{"uid":"cap_QhD8hPcZLerf7-0cL2wuP","slug":"company-filing-inventories-numeric-distribution-trailing-mean-series-47d474f8","name":"Company Filing Inventories — Numeric Distribution + Trailing Mean Series","description":"Company filing inventories — Numeric distribution + Trailing mean series: Numeric distribution + Trailing mean series for supplied company filing inventories records (available_filings, expected_filings). 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-company-17-076?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","available_filings","expected_filings"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_group":{"type":"string","default":"","maxLength":80},"expected_filings":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"available_filings":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","expected_filings":1,"available_filings":10},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","expected_filings":2,"available_filings":20},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","expected_filings":3,"available_filings":15},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","expected_filings":4,"available_filings":30}],"maxItems":200,"minItems":1},"field":{"enum":["available_filings","expected_filings"],"type":"string","default":"available_filings"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_r41eZyvu3moXuqVHh9dFU","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 a trailing mean series for supplied company filing inventory data (available_filings, expected_filings) across up to 200 rows.","exampleAgentPrompt":"Run a numeric distribution analysis and trailing mean series (window of 7) on my company filing inventory data — I have records for two groups, 'alpha-corp' and 'beta-corp', with dates and available_filings values, and I want both reports for the available_filings field.","exampleUseCases":[{"title":"Filing compliance gap analysis","prompt":"I have 150 rows of company filing data with available_filings and expected_filings for several company groups over the past quarter. Can you compute the numeric distribution and a trailing mean with a window of 10 for the expected_filings field so I can see where filings are falling short?"},{"title":"Monthly filing inventory trend review","prompt":"Analyze my company filing inventory records — about 80 rows covering groups 'retail-div' and 'tech-div' across October — and give me the numeric distribution plus a trailing mean series using a window of 5 for available_filings."},{"title":"Comparing filing availability across groups","prompt":"I've got filing inventory data for three company groups over the last 6 months, up to 200 rows total. Run the numeric distribution and trailing mean (window of 14) on available_filings so I can compare how consistently each group has filings on hand."}],"resultDescription":"Returns two analytical reports: (1) a numeric distribution breakdown of the selected field (available_filings or expected_filings) across the supplied rows, and (2) a trailing mean series computed over the specified window size — both generated locally without external lookups.","failureModes":["Fewer than 1 or more than 200 rows submitted — validation error","Window size smaller than 2 or larger than 200 — rejected input","Invalid date format (not YYYY-MM-DD) — schema validation failure","Non-numeric values in available_filings or expected_filings where numbers are required","Missing required fields (row_id, date, company_group) — row rejected","Payment of 0.01 USDC not completed — request blocked by x402 protocol"],"whenToPreferThis":"Choose this endpoint when you have structured company filing inventory records (available_filings, expected_filings) and need both a distribution summary and a rolling mean series in a single low-cost call. It is ideal for offline/batch analytical workflows where no live data lookup or external enrichment is needed — all computation runs locally on supplied data. Best suited for datasets of up to 200 rows where cost efficiency ($0.01 for two reports) matters.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T18:57:13.872Z","isFirstParty":false,"canonicalSlug":"company-filing-inventories-numeric-distribution-trailing-mean-series-47d474f8"}