Register Allocation
Expert skill for register allocation algorithms including graph coloring, linear scan, and spill code generation
Best use case
Register Allocation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Expert skill for register allocation algorithms including graph coloring, linear scan, and spill code generation
Teams using Register Allocation should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/register-allocation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Register Allocation Compares
| Feature / Agent | Register Allocation | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Expert skill for register allocation algorithms including graph coloring, linear scan, and spill code generation
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Register Allocation Skill
## Overview
Expert skill for register allocation algorithms including graph coloring, linear scan, and spill code generation.
## Capabilities
- Implement graph coloring register allocation
- Implement linear scan register allocation
- Generate spill code with minimal overhead
- Handle calling convention register constraints
- Implement register coalescing
- Handle pre-colored nodes and fixed registers
- Implement live range splitting
- Design register pressure analysis
## Target Processes
- jit-compiler-development.js
- code-generation-llvm.js
- bytecode-vm-implementation.js
## Dependencies
None (algorithmic skill)
## Usage Guidelines
1. **Algorithm Selection**: Use linear scan for JIT (fast), graph coloring for AOT (optimal)
2. **Live Ranges**: Compute accurate live ranges before allocation
3. **Spill Costs**: Use heuristics to minimize spill costs (loop depth, usage frequency)
4. **Calling Conventions**: Handle caller/callee-saved registers correctly
5. **Coalescing**: Implement aggressive coalescing to reduce moves
## Output Schema
```json
{
"type": "object",
"properties": {
"algorithm": {
"type": "string",
"enum": ["graph-coloring", "linear-scan", "second-chance-binpacking"]
},
"spillStrategy": { "type": "string" },
"registerClasses": {
"type": "array",
"items": { "type": "string" }
},
"generatedFiles": {
"type": "array",
"items": { "type": "string" }
}
}
}
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