o1op 1.1.0

A deterministic code synthesis operator — composes working programs from natural-language intent without any LLM in the loop. 8-color algebraic type system over a 7-pass causal knowledge graph, with a 7-layer verification pipeline and an autonomous 9-phase engagement operator.

O1-O — deterministic code synthesis operator

Zero-LLM program composition from natural-language intent.
8-color algebraic type system · 7-pass causal inference · 7-layer verification · 9-phase autonomous engagement.

~300ms generation · offline · air-gapped · deterministic

pip install o1op

Quick start

# interactive REPL
o1o

# or run from source
python3 -m o1o_o.o1o_live

What it does

You type intent in plain English. O1-O queries a .causal knowledge graph (~75k triplets, ~1200 code fragments), assembles a working program, runs a 7-layer verification pipeline (compile check → formal verification → evasion scan → OPSEC audit), and hands you deployable code. No model, no API, no network.

O1-O> build a port scanner with banner grabbing for 10.0.0.1

11 pipeline steps, ~300ms, done.

The /engage operator

Full autonomous engagement: recon → tool generation → deployment → post-exploitation → reporting. One command, zero human intervention.

O1-O> /engage 10.0.0.1

What's inside

Component	Count
.causal knowledge graph triplets	~75,000
Code fragments (verified)	~1,200
MITRE ATT&CK techniques covered	102
MITRE tactics covered	14/14
Algebraic type colors	8
Pipeline verification layers	7

Current state

This works. It generates real code from a real knowledge graph in real time. It's also the first public release and there are rough edges — some fragment selections are imprecise, some intents don't have matching fragments yet, and the engagement operator iterates on failures live (which is a feature, not a bug — you see it retry and adapt).

If something doesn't work, fix it. The fragment registry is plain JSON, the knowledge graph is documented, the pipeline is readable Python. PRs welcome, issues welcome, forks encouraged.

Requirements

• Python ≥ 3.10
• Dependencies: msgpack, jellyfish, requests, beautifulsoup4

Full documentation

Architecture, papers (9 peer-reviewed at 4 IEEE 2026 conferences + IBM z/OS mainframe validation), math, and the full technical deep-dive:

→ github.com/DT-Foss/O1-O

License

Apache-2.0 · David Tom Foss · [e-mail]