master-workflow

master-workflow

Enables multi-agent code review and iterative improvement loop using different LLM backends, with deterministic scoring and audit trail.

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master-workflow

Multi-agent orchestration loop: worker → cross-model reviewer → score ≥ 9.

License: MIT Python 3.10+ MCP Server

An AI agent orchestration framework that runs a deterministic build-review loop across multiple LLM backends. You define the goal and acceptance criteria; the harness spawns a fresh worker agent, captures the real git diff, hands it to a different model running read-only, and loops until an independent reviewer scores the work 9/10 or higher.

Ships as an MCP server, an agent skill, and a plain CLI.

                    ┌──────────────── harness (deterministic) ────────────────┐
you ─▶ orchestrator ─▶ brief ─▶ worker CLI ─▶ git diff ─▶ reviewer ─▶ score ≥ 9?
        (your agent)     ▲       fresh ctx     (not the    (other model,   │ no
                         │                      summary)    read-only)     │
                         └──────── findings folded into a new brief ◀───────┘

Features

  • Cross-model code review — the reviewer is never the worker; a different backend grades every diff in a clean, read-only context
  • Deterministic loop — the control flow is code, not a prompt that promises to loop; every iteration is auditable
  • Five backends — Codex, Grok, Claude, OpenCode, and Kimi, with advisory routing based on task type
  • Git-native verification — the reviewer reads the actual diff from git, never the worker's summary
  • Fresh context per iteration — each worker spawns clean; findings from the previous round become requirements in the next brief
  • Sandbox enforcement — OS-level read-only sandboxes where available (Codex, Grok), with PTY-verified enforcement for Grok
  • Full audit trail — every run leaves a filesystem ledger: briefs, diffs, event streams, scores, and verdicts
  • Session search — fold decisions from past agent sessions (any backend) into the worker brief

Why it is shaped like this

The reviewer is never the worker. A model grading its own diff scores it far too generously, and your orchestrator's context already wants the task to be finished. The reviewer runs on a different backend, in a clean context, with writes disabled. It is the only thing that can end the loop.

The reviewer reads the diff, never the summary. A worker's final message is the least reliable artifact it produces. The harness takes the diff from git itself and puts that in front of the reviewer.

Every iteration spawns a fresh worker. A context that already argued for a failed attempt tends to defend it; a clean one reads the reviewer's findings as requirements. Everything the worker needs travels in the brief, which is why the brief is the thing worth designing. (carry_session: true opts out.)

Verify, don't trust. Grok's --sandbox silently does nothing when there is no TTY — the Landlock profile fails to apply, the run continues unconfined, and the command still exits 0. The vendored wrapper supplies a PTY and then verifies enforcement after the fact, reporting NOT ENFORCED rather than letting an unconfined run pass as a sandboxed one.

Requirements

  • Python 3.10+
  • At least two agent CLIs installed (one to work, one to review)
  • Git

Installation

git clone https://github.com/luckeyfaraday/master-workflow
cd master-workflow
python3 -m venv .venv && .venv/bin/pip install -e ".[mcp]"
.venv/bin/master-workflow status
backend    installed  review-sandbox  version
codex      yes        os-enforced     codex-cli 0.145.0
grok       yes        os-enforced     grok 0.2.112
claude     yes        tool-denied     2.1.220 (Claude Code)
opencode   yes        none            0.0.0-dev
kimi       yes        none            kimi, version 1.49.0

review-sandbox is how a reviewer's writes are suppressed. os-enforced means the sandbox blocks them (codex -s read-only, grok --sandbox read-only) while the reviewer can still run the tests — the best kind. tool-denied means the editing tools are denied by name but nothing stops a shell command; Claude Code's --allowedTools is additive, not exclusive, so it cannot be used to lock a reviewer down. none means don't review with it. The harness prefers os-enforced reviewers automatically.

As an MCP server

claude mcp add --scope user master-workflow -- /path/to/master-workflow/.venv/bin/master-workflow-mcp

As an agent skill

ln -s "$PWD/skills/master-workflow" ~/.claude/skills/master-workflow

Then just talk to your agent:

Use master-workflow to add rate limiting to the API. Send it to Codex, have Claude review it, and don't stop until it's a 9.

Backend routing

Suggestions, not rules — your explicit choice always wins.

Backend Route it here Models
codex Backend, APIs, databases, migrations, auth, infra, security, deep reasoning over a large codebase. The strongest reviewer. gpt-5.6-sol (hard), gpt-5.6-terra (default), gpt-5.6-luna (bounded, fast)
grok Speed on mechanical volume: sweeping refactors, bulk migrations, forty similar test failures, boilerplate, CI config. grok-build-0.1, grok-4.3
claude Frontend, UI, visual and rendering work — anything a human will look at. Also a good reviewer. opus, sonnet, haiku
opencode The escape hatch: any model on OpenRouter and every other configured provider. Reach a model the others can't, or A/B two models on one brief. any provider/model
kimi Frontend and components; a second opinion against Claude on UI. provider default

master-workflow suggest "<task>" scores a task against these and explains the route it picks.

CLI usage

master-workflow run \
  --goal "Add a /health endpoint that reports DB connectivity" \
  --criteria "Returns 200 with {status,db} when reachable, 503 when not. Has a test. Existing tests still pass." \
  --cwd ~/code/api \
  --backend codex --reviewer claude \
  --threshold 9 --max-iterations 4
run_id=20260728-141902-add-a-health-endpoint
worker=codex reviewer=claude threshold=9.0

iteration 1  worker=codex  reviewer=claude  score=6.0/9.0
verdict: Endpoint works but the failure path is untested and swallows the error.
  - `except Exception: return {"db": "down"}` at health.py:24 hides the real error
  - No test covers the 503 branch
-> continue: score 6.0 < 9.0; 2 findings to fix

iteration 2  worker=codex  reviewer=claude  score=9.0/9.0
verdict: Meets every criterion; failure path tested and the error is surfaced.
-> stop: score 9.0 >= 9.0

status=passed best_score=9.0 — score 9.0 >= 9.0

Other commands: status, suggest, iterate <run_id>, list, show <run_id>, ledger <run_id>, search <query>.

MCP tools

Tool Purpose
worker_status What's installed, what each backend is good at, who can review
suggest_backend Advisory route for a task description
search_sessions / show_session Full-text search across Claude Code, Codex, opencode, and Hermes history
workflow_create Register goal + criteria + routing; returns a run_id
workflow_iterate One worker → reviewer cycle, blocking. The primary driver
workflow_run_background Hand the whole loop off; poll workflow_status
workflow_status / workflow_list / workflow_ledger Progress and audit
workflow_diff The actual diff, so the orchestrator can review it too
workflow_abort Stop a run
delegate One-shot worker run, no loop, for bounded errands

Context from your own history

Workers start clean, so anything they need has to travel in the brief. When the goal depends on a decision made in an earlier session — with any agent — search_sessions finds it and the orchestrator folds it into context_notes before the first worker spawns.

master-workflow search "why we dropped the redis cache" --agent codex

Requires sessions-search on PATH. Optional — everything else works without it.

Run artifacts

Everything writes to one layout, so resume works uniformly and the audit log is just the filesystem:

~/.master-workflow/runs/<run_id>/
    run.json                  full state, rewritten on every transition
    ledger.jsonl              append-only event log
    iterations/01/worker/     brief.md prompt.md events.jsonl last_message.txt
                              session_id diff.patch sandbox stderr.log
    iterations/01/review/     brief.md last_message.txt review.json

Override the root with MASTER_WORKFLOW_HOME.

Scoring rubric

The reviewer is calibrated to be hard to please:

Score Means
0–3 Doesn't do the task, or is broken
4–6 Partial, defective, or no evidence it was verified
7–8 Works, but has real problems a careful engineer would fix first
9 Meets every criterion, verified, nothing worth blocking on
10 As above, and the approach itself is right

A review that fails to emit its JSON verdict is capped below threshold — an unparsed review can never end the loop on its own.

Related projects

Consolidates ideas from codex-router, delegate-to-grok, delegate-to-opencode, frontier-orchestrator, athena-loops, athena-graphs, multi-loops, and sessions-search. The Grok PTY sandbox wrapper is vendored from delegate-to-grok.

License

MIT

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