prompt2bin 0.3.3

From natural language to verified machine code

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Natural language in, verified machine code out.

---

Describe what you need in plain English. A formal verification engine (Z3) proves safety properties. An LLM generates the C implementation. A test harness validates correctness. GCC compiles it to a binary.

"I need a lock-free audio ring buffer"
     ↓
  formal spec → Z3 proves 7/7 safety properties
     ↓
  LLM generates C → test harness validates
     ↓
  GCC → x86-64 assembly + machine code
     ↓
  audio_ringbuf.h  audio_ringbuf.s  audio_ringbuf.o

Install

pip install prompt2bin

Requires GCC and at least one LLM backend:

Backend	Setup	API key?
Claude CLI (default)	Install Claude CLI	No — uses subscription
Codex CLI	Install Codex CLI	No — uses subscription
Anthropic API	pip install prompt2bin[anthropic] + set ANTHROPIC_API_KEY	Yes
OpenAI API	pip install prompt2bin[openai] + set OPENAI_API_KEY	Yes

Auto-detects in priority order: CLI > API key. Set P2B_BACKEND to override.

Quick start

p2b is the short alias for prompt2bin.

# one-shot: describe what you need, get a binary
p2b "I need a memory pool for allocating small objects"

# scaffold a new project
p2b init my_project

# build all components + generate main.c + compile
p2b build my_project

# build and run
p2b run my_project

# interactive mode
p2b --interactive

Project builds

A project is a directory with a build.toml, component .prompt files, and an app.prompt:

my_project/
├── build.toml
├── app.prompt                # what the app does, how components wire together
├── specs/
│   ├── memory_pool.prompt    # "I need a memory pool for allocating small objects..."
│   └── message_queue.prompt  # "I need a queue for passing messages between two threads..."
└── build/                    # generated: .h .s .o for each component + main.c

[project]
name = "my_project"
target = "x86-64-linux"

[model]                         # optional: per-project LLM configuration
backend = "anthropic-api"       # claude, codex, anthropic-api, openai-api
name = "claude-sonnet-4-6"
reasoning = "high"              # low, medium, high
temperature = 0.2

[components.memory_pool]
prompt = "specs/memory_pool.prompt"

[components.message_queue]
prompt = "specs/message_queue.prompt"

Templates:

p2b init my_project --template starter     # memory pool + message queue demo
p2b init my_project --template grok-cli    # interactive xAI Grok API client

Build features: incremental caching (SHA-256), parallel builds (up to 4 workers), per-project model config.

Supported domains

Domain	What Z3 proves
Arena allocators	Overflow safety, alignment correctness, memory bounds
Ring buffers	Capacity invariants, index bounds, data loss prevention
Process spawners	Buffer bounds, timeouts, static memory bounds
String tables	Table sizing, index masking safety, storage bounds
Terminal I/O	Cursor/index bounds, input overflow prevention

Each domain has 7 verified safety properties. See examples/ for generated outputs including C code, assembly, and terminal transcripts.

Examples

"I want a fast game frame allocator for temporary per-frame scratch memory, maybe 64KB"
→ 7/7 properties verified → game_frame.h + .s + .o

"Handle crypto key material in memory — must be wiped when done, no traces left"
→ 7/7 properties verified → crypto_secure.h + .s + .o

page_size=100, min_align=3  (bad spec)
→ [FAIL] power_of_two → Code generation blocked.

License

MIT