feat(schemas): plays scalar — close forecast↔delivery asymmetry - #3583
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Add `plays` to delivery-metrics.json (top-level, type:number) and available-metric.json enum. Mirrors the forecastable-metric.plays declaration so buyers reconciling DOOH/broadcast delivery against forecast have a 1:1 metric pairing. Distinct from dooh_metrics.loop_plays (per-screen rotation count) and impressions (multiplied audience figure). Top-level placement (Option A from the triage discussion) instead of nesting in dooh_metrics — the forecast side declares plays at the same level as impressions/views, broadcast inventory uses it too (not DOOH-only), and the type matches other top-level count scalars (number, not the integer used inside dooh_metrics). Closes #3516. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Summary
Add
playstodelivery-metrics.json(top-level,type: number) andavailable-metric.jsonenum. Closes the forecast↔delivery asymmetry whereplayswas declared as a forecastable metric (forecastable-metric.json:23,forecast-point.json:38) but absent from delivery reporting. Closes #3516.Why top-level (Option A)
playsat the same level asimpressions/viewsonforecast-point. Mirroring placement on the delivery side makes forecast↔delivery reconciliation a 1:1 pairing.dooh_metricswould force a separate field for broadcast plays.number, not theintegerused insidedooh_metrics.Distinct from neighbors
dooh_metrics.loop_plays— per-screen rotation count (a screen plays the same creative N times in a loop).playsis the campaign-level total across all screens.impressions— multiplied audience figure (one play × screen audience = many impressions).playsis the raw play count before any audience multiplier.Both distinctions are spelled out in the schema description.
Backwards compatibility
Optional and additive. Existing reports without
playsstay conformant.Test plan
npm run build:schemas— cleannpm run test:schemas— 7/7npm run test:examples— 34/34npm run typecheck— cleanCloses #3516.
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