Bytecode VM
Expert skill for bytecode virtual machine design including instruction set design, dispatch mechanisms, and stack/register architectures
Best use case
Bytecode VM is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Expert skill for bytecode virtual machine design including instruction set design, dispatch mechanisms, and stack/register architectures
Teams using Bytecode VM 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/bytecode-vm/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Bytecode VM Compares
| Feature / Agent | Bytecode VM | 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 bytecode virtual machine design including instruction set design, dispatch mechanisms, and stack/register architectures
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
# Bytecode VM Skill
## Overview
Expert skill for bytecode virtual machine design including instruction set design, dispatch mechanisms, and stack/register architectures.
## Capabilities
- Design bytecode instruction sets
- Implement stack-based vs register-based VMs
- Implement efficient dispatch (switch, computed goto, threaded)
- Design compact bytecode encoding
- Implement bytecode verification
- Handle exception handling in bytecode
- Design inline caching for dynamic dispatch
- Implement bytecode serialization/deserialization
## Target Processes
- bytecode-vm-implementation.js
- interpreter-implementation.js
- jit-compiler-development.js
- repl-development.js
## Dependencies
VM implementation literature (Crafting Interpreters, Programming Language Pragmatics)
## Usage Guidelines
1. **Architecture Selection**: Choose stack-based for simplicity, register-based for performance
2. **Dispatch Mechanism**: Use computed goto/threaded dispatch for hot loops
3. **Encoding**: Design compact bytecode encoding to improve cache locality
4. **Verification**: Implement bytecode verification for security and debugging
5. **Inline Caching**: Add inline caching for polymorphic call sites
## Output Schema
```json
{
"type": "object",
"properties": {
"architecture": {
"type": "string",
"enum": ["stack-based", "register-based", "hybrid"]
},
"dispatch": {
"type": "string",
"enum": ["switch", "computed-goto", "direct-threaded", "indirect-threaded"]
},
"instructionCount": { "type": "integer" },
"encoding": {
"type": "string",
"enum": ["fixed-width", "variable-length"]
},
"generatedFiles": {
"type": "array",
"items": { "type": "string" }
}
}
}
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