Autonomous conduction and mediated adversarial deliberation between AI agents, pluggable into any project.
Project description
regent
Autonomous conduction and mediated adversarial deliberation between AI agents, pluggable into any project.
regent governs turns between agents (Claude, Codex, human mediators) under a frozen protocol: atomic turn mutex, CAS-versioned state, deliberation rounds with versioned acceptances, and a conduction daemon that executes production batches with a confined agent, test gates and evidence proof.
Extracted from the tool proven end-to-end in the ArtNFT project (IMP-003: first product batch fully conducted by the daemon, deliberated, accepted and deployed to production).
- Requirements:
docs/PRD.md - Extraction scope and decisions:
docs/ESCOPO.md(PT-BR, pre-rename) - Deliberation rounds:
docs/brainstorm/(mediator's language, PT-BR) - Status: pre-extraction (scope closed 2026-07-20; code not yet migrated)
Install
pip install <path-to-this-repo> # package: regent-cli; CLI: regent (not on PyPI yet)
cd <your-project>
regent init # seeds .regent/ + .claude/skills symlinks (atomic, idempotent)
regent doctor # checks executor (claude) and advisor (codex) CLIs
Then open a Claude Code session in the project — /regent and /regent-stop are available
(/regent brainstorm "<question>" opens the first round). v0 capability is file-driven
(rounds under .regent/brainstorm/rodadas/); the advisor requires the codex CLI.
Development: PYTHONPATH=src python3 -m unittest discover -s tests. Canonical skill content
lives in src/regent/templates/ (ships inside the wheel); the repo's own .regent/skills/
symlinks into it (dogfood without duplication).
MIT License © 2026 Flavio Alvim.
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