darq 0.1.0

darq CLI + TUI — autonomous issue → PR pipeline with SAT and a learning loop.
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<h1 align="center">darq</h1>

<p align="center">
  <strong>The dark software factory.</strong><br/>
  Software that writes itself — and gets smarter without you in between.
</p>

<p align="center">
  <a href="https://crates.io/crates/darq"><img src="https://img.shields.io/crates/v/darq.svg?label=crates.io&color=a0ce29" alt="crates.io"></a>
  <a href="https://github.com/dark-builders/darq/blob/main/LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue.svg" alt="License"></a>
  <a href="https://darq.sh"><img src="https://img.shields.io/badge/site-darq.sh-a0ce29.svg" alt="darq.sh"></a>
</p>

---

darq takes a GitHub issue and ships the merged PR — autonomously. Plan, implement, review, fix, merge, then Scenario-driven AI Testing (SAT) the result through three personas (junior / senior / maintainer). Every run extracts patterns into a learning store; the next run starts smarter.

---

<p align="center">
  <a href="https://asciinema.org/a/947476">
    <img src="https://asciinema.org/a/947476.svg" alt="darq demo" width="720">
  </a>
</p>

---

## Install

```bash
cargo install darq
```

Requires an [ACP-compatible](https://agentclientprotocol.com) coding agent on your `PATH` (default: [opencode](https://opencode.ai)).

> Only tested on Linux (Ubuntu 25). macOS and Windows are not supported in v0.1.

## Run

```bash
# Start the daemon (one time)
darq daemon start

# Run a full pipeline against a real issue
darq run issue 42 --full

# Watch it live in the TUI
darq tui
```

## What it does

```
issue → plan → implement → review ⇄ fix → merge → SAT → learn → next run
```

Seven workflow stations, one autonomous loop. The agent calls tools, opens a PR, and waits for itself to merge. After merge, three persona-driven judges score the result. Patterns flow into a vector store; future runs retrieve and inject them at plan time.

## What makes it different

- **SAT (Scenario-driven AI Testing)** — quality gate is persona-based judgement, not just `cargo test`. Three judges, blended score, threshold-gated verdict.
- **Learning loop** — `ruvector` + `sona_engine` extract reusable patterns from every successful run. Future plans cite them.
- **Alien-living TUI** — 30 Hz oscilloscope shows the agent's heartbeat, breathing, and tool-use bursts as a live waveform. Three readable shapes — *idle / thinking / producing.* Built on [ratatui](https://ratatui.rs).
- **Daemon architecture** — long-lived process owns DB, broadcaster, workflow engine. CLI commands are thin clients over a Unix socket.


## Architecture

Two-crate workspace:

- **[`darq-core`](crates/darq-core)** — workflow engine, SAT, ruvector, sona, broadcaster
- **[`darq`](crates/darq)** — daemon, CLI, TUI (binary crate)

Built on Rust 2024, ratatui, tokio, rusqlite (bundled), serde_yml.

For more depth, see [`docs/`](./docs/) and the inline `AGENTS.md` files per crate.

## License

Licensed under [MIT](./LICENSE).

## Acknowledgements

Built by [@DogaOztuzun](https://github.com/DogaOztuzun) at [dark-builders](https://github.com/dark-builders).