JIT Compilation
Expert skill for just-in-time compilation including profiling, tiered compilation, and deoptimization
Best use case
JIT Compilation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Expert skill for just-in-time compilation including profiling, tiered compilation, and deoptimization
Teams using JIT Compilation 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/jit-compilation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How JIT Compilation Compares
| Feature / Agent | JIT Compilation | 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 just-in-time compilation including profiling, tiered compilation, and deoptimization
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
# JIT Compilation Skill
## Overview
Expert skill for just-in-time compilation including profiling, tiered compilation, and deoptimization.
## Capabilities
- Implement execution profiling and hot path detection
- Design tiered compilation strategies (baseline + optimizing)
- Implement on-stack replacement (OSR)
- Implement speculative optimizations with guards
- Design deoptimization frame reconstruction
- Implement inline caching and type feedback
- Design code cache management and eviction
- Implement method inlining heuristics
## Target Processes
- jit-compiler-development.js
- bytecode-vm-implementation.js
- interpreter-implementation.js
## Dependencies
V8/HotSpot architecture references
## Usage Guidelines
1. **Tiered Approach**: Start with a baseline tier, add optimizing tier when profiling data is available
2. **Profile-Guided**: Use profiling data to guide optimization decisions
3. **Speculation**: Implement guards for speculative optimizations with clean deoptimization
4. **OSR**: Implement OSR for long-running loops to benefit from optimization mid-execution
5. **Code Cache**: Implement code cache management to handle memory pressure
## Output Schema
```json
{
"type": "object",
"properties": {
"tiers": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"trigger": { "type": "string" }
}
}
},
"profilingMethod": {
"type": "string",
"enum": ["counters", "sampling", "tracing"]
},
"osrSupport": { "type": "boolean" },
"generatedFiles": {
"type": "array",
"items": { "type": "string" }
}
}
}
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