Bytecode VM

Expert skill for bytecode virtual machine design including instruction set design, dispatch mechanisms, and stack/register architectures

509 stars

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

$curl -o ~/.claude/skills/bytecode-vm/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/programming-languages/skills/bytecode-vm/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/bytecode-vm/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How Bytecode VM Compares

Feature / AgentBytecode VMStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/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" }
    }
  }
}
```