axiom-metal-migration▌
charleswiltgen/axiom · updated Apr 8, 2026
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Porting OpenGL/OpenGL ES or DirectX code to Metal on Apple platforms.
Metal Migration
Porting OpenGL/OpenGL ES or DirectX code to Metal on Apple platforms.
When to Use This Skill
Use this skill when:
- Porting an OpenGL/OpenGL ES codebase to iOS/macOS
- Porting a DirectX codebase to Apple platforms
- Deciding between translation layer (MetalANGLE) vs native rewrite
- Planning a phased migration strategy
- Evaluating effort vs performance tradeoffs
Red Flags
❌ "Just use MetalANGLE and ship" — Translation layers add 10-30% overhead; fine for demos, not production
❌ "Convert shaders one-by-one without planning" — State management differs fundamentally; you'll rewrite twice
❌ "Keep the GL state machine mental model" — Metal is explicit; thinking GL causes subtle bugs
❌ "Port everything at once" — Phased migration catches issues early; big-bang migrations hide compounding bugs
❌ "Skip validation layer during development" — Metal validation catches 80% of porting bugs with clear messages
❌ "Worry about coordinate systems later" — Y-flip and NDC differences cause the most debugging time
❌ "Performance will be the same or better automatically" — Metal requires explicit optimization; naive ports can be slower
Migration Strategy Decision Tree
Starting a port to Metal?
│
├─ Need working demo in <1 week?
│ ├─ OpenGL ES source? → MetalANGLE (translation layer)
│ │ └─ Caveats: 10-30% overhead, ES 2/3 only, no compute
│ │
│ └─ Vulkan available? → MoltenVK
│ └─ Caveats: Vulkan complexity, indirect translation
│
├─ Production app with performance requirements?
│ └─ Native Metal rewrite (recommended)
│ ├─ Phased: Keep GL for reference, port module-by-module
│ └─ Full: Clean rewrite using Metal idioms from start
│
├─ DirectX/HLSL source?
│ └─ Metal Shader Converter (Apple tool)
│ └─ Converts DXIL bytecode → Metal library
│ └─ See metal-migration-ref for usage
│
└─ Hybrid approach?
└─ MetalANGLE for demo → Native Metal incrementally
└─ Best of both: fast validation, optimal end state
Pattern 1: Translation Layer (Quick Demo Path)
When to use: Validate feasibility, get stakeholder buy-in, prototype
MetalANGLE Setup (OpenGL ES → Metal)
// 1. Add MetalANGLE via SPM or CocoaPods
// GitHub: nicklockwood/MetalANGLE
// 2. Replace EAGLContext with MGLContext
import MetalANGLE
let context = MGLContext(api: kMGLRenderingAPIOpenGLES3)
MGLContext.setCurrent(context)
// 3. Replace GLKView with MGLKView
let glView = MGLKView(frame: bounds, context: context)
glView.delegate = self
glView.drawableDepthFormat = .format24
// 4. Existing GL code works unchanged
glClearColor(0, 0, 0, 1)
glClear(GL_COLOR_BUFFER_BIT)
// ... your existing GL rendering code
Tradeoffs Table
| Aspect | MetalANGLE | Native Metal |
|---|---|---|
| Time to demo | Hours | Days-weeks |
| Runtime overhead | 10-30% | Baseline |
| Shader changes | None | Full rewrite |
| Compute shaders | Not supported | Full support |
| Future-proof | Translation debt | Apple-recommended |
| Debugging | GL tools only | GPU Frame Capture |
| Thermal/battery | Higher | Optimizable |
When MetalANGLE Fails
MetalANGLE will NOT work if your code:
- Uses OpenGL ES extensions not in core ES 2/3
- Relies on compute shaders (GL_COMPUTE_SHADER)
- Requires precise GL state machine semantics
- Needs performance within 10% of native
- Targets visionOS (no translation layer support)
Pattern 2: Native Metal Rewrite (Production Path)
When to use: Production apps, performance-critical rendering, long-term maintenance
Phased Migration Strategy
Phase 1: Abstraction Layer (1-2 weeks)
├─ Create renderer interface hiding GL/Metal specifics
├─ Keep GL implementation as reference
├─ Define clear boundaries: setup, resources, draw, present
└─ Validate abstraction with existing tests
Phase 2: Metal Backend (2-4 weeks)
├─ Implement Metal renderer behind same interface
├─ Convert shaders GLSL → MSL (use metal-migration-ref)
├─ Run GL and Metal side-by-side for visual diff
├─ GPU Frame Capture for debugging
└─ Milestone: Feature parity, visual match
Phase 3: Optimization (1-2 weeks)
├─ Remove abstraction overhead where it hurts
├─ Use Metal-specific features (argument buffers, indirect)
├─ Profile with Metal System Trace
├─ Tune for thermal envelope and battery
└─ Remove GL backend entirely
GLSL to Metal Shading Language (MSL) Conversion
| GLSL | MSL | Notes |
|---|---|---|
attribute / varying |
[[stage_in]] struct |
Vertex attributes via struct |
uniform |
[[buffer(N)]] parameter |
Explicit binding index |
gl_Position |
Return float4 from vertex |
Vertex function return value |
gl_FragColor |
Return float4 from fragment |
Fragment function return value |
texture2D(tex, uv) |
tex.sample(sampler, uv) |
Separate sampler object |
vec2/3/4 |
float2/3/4 |
Type names differ |
mat4 |
float4x4 |
Matrix types differ |
mix() |
mix() |
Same name |
precision mediump float |
(not needed) | Metal infers precision |
#version 300 es |
#include <metal_stdlib> |
Different preamble |
Example conversion:
// GLSL vertex shader
#version 300 es
uniform mat4 u_mvp;
in vec3 a_position;
in vec2 a_texCoord;
out vec2 v_texCoord;
void main() {
v_texCoord = a_texCoord;
gl_Position = u_mvp * vec4(a_position, 1.0);
}
// Equivalent MSL vertex shader
#include <metal_stdlib>
using namespace metal;
struct VertexIn {
float3 position [[attribute(0)]];
float2 texCoord [[attribute(1)]];
};
struct VertexOut {
float4 position [[position]];
float2 texCoord;
};
struct Uniforms {
float4x4 mvp;
};
vertex VertexOut vertexShader(VertexIn in [[stage_in]],
constant Uniforms &uniforms [[buffer(1)]]) {
VertexOut out;
out.texCoord = in.texCoord;
out.position = uniforms.mvp * float4(in.position, 1.0);
return out;
}
Key differences to watch:
- GLSL globals → MSL function parameters with
[[attribute]]qualifiers - Implicit uniform binding → explicit
[[buffer(N)]]indices sampler2Dcombines texture+sampler → Metal separatestexture2dandsampler- GLSL preprocessor → Metal uses C++
#includeandusing namespace metal
Core Architecture Differences
| Concept | OpenGL | Metal |
|---|---|---|
| State model | Implicit, mutable | Explicit, immutable PSO |
| Validation | At draw time | At PSO creation |
| Shader compilation | Runtime (JIT) | Build time (AOT) |
| Command submission | Implicit | Explicit command buffers |
| Resource binding | Global state | Per-encoder binding |
| Synchronization | Driver-managed | App-managed |
MTKView Setup (Native Metal)
import MetalKit
class MetalRenderer: NSObject, MTKViewDelegate {
let device: MTLDevice
let commandQueue: MTLCommandQueue
var pipelineState: MTLRenderPipelineState!
init?(metalView: MTKView) {
guard let device = MTLCreateSystemDefaultDevice(),
let queue = device.makeCommandQueue() else {
return nil
}
self.device = device
self.commandQueue = queue
metalView.device = device
metalView.clearColor = MTLClearColor(red: 0, green: 0, blue: 0, alpha: 1)
metalView.depthStencilPixelFormat = .depth32Float
super.init()
metalView.delegate = self
buildPipeline(metalView: metalView)
}
private func buildPipeline(metalView: MTKView) {
let library = device.makeDefaultLibrary()!
let vertexFunction = library.makeFunction(name: "vertexShader")
let fragmentFunction = library.makeFunction(name: "fragmentShader")
let descriptor = MTLRenderPipelineDescriptor()
descriptor.vertexFunction = vertexFunction
descriptor.fragmentFunction = fragmentFunction
descriptor.colorAttachments[0].pixelFormat = metalView.colorPixelFormat
descriptor.depthAttachmentPixelFormat = metalView.depthStencilPixelFormat
// Pre-validated at creation, not at draw time
pipelineState = try! device.makeRenderPipelineState(descriptor: descriptor)
}
func draw(in view: MTKView) {
guard let drawable = view.currentDrawable,
let descriptor = view.currentRenderPassDescriptor,
let commandBuffer = commandQueue.makeCommandBuffer()how to use axiom-metal-migrationHow to use axiom-metal-migration on Cursor
AI-first code editor with Composer
1Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add axiom-metal-migration
2Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/charleswiltgen/axiom --skill axiom-metal-migrationThe skills CLI fetches axiom-metal-migration from GitHub repository charleswiltgen/axiom and configures it for Cursor.
3Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
◆ Which agents do you want to install to?││ ── Universal (.agents/skills) ── always included ────│ • Amp│ • Antigravity│ • Cline│ • Codex│ ●Cursor(selected)│ • Cursor│ • Windsurf4Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/axiom-metal-migrationReload or restart Cursor to activate axiom-metal-migration. Access the skill through slash commands (e.g., /axiom-metal-migration) or your agent's skill management interface.
⚠Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
Additional Resources
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GET_STARTED →Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
✓Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
✓Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
✓Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
✓Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
general reviewsRatings
4.8★★★★★47 reviews- ★★★★★Shikha Mishra· Dec 28, 2024
axiom-metal-migration is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Alexander Gonzalez· Dec 20, 2024
axiom-metal-migration reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Lucas Gill· Dec 16, 2024
Keeps context tight: axiom-metal-migration is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Jin Martinez· Dec 16, 2024
axiom-metal-migration has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Soo Abbas· Dec 4, 2024
We added axiom-metal-migration from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Nia Diallo· Nov 27, 2024
We added axiom-metal-migration from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Rahul Santra· Nov 19, 2024
axiom-metal-migration fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Charlotte Diallo· Nov 7, 2024
Registry listing for axiom-metal-migration matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Mateo Garcia· Nov 7, 2024
Solid pick for teams standardizing on skills: axiom-metal-migration is focused, and the summary matches what you get after install.
- ★★★★★Charlotte Ndlovu· Nov 7, 2024
Keeps context tight: axiom-metal-migration is the kind of skill you can hand to a new teammate without a long onboarding doc.
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