{"uid":"cap_0eslKODclaN_VWzJkBbZz","slug":"time-entries-keyed-dataset-comparison-b5d4556a","name":"Time Entries Keyed Dataset Comparison","description":"Time entries - Keyed dataset comparison: Keyed dataset comparison for Time entries. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded keyed dataset comparison deliverable.","url":"https://market.datapackvibe.com/x402/assistant-sector-analytics-time-entries-compare?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","project","date","hours","billable_hours"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"project":{"type":"string","default":"","maxLength":80},"billable_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","hours":10,"row_id":"row-1","project":"group-a","billable_hours":1},{"date":"2026-10-02","hours":20,"row_id":"row-2","project":"group-b","billable_hours":2},{"date":"2026-10-03","hours":15,"row_id":"row-3","project":"group-a","billable_hours":3},{"date":"2026-10-04","hours":30,"row_id":"row-4","project":"group-b","billable_hours":4}],"maxItems":200,"minItems":1},"other":{"type":"array","items":{"type":"object","required":["row_id","project","date","hours","billable_hours"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"project":{"type":"string","default":"","maxLength":80},"billable_hours":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","hours":10,"row_id":"row-1","project":"group-a","billable_hours":1},{"date":"2026-10-02","hours":21,"row_id":"row-2","project":"group-b","billable_hours":2},{"date":"2026-10-03","hours":17,"row_id":"row-3","project":"group-a","billable_hours":3},{"date":"2026-10-04","hours":33,"row_id":"row-4","project":"group-b","billable_hours":4}],"maxItems":200,"minItems":0}}},"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_hqnGAjjJTiYhwbJM0fLCD","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":"Compares two keyed datasets of time entry records (up to 200 rows each) and returns data-quality and numeric difference analysis between them.","exampleAgentPrompt":"Compare these two sets of time entries for me — the original has row-1 through row-4 with 10, 20, 15, and 30 hours logged across group-a and group-b projects, and the updated version has the same rows but with 10, 21, 17, and 33 hours — tell me what changed in total hours and billable hours.","exampleUseCases":[{"title":"Timesheet reconciliation before payroll","prompt":"I have two exports of our team's time entries for October — the first is what employees submitted and the second is what got approved. Can you compare them row by row and tell me where the hours or billable hours changed, so I can flag discrepancies before we run payroll?"},{"title":"Detecting billing errors across project groups","prompt":"We have a before-and-after snapshot of time entries for our client projects — can you diff the two datasets keyed by row ID and surface any rows where billable hours don't match, so we can catch billing errors before invoicing?"},{"title":"Audit trail for time tracking system migration","prompt":"We just migrated our time tracking system and I need to verify the data came over correctly. I have the original time entries and the migrated ones — compare them for me and highlight any rows where hours or project assignments differ."}],"resultDescription":"Returns a bounded keyed dataset comparison deliverable that includes per-row numeric differences in hours and billable_hours fields, matched/unmatched row identification by row_id, and data-quality metrics across the two supplied time entry arrays.","failureModes":["Rows array exceeds 200 items — request rejected with validation error","Missing required fields (row_id, project, date, hours, billable_hours) on any row — schema validation failure","Invalid date format (not YYYY-MM-DD) — pattern validation error","Numeric values outside allowed range — validation error","Empty rows array — minItems constraint violation","Mismatched row_ids between datasets resulting in all-unmatched comparison"],"whenToPreferThis":"Choose this endpoint when you need a structured, keyed comparison of two time entry datasets (up to 200 rows) with numeric delta analysis, particularly for timesheet auditing, billing reconciliation, or data migration validation. It performs local numeric and data-quality processing without external enrichment, making it fast and deterministic. Prefer this over generic diff tools when your data is specifically time entries with project, date, hours, and billable_hours fields.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T18:48:02.047Z","isFirstParty":false,"canonicalSlug":"time-entries-keyed-dataset-comparison-b5d4556a"}