name: ztp3d-video-3d-fusion-audio-video-sync description: "A/V Synchronization and Drift: specialized Perfect_AI quality workflow for Video × 3D Fusion Engine."

A/V Synchronization and Drift

Where this skill applies

Handle audio latency, playback speed, drift and dropped frames deliberately.

Task-specific implementation plan

Prefer HTMLMediaElement audio clock for common playback; use precise decoded frame seek for editing, with tolerance, queue backpressure, decode batching and frame dropping policy.

Inputs and dependencies

• Existing project source and its installed versions, target browser, 3D scene/camera, ownership rules.
• Parent integration guide: ../ztp3d-video-3d-fusion/SKILL.md.
• Working example and adapter: ../../src/adapters/video-texture.mjs.
• Upstream technical reference: https://github.com/Vanilagy/mediabunny.

Step-by-step operational checklist

1. Inspect target source files and preserve all existing behavior; explicitly name the owner of each component, canvas and animation timeline.
2. Validate input data and preconditions. For missing support, stop gracefully with a useful error and a visible fallback.
3. Implement a/v synchronization and drift through smallest observable patch, preferring local modules, deterministic data and reusable functions.
4. Include edge cases: empty assets, large assets, stale asynchronous work, component unmount, 320px mobile, RTL layout and prefers-reduced-motion.
5. Verify each change independently before enabling it in the full pipeline; record precise reproduction steps.
6. Test final rendering on browser and target device and collect screenshot, console and resource lifecycle evidence.
7. Classify final result as documented / implemented / unit tested / browser tested / actual GPU tested.

Targeted acceptance tests

Measure drift for 30 seconds on target device; report tolerance in milliseconds.

Failure and rollback

• If a feature is unavailable, keep prior renderer or accessible HTML content intact and report why.
• If perf regresses, turn off the optional effect/plugin through an explicit feature flag.
• Do not change or delete upstream Perfect_AI skills; add new files or narrowly patch the destination application only on request.
• Always distinguish simulated/browser/device evidence.

Example deliverables

• Implementation diff and dependency changes; deterministic fixture and tested commands.
• Baseline/target render screenshots and p95 frame-time notes where GPU work is involved.
• List of remaining limitations, security/privacy and licensing issues.