{"uid":"cap_AdvDC6H_7tlDyWR8T89jF","slug":"inventory-administration-string-normalisation-and-keyed-dataset-c1d6a2f3","name":"Inventory Administration String Normalisation and Keyed Dataset Comparison","description":"Inventory administration — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison for supplied inventory administration records (count_sessions, discrepancy_count). 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-operations-21-036?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","team_group","date","count_sessions","discrepancy_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"team_group":{"type":"string","default":"","maxLength":80},"count_sessions":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"discrepancy_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","team_group":"group-a","count_sessions":10,"discrepancy_count":1},{"date":"2026-10-02","row_id":"row-2","team_group":"group-b","count_sessions":20,"discrepancy_count":2},{"date":"2026-10-03","row_id":"row-3","team_group":"group-a","count_sessions":15,"discrepancy_count":3},{"date":"2026-10-04","row_id":"row-4","team_group":"group-b","count_sessions":30,"discrepancy_count":4}],"maxItems":200,"minItems":1},"other":{"type":"array","items":{"type":"object","required":["row_id","team_group","date","count_sessions","discrepancy_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"team_group":{"type":"string","default":"","maxLength":80},"count_sessions":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"discrepancy_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","team_group":"group-a","count_sessions":10,"discrepancy_count":1},{"date":"2026-10-02","row_id":"row-2","team_group":"group-b","count_sessions":21,"discrepancy_count":2},{"date":"2026-10-03","row_id":"row-3","team_group":"group-a","count_sessions":17,"discrepancy_count":3},{"date":"2026-10-04","row_id":"row-4","team_group":"group-b","count_sessions":33,"discrepancy_count":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_O2IlWMz7NYtdRJK5XhwBk","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":"Normalizes strings and performs keyed dataset comparison on inventory administration records tracking count sessions and discrepancy counts across up to 200 rows.","exampleAgentPrompt":"Compare these two sets of inventory session records — one from our current system and one from the audit — and normalize the team group names, then tell me where count_sessions or discrepancy_count values differ between matching row IDs.","exampleUseCases":[{"title":"Audit reconciliation between two inventory snapshots","prompt":"I have two exports of our warehouse inventory session data from different systems — can you normalize the team group labels and compare them row by row to highlight where count_sessions or discrepancy_count don't match?"},{"title":"Detecting data entry discrepancies across team groups","prompt":"Our inventory admin team entered session counts twice in two different tools. Run string normalization on the team_group fields and compare the two datasets so I can see which rows have discrepancy_count mismatches."},{"title":"Weekly inventory session cross-check for operations","prompt":"Here are this week's inventory session records from two sources — normalize the strings and do a keyed comparison by row_id so I can see if any count_sessions numbers are off between the two reports."}],"resultDescription":"Returns two analytical reports: one covering string normalization results for team_group and string fields, and one covering keyed dataset comparison between the two supplied row arrays, highlighting differences in count_sessions and discrepancy_count values per row_id. No external data is fetched; all analysis is performed locally on submitted data.","failureModes":["Missing required fields (row_id, team_group, date, count_sessions, discrepancy_count) causes validation failure","Exceeding 200 rows per dataset returns an error","Invalid date format (not YYYY-MM-DD) causes rejection","Empty rows array triggers minimum-items validation error","Malformed JSON body returns a 400-level error"],"whenToPreferThis":"Choose this endpoint when you need to reconcile two sets of inventory administration records locally — specifically when you need both string normalization of categorical fields like team_group AND keyed row-level comparison of numeric metrics (count_sessions, discrepancy_count) in a single cheap call. Ideal for audit workflows, data quality checks, and operational reporting where no external lookups or predictions are needed and datasets are under 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T12:53:39.754Z","isFirstParty":false,"canonicalSlug":"inventory-administration-string-normalisation-and-keyed-dataset-c1d6a2f3"}