Architectural Invariant Design: Skiko Frame Pacing and Native VSync Lock Invariant
Skiko Frame Pacing and Native VSync Lock Invariant defines an industrial-grade behavioral standard for mobile engineering. Enforces deterministic VSync synchronization between native hardware refresh cycles (CADisplayLink on iOS, platform display clocks on Desktop) and Skiko's Skia-backed rendering pipelines. Prevents frame tearing, dropped redraw buffers, jitter, and excessive GPU queue depth caused by unsynchronized polling loops or decoupled coroutine render drivers. Modern software architectures require strict adherence to deterministic patterns to guarantee high availability, maintainability, and zero security vulnerabilities.
Hazard Analysis: What Breaks Without This Rule
The following failure modes have been cataloged from hundreds of hours of production code reviews where AI assistants produced non-compliant implementations:
| Failure Mode | AI Symptom (The Anti-Pattern) | Severity | Production Impact & Remedy |
|---|---|---|---|
| AI Hallucination & Deprecation Drift | Decoupled Coroutine Loop or Unthrottled Polling Driving Skiko Canvas Redraws | Critical | Violating this industrial standard introduces regression bugs, security risks, and unexpected runtime failures in production. Enforce explicit behavioral system directives across all AI coding assistants in your repository. |
| Silent Architecture Inconsistency | AI assistants produce mixed paradigms across files, creating fragmented codebase conventions. | Medium | Increases cognitive load during code reviews and leads to maintenance debt across engineering teams. Pin project conventions in .cursor/rules, CLAUDE.md, and AGENTS.md so all team agents follow identical guardrails. |
Step-by-Step Production Directives
Each rule constraint below is injected into the AI agent's system prompt to establish deterministic boundaries:
Engineers MUST ALWAYS bind Skiko draw invalidation directly to native display signals (CADisplayLink on iOS, CVDisplayLink on macOS, or platform-managed swap chains).
Engineers MUST ALWAYS bind Skiko draw invalidation directly to native display signals (CADisplayLink on iOS, CVDisplayLink on macOS, or platform-managed swap chains).
Engineers MUST NOT trigger Skiko render passes inside autonomous coroutines using fixed time steps like `delay(16)` or unconstrained `while(isActive)` loops.
Engineers MUST NOT trigger Skiko render passes inside autonomous coroutines using fixed time steps like `delay(16)` or unconstrained `while(isActive)` loops.
Code MUST throttle Skia canvas invalidations when the window or view is hidden, occluded, or running in background state to eliminate GPU wake-locks.
Code MUST throttle Skia canvas invalidations when the window or view is hidden, occluded, or running in background state to eliminate GPU wake-locks.
Services MUST ensure that frame timestamps passed to animations originate from native hardware clock ticks rather than host system wall time (`currentTimeMillis()`).
Services MUST ensure that frame timestamps passed to animations originate from native hardware clock ticks rather than host system wall time (`currentTimeMillis()`).
Components NEVER execute blocking operations, file I/O, or heavy recomposition allocations within the synchronized `onRender` or Skiko draw callbacks.
Components NEVER execute blocking operations, file I/O, or heavy recomposition allocations within the synchronized `onRender` or Skiko draw callbacks.
Frequently Asked Technical Questions
Common questions developers face when configuring AI coding assistants for this stack:
Q:Why is Skiko Frame Pacing and Native VSync Lock Invariant critical for AI coding assistants?
Enforces deterministic VSync synchronization between native hardware refresh cycles (CADisplayLink on iOS, platform display clocks on Desktop) and Skiko's Skia-backed rendering pipelines. Prevents frame tearing, dropped redraw buffers, jitter, and excessive GPU queue depth caused by unsynchronized polling loops or decoupled coroutine render drivers. Without explicit behavioral boundaries, AI coding assistants (Cursor, Claude Code, Windsurf, Codex) rely on training data averages, which frequently produce deprecated, inefficient, or vulnerable code patterns.
Q:How does adopting this rule prevent AI hallucinations?
This rule explicitly declares what the AI must avoid (Decoupled Coroutine Loop or Unthrottled Polling Driving Skiko Canvas Redraws) and prescribes verified positive examples. Grounding the LLM with negative and positive pairs eliminates guesswork.
Q:Which AI coding environments are supported?
This specification is multi-platform compatible: Cursor (.cursor/rules/*.mdc & .cursorrules), Anthropic Claude Code (CLAUDE.md), Windsurf (.windsurfrules), Codex / Cline (AGENTS.md), and GitHub Copilot (.github/copilot-instructions.md).
Q:Can I combine this rule with other technology stacks?
Yes. Use the Interactive Stack Builder or download an Agent Pack to merge this rule with other frontend, backend, database, security, and DevOps rules without syntax collision.