Ortim CLI Documentation
Ortim is a disciplined, multi-agent AI software factory. It turns a one-paragraph brief into working, reviewed, audit-trailed code — without surrendering control to the LLM.
pip install ortim
Requires Python ≥ 3.11. After install, run ortim config init to pick a provider
(DeepSeek / Anthropic / local Ollama) and store credentials — no .env setup needed.
What it is
Ortim treats AI coding as a production-engineering problem, not a prompting problem. Five structural pieces turn an unreliable LLM into a reviewable software pipeline:
- A deterministic state machine drives the pipeline: brief → PRD → RFC → task DAG → code.
- Two mandatory human gates (PRD and RFC) — the LLM never silently commits to a scope or an architecture.
- A hash-chained audit log records every LLM call, state transition, and gate decision.
- Scope-locked task DAGs keep work inside declared module boundaries.
- A reviewer chain (Code → Security → Test → Perf) that treats "couldn't verify" differently from "passed".
Where to go next
- Getting started — install to a finished project in ~15 minutes.
- Concepts — the state machine, gates, deterministic architecture, and audit chain.
- CLI reference — every command you'll use day to day.
- Providers & cost — multi-provider routing and what a run actually costs.
- Ortim Cloud — sync runs and audit trails to a shared team workspace.
What it is not
Ortim is not an autocomplete or an IDE. If you love Cursor or Claude Code for interactive work, Ortim is the opposite end of the spectrum: batch, gated, auditable. It works on greenfield and existing codebases — brownfield mode scans the import graph. The bet is that teams who need to answer "who approved this, and why?" will trade some interactivity for governance.