:33:06.870Z","isFirstParty":false,"canonicalSlug":"metadata-completeness-numeric-distribution-iqr-outlier-flags-85237c0e"}