Cezar — AI Coding Agent Orchestrator

What does this agent do, and when should you use it?

Cezar is the open-source orchestrator and ADE from the open-mercato/cezar repository, providing a single web cockpit for running multiple AI coding agents concurrently. It reuses your existing logged-in claude, codex, opencode or pi CLIs, so no API keys are required. Every task runs in its own git worktree, letting several agents work simultaneously while extra tasks wait in a queue. Workflows are short YAML files and skills are Markdown files, with agents mixable per step; live runs stream agent text, tool calls, tokens and cost. It has no database — all state is plain files under .ai/cezar/ — and can be started locally with npx cezar-run or deployed to an Ubuntu VPS via server-install for 24/7 operation, reviewable from a fully responsive phone UI.

Cezar takes task descriptions (typed, with attached files, or launched from a GitHub issue / Jira / Linear) and runs them in a fresh git worktree according to a YAML workflow (such as the built-in quick-task), executing agent steps plus shell checks. A typical workflow:

yaml

name: fix-and-verify

steps:

- id: implement
prompt: "{{task}}"
skill: project-conventions
runner: codex
- id: verify
command: "npm test"
onFail: { retry: implement, max: 2 }

It invokes your locally logged-in agent CLIs to execute steps, retrying automatically with the error fed back when a check fails. The cockpit streams every step, tool call, token and cost live. You can run the same task ×2 or ×3 and compare diffs, agents can delegate child tasks (up to four children in flight per parent, sharing the parent budget), and Automations launch tasks on schedules or from GitHub/tracker events. Everything — workflows, skills, task state — is stored as plain files in .ai/cezar/. Results are reviewed as diffs, with notes or draft PRs; nothing auto-merges.

1. A solo developer who wants several coding agents working on different tasks across repos simultaneously, each in its own worktree.
2. A remote/freelance developer deploying Cezar on a VPS so agents keep working 24/7 after the laptop closes, reviewing diffs from a phone.
3. An open-source maintainer handing a GitHub issue to an agent in one click and reviewing the resulting draft PR.
4. Teams on Jira or Linear launching workflows directly from tracker issues and configuring event-driven automations.
5. A developer comparing approaches by running the same task ×2 or ×3 and keeping the best diff.
6. A team tracking per-project token usage and reported cost through the Usage & cost dashboard.

How do you install or deploy this agent?

Prerequisites: Node 20+ and at least one logged-in agent CLI (Claude Code, Codex, OpenCode, or pi); git and gh are optional. No database or API keys needed.

bash

cd your-repo
npx cezar-run

This opens the cockpit at http://localhost:4321. To try it without logging in:

bash

CEZ_DRY_RUN=1 npx cezar-run

(Uses a built-in mock agent.) To set up a server:

bash

npx cezar-run server-install --platform ubuntu-vps

This sets up HTTPS, a login and a system service so the cockpit is reachable from anywhere, including your phone. A macOS + ngrok guide is also documented.

How do you use this agent?

Type a task in the cockpit, pick a workflow and hit Start, or run headless from the CLI:

bash

npx cezar-run run "add a -- flag to the export command"

Scaffold project configuration:

bash

npx cezar-run init

Try the nightly build:

bash

npx cezar-run@nightly

Custom workflows are YAML files in .ai/cezar/workflows/; skills are Markdown files in .ai/skills. Workflows can be built by drag-and-drop in the UI and are saved as YAML. Each step can target a different agent via the runner field, and command steps pass when they exit 0. You can also connect GitHub, Jira or Linear to launch tasks from issues, or schedule recurring work and event triggers in Automations.

What are this agent's strengths and limitations?

How does this agent compare with similar options?

Key facts side by side with the most closely related agents.

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