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/metal-asset-streaming-workflow

Guide Metal game asset residency and streaming for textures, meshes, mipmaps, heaps, residency sets, sparse resources, and fast resource loading. Use when Codex investigates GPU memory pressure, streaming hitches, resource lifetime, texture or mesh upload, sparse texture

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socket
7200 skills5 MCP
Install
$ npx -y skills add gaelic-ghost/socket --skill metal-asset-streaming-workflow --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/metal-asset-streaming-workflow

Context preview

The summary Claude sees to decide when to auto-load this skill.

Guide Metal game asset residency and streaming for textures, meshes, mipmaps, heaps, residency sets, sparse resources, and fast resource loading. Use when Codex investigates GPU memory pressure, streaming hitches, resource lifetime, texture or mesh upload, sparse texture

SKILL.md

metal-asset-streaming-workflow.SKILL.md
name: metal-asset-streaming-workflow
description: Guide Metal game asset residency and streaming for textures, meshes, mipmaps, heaps, residency sets, sparse resources, and fast resource loading. Use when Codex investigates GPU memory pressure, streaming hitches, resource lifetime, texture or mesh upload, sparse texture mapping, or asset budgets in a Metal renderer; do not use for generic asset-catalog or SceneKit resource work.

Metal Asset Streaming Workflow

Scope

Own the GPU-facing asset path: package or source asset, CPU staging, upload, residency, eviction, and use in a frame. Do not hide all asset ownership in a generic cache; name the asset manager and the renderer boundary that consumes it.

Read [streaming-model.md](references/streaming-model.md) before introducing a heap, residency set, sparse resource, or fast-resource-loading path.

Workflow

1. Measure the actual symptom: first-use hitch, sustained stutter, missing detail, out-of-memory termination, or GPU resource-pressure growth. 2. Inventory asset classes, size ranges, mip/LOD behavior, residency lifetime, upload path, and current CPU/GPU ownership. 3. Choose the simplest durable path:

  • ordinary texture or buffer loading for bounded content;
  • explicit heaps or residency sets when allocation and lifetime grouping are the problem;
  • fast resource loading when packaged asset loading is proven to dominate;
  • sparse resources only when content size or streaming granularity justifies their mapping complexity.

4. Define budget and eviction policy before loading more data: per-class budget, minimum viable mip/LOD, prefetch trigger, eviction trigger, fallback content, and telemetry. 5. Synchronize upload, mapping, and use. A resource must not become visible to a render pass until its data and mapping work have completed. 6. Validate memory and frame pacing on target hardware with representative content and movement, not a synthetic empty scene.

Guardrails

  • Do not equate unified memory with unlimited GPU memory or omit budgeting on Apple silicon.
  • Do not call a resource zero-copy without demonstrating compatible storage, format, synchronization, and absence of conversion/readback.
  • Keep sparse residency and asset LOD decisions data-driven; do not infer success from allocated bytes alone.

Handoffs

  • `metal-game-rendering-workflow` for command encoding, renderer lifetime, and resource consumers.
  • `xcode-game-profiling-workflow` for memory pressure, VM behavior, GPU timeline, or hitch evidence.
  • `game-porting-toolkit-workflow` for a source port that needs GPTK’s asset and resource translation guidance.

Output

Return the measured symptom, selected loading/residency path, budget and fallback policy, synchronization boundary, validation evidence, and unproven hardware assumptions.

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