{"uid":"cap_vKDncK8lTGE7g-U3GUMcU","slug":"camera-coverage-string-normalisation-and-keyed-dataset-comparison-4c1c37b4","name":"Camera Coverage String Normalisation and Keyed Dataset Comparison","description":"Camera coverage — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison for supplied camera coverage records (shot_count, coverage_seconds). 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 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strings and performs keyed dataset comparison on two sets of camera coverage records (shot_count, coverage_seconds), producing 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"Compare these two sets of camera coverage records — I have a primary dataset and a secondary dataset each with up to 50 rows of shot_count and coverage_seconds by asset_group and date, and I want a normalised string comparison report highlighting any differences between the two.","exampleUseCases":[{"title":"Post-production shot count reconciliation","prompt":"I have two exports from our camera logging system for October 2026 — can you normalise the asset group names and compare them row by row so I can see where shot_count or coverage_seconds differ between the two files?"},{"title":"Daily coverage audit across camera groups","prompt":"Run a keyed comparison on these two camera coverage datasets — both have about 80 rows with asset_group, date, shot_count, and coverage_seconds — and tell me which rows have inconsistencies after string normalisation."},{"title":"Pre-delivery data validation for camera logs","prompt":"Before I hand off these camera coverage logs, can you normalise the strings and compare my current dataset against last week's baseline to flag any rows where coverage_seconds or shot_count don't match by row_id?"}],"resultDescription":"Returns 2 analytical reports: one covering string normalisation results (standardised asset_group labels and date fields) and one covering keyed dataset comparison results (row-by-row differences in shot_count and coverage_seconds between the primary and secondary datasets), for up to 200 rows total.","failureModes":["More than 200 rows submitted — request rejected","Missing required fields (row_id, asset_group, date, shot_count, coverage_seconds) — validation error","Date field does not match YYYY-MM-DD pattern — schema validation failure","Numeric fields outside allowed range — rejection","Empty rows array — minimum 1 item required"],"whenToPreferThis":"Choose this endpoint when you need to locally compare two structured camera coverage datasets (shot_count, coverage_seconds) with string normalisation and keyed row-by-row diffing, without any live data lookup, external enrichment, or prediction. Ideal for post-production reconciliation, audit workflows, or pre-delivery QA checks on camera log exports of up to 200 rows at low cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T12:42:04.675Z","isFirstParty":false,"canonicalSlug":"camera-coverage-string-normalisation-and-keyed-dataset-comparison-4c1c37b4"}