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). The v1 skills are
control-backed: activity state lives in .regent/control.json and is driven through
the JSON subcommands — regent status (control + lock + the executable control×files
matrix as workspace.verdict), regent activity start|resume|suspend|conclude|heartbeat|takeover, regent stop request|check. Hosts
seeded by older versions upgrade automatically on regent init (known-version manifest;
unknown local edits are preserved as conflicts). The advisor requires the codex CLI. Conduction
phase 1 mechanizes the two most error-prone sub-steps: regent advisor consult --prompt-file … --artifact … --linkage … (read-only sandboxed consultation with the
REQ-003 §5 evidence pair generated by the command, fail-closed verdict expectation) and
regent gate run --command … --declared-in <plan> --artifact … --linkage … (verbatim
provenance check, process-group-killing timeout, integral output preserved). Conduction
phase 2 adds regent turn run: one supervised, CONFINED claude -p turn — the agent may
only write inside a declared envelope (a PreToolUse hook denies the rest), the supervisor
proves what changed via git (blob shas vs authenticated post events) and commits through a
private index with a HEAD compare-and-swap. The agent never commits; a violation, a
tampered log or a red gate never yields a product commit.
Development: PYTHONPATH=src python3 -m unittest discover -s tests; packaging gate:
bash scripts/gate-package.sh. Canonical skill content lives in src/regent/templates/
(ships inside the wheel); the repo's own .regent/skills/ symlinks into it (dogfood
without duplication).
Protocol layer
regent.protocol (PLAN-001) is the transactional foundation the conduction daemon will
drive: ControlStore (control.json with a real CAS — every mutation runs inside a
kernel-flock critical section, atomic AND durable publication with file+directory fsync),
TurnLock (executor-only turn ownership by uuid4 token; the whole lifecycle —
acquire/heartbeat/release/takeover — is serialized under a flock; takeover is graced,
audited, and rotates the control turn token BEFORE the new lock exists, aborting on
divergence), stop-request representation (record_stop_request /
read_valid_stop_request / suspend_activity, with activity/epoch/turn-token staleness
fencing) and AuditLog (flock-serialized, fsynced JSONL under
.regent/protocol/audit.jsonl). Dormant until the conduction phase wires it to the
skills; the v0 skills remain file-driven.
MIT License © 2026 Flavio Alvim.
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