interpreters — Claude Code skill: bytecode VMs and JIT in C/C++
Walks the agent through bytecode dispatch loops, stack- and register-based VMs, and a small mmap-based JIT.
npx skills add mohitmishra786/low-level-dev-skills --skill interpreters -a claude-codeWhat interpreters does
This skill covers writing interpreters and small JIT compilers in C and C++. It lays out a workflow: pick a VM architecture, choose a dispatch strategy, decide how values are represented, manage the stack, add inline caching, then build a minimal JIT.
Dispatch gets three options with code: switch, computed goto, and direct threading. Computed goto is flagged as a GCC/Clang extension rather than standard C, so the skill suggests guarding it with #ifdef __GNUC__ and keeping switch as a fallback. The JIT section shows x86-64: allocate executable memory with mmap, copy machine code bytes in, call the result. On macOS Apple Silicon you need pthread_jit_write_protect_np() or the MAP_JIT flag, or the code won't run at all.
A performance section follows: keep the stack pointer in a callee-saved register, use NaN boxing or tagged pointers, profile with perf to separate dispatch overhead from real work, and generate specialised handlers for common type pairs. Useful when your interpreter is slow and you can't tell which part is to blame.
What it helps with
- choose between a stack-based and register-based VM
- speed up a bytecode dispatch loop
- add a small JIT without pulling in a library
- diagnose branch misprediction in an interpreter
- fit values into one slot with NaN boxing or tagged pointers
Example prompts for the agent
- Rewrite my
switchdispatch loop as computed goto with a fallback for MSVC - Compare stack-based and register-based VMs for a language with closures
- Write a minimal
mmapJIT that compiles int addition
How to install interpreters
1Skills CLI (Vercel)
npx skills add mohitmishra786/low-level-dev-skills --skill interpreters -a claude-code2Manually: put the files in place
~/.claude/skills/interpreters/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/interpreters/
1Skills CLI (Vercel)
npx skills add mohitmishra786/low-level-dev-skills --skill interpreters -a codex2Manually: put the files in place
.agents/skills/interpreters/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add mohitmishra786/low-level-dev-skills --skill interpreters -a cursor2Manually: put the files in place
.cursor/skills/interpreters/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install mohitmishra786/low-level-dev-skills interpreters2Manually: put the files in place
.github/skills/interpreters/SKILL.md1Skills CLI (Vercel)
npx skills add mohitmishra786/low-level-dev-skills --skill interpreters -a gemini-cli2Platform CLI
gemini skills install https://github.com/mohitmishra786/low-level-dev-skills --path skills/low-level-programming/interpretersManually: put the files in place
.devin/skills/interpreters/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add mohitmishra786/low-level-dev-skills --skill interpreters -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about interpreters
How do I install interpreters in Claude?
Run npx skills add mohitmishra786/low-level-dev-skills --skill interpreters -a claude-code. The skill file then sits at ~/.claude/skills/interpreters/SKILL.md.
What does the interpreters skill do?
It guides an agent through implementing a bytecode interpreter and a simple JIT in C/C++: VM architecture, dispatch loops, value representation, inline caching, and performance advice.
Where does the JIT example break?
On macOS Apple Silicon, where a plain mmap with PROT_EXEC won't work — you need pthread_jit_write_protect_np() or MAP_JIT. Computed goto is also non-standard, so other compilers need the switch fallback.
Source text
SKILL.md · MIT
---
name: interpreters
description: Bytecode interpreter and JIT compiler skill for implementing language runtimes in C/C++. Use when designing bytecode dispatch loops (switch, computed goto, threaded code), implementing stack-based or register-based VMs, adding a simple JIT using mmap/mprotect, or understanding performance trade-offs in interpreter design. Activates on queries about bytecode VMs, dispatch loops, computed goto, JIT compilation basics, tracing JITs, or implementing a scripting language runtime.
---
# Interpreters and Bytecode VMs
## Purpose
Guide agents through implementing efficient bytecode interpreters and simple JITs in C/C++: dispatch strategies, VM architecture choices, and performance patterns.
## Triggers
- "How do I implement a fast bytecode dispatch loop?"
- "What is the difference between switch dispatch and computed goto?"
- "How do I implement a register-based vs stack-based VM?"
- "How do I add basic JIT compilation to my interpreter?"
- "Why is my interpreter slow?"
## Workflow
### 1. VM architecture choice
| Style | Description | Examples |
|-------|-------------|---------|
| Stack-based | Operands on a value stack; compact bytecode | JVM, CPython, WebAssembly |
| Register-based | Operands in virtual registers; fewer instructions | Lua 5+, Dalvik |
| Direct threading | Each "instruction" is a function call | Some Forth implementations |
| Continuation-passing | Interpreter functions return continuations | Academic |
**Stack-based:** easier to implement, compile to; code generation is simpler. More instructions per expression.
**Register-based:** fewer dispatch iterations; needs register allocation in the compiler; better cache behaviour for complex expressions.
### 2. Dispatch loop strategies
#### Switch dispatch (simplest, baseline)
```c
while (1) {
uint8_t op = *ip++;
switch (op) {
case OP_LOAD: push(constants[*ip++]); break;
case OP_ADD: { Value b = pop(); Value a = pop(); push(a + b); } break;
case OP_HALT: return;
// ...
}
}
```
Problem: `switch` compiles to a single indirect branch from a jump table. Modern CPUs can mispredict it heavily because the same indirect branch is used for all opcodes.
#### Computed goto (GCC/Clang extension — fastest portable approach)
```c
// Table of label addresses
static const void *dispatch_table[] = {
[OP_LOAD] = &&op_load,
[OP_ADD] = &&op_add,
[OP_HALT] = &&op_halt,
// ...
};
#define DISPATCH() goto *dispatch_table[*ip++]
DISPATCH(); // start
op_load:
push(constants[*ip++]);
DISPATCH();
op_add: {
Value b = pop(); Value a = pop(); push(a + b);
DISPATCH();
}
op_halt:
return;
```
Each opcode ends with its own indirect branch. The CPU can train the branch predictor per-opcode, dramatically improving prediction rates.
**Note:** `&&label` is a GCC/Clang extension, not standard C. Use `#ifdef __GNUC__` to guard and fall back to switch for other compilers.
#### Direct threaded code (most aggressive)
Each bytecode word is a function pointer or label address; the VM is the fetch-decode-execute loop itself.
```c
typedef void (*Handler)(VM *vm);
// Bytecode is an array of handlers
Handler bytecode[] = { op_load, op_push_1, op_add, op_halt };
for (int i = 0; ; i++) {
bytecode[i](vm);
}
```
### 3. Value representation
**Tagged pointer:** Store type tag in low bits of pointer (pointer alignment guarantees ≥ 2 bits free):
```c
typedef uintptr_t Value;
#define TAG_INT 0x0
#define TAG_FLOAT 0x1
#define TAG_PTR 0x2
#define TAG_MASK 0x3
#define INT_VAL(v) ((int64_t)(v) >> 2)
#define FLOAT_VAL(v) (*(float*)((v) & ~TAG_MASK))
#define IS_INT(v) (((v) & TAG_MASK) == TAG_INT)
```
**NaN boxing (64-bit):** Store non-double values in NaN bit patterns:
```c
// IEEE 754 quiet NaN: exponent all 1s, mantissa != 0
// Use high mantissa bits as type tag, low 48 bits as payload
// Allows pointer/int/bool/nil to fit in a double-sized slot
```
Used by V8 (formerly), LuaJIT, JavaScriptCore.
### 4. Stack management
```c
#define STACK_SIZE 4096
Value stack[STACK_SIZE];
Value *sp = stack; // stack pointer
#define PUSH(v) (*sp++ = (v))
#define POP() (*--sp)
#define TOP() (sp[-1])
#define PEEK(n) (sp[-(n)-1])
// Check for overflow
#define PUSH_SAFE(v) do { \
if (sp >= stack + STACK_SIZE) { vm_error("stack overflow"); } \
PUSH(v); \
} while(0)
```
### 5. Inline caching (IC)
Inline caching speeds up property lookups and method dispatch by caching the last observed type at each call site.
```c
struct CallSite {
Type cached_type; // Last observed receiver type
void *cached_method; // Cached function pointer
int miss_count; // Number of misses
};
void invoke_method(VM *vm, CallSite *cs, Value receiver, ...) {
Type t = GET_TYPE(receiver);
if (t == cs->cached_type) {
// Cache hit: direct call, no lookup
cs->cached_method(vm, receiver, ...);
} else {
// Cache miss: look up, update cache
void *method = lookup_method(t, name);
cs->cached_type = t;
cs->cached_method = method;
cs->miss_count++;
method(vm, receiver, ...);
}
}
```
Polymorphic IC (PIC): cache up to N (typ. 4) type-method pairs.
### 6. Simple JIT (mmap + machine code)
For x86-64: allocate executable memory, write machine code bytes, call it.
```c
#include <sys/mman.h>
#include <string.h>
typedef int (*JitFn)(int a, int b);
JitFn jit_compile_add(void) {
// x86-64: add rdi, rsi; mov rax, rdi; ret
static const uint8_t code[] = {
0x48, 0x01, 0xF7, // add rdi, rsi
0x48, 0x89, 0xF8, // mov rax, rdi
0xC3 // ret
};
void *mem = mmap(NULL, sizeof(code),
PROT_READ | PROT_WRITE | PROT_EXEC,
MAP_PRIVATE | MAP_ANONYMOUS, -1, 0);
if (mem == MAP_FAILED) return NULL;
memcpy(mem, code, sizeof(code));
// On some systems (macOS Apple Silicon): must use mprotect
// mprotect(mem, sizeof(code), PROT_READ | PROT_EXEC);
return (JitFn)mem;
}
```
On macOS Apple Silicon (M-series): use `pthread_jit_write_protect_np()` or `MAP_JIT` flag.
### 7. Performance tips
1. **Dispatch:** Use computed goto over switch on GCC/Clang
2. **Values:** Use NaN boxing or tagged pointers; avoid boxing/unboxing in hot paths
3. **Stack:** Keep stack pointer in a callee-saved register (`register Value *sp asm("r15")` — GCC global register variable)
4. **Locals access:** Keep frequently accessed locals in VM registers (struct fields), not stack
5. **Profiling:** Use `perf` or sampling to find dispatch overhead vs actual work
6. **Specialisation:** Generate specialised handler variants for common type combinations (int+int add vs generic add)
7. **Trace recording:** Trace JITs (LuaJIT approach) compile hot traces instead of full functions
For a benchmark of dispatch strategies, see [references/benchmarks.md](references/benchmarks.md).
## Related skills
- Use `skills/profilers/linux-perf` to profile the interpreter dispatch loop
- Use `skills/low-level-programming/assembly-x86` to understand JIT output
- Use `skills/runtimes/fuzzing` to fuzz the bytecode parser/loader
- Use `skills/compilers/llvm` for LLVM IR-based JIT (MCJIT / ORC JIT)
© mohitmishra786 · MIT · mohitmishra786/low-level-dev-skills