Add deterministic repro bundle recording and headless replay

[RtlZeroMemory]

Summary

• add a versioned rezi-repro-v1 schema with strict validation and deterministic stable serialization in @rezi-ui/core
• add createReproRecorder in @rezi-ui/node to capture bounded backend event batches (maxBatches, maxEvents, maxBytes) with deterministic truncation metadata and return bundle object/bytes without filesystem writes
• add a headless replay harness in core that replays recorded batches through createApp using a stub backend, captures routed actions, and reports PASS/FAIL with structured mismatches
• add a committed repro fixture (packages/testkit/fixtures/repro/replay_resize_tab_text.json) and deterministic replay tests (PASS path + failure diff path + invariant checks)
• document record/replay usage, schema fields, determinism, and privacy notes in docs/guide/record-replay.md

Why

This makes bug reports reproducible in CI by recording deterministic input/resize sessions and replaying them headlessly with assertable routing outcomes.

Validation

• npm run lint
• npm run typecheck
• npm run build
• npm test
• npm run test:e2e
• npm run test:e2e:reduced
• npm run test:native:smoke

[chatgpt-codex-connector]

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[chatgpt-codex-connector]

Inject bootstrap resize when first batch lacks viewport event

This condition only prepends a synthetic resize when no batch in the bundle has resize metadata, so bundles that contain a resize later (but start with key/text input) are replayed without an initial committed viewport. In that scenario createApp cannot build the first frame before the later resize arrives, so early routable events are dropped and the harness reports action mismatches for otherwise valid recordings (for example, captures started after app bootstrap).

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[chatgpt-codex-connector]

Replace fixed spin cap with replay-completion waiting

The harness exits the drain loop after spins < 4000 even if batches are still being processed, then turns that into ZR_REPLAY_TIMEOUT. Because capture bounds are configurable and scheduler throughput is workload-dependent, larger or slower replays can fail with a timeout despite making forward progress, which creates false FAIL results unrelated to routing correctness.

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