chorus

The Agent Harness for AI-Human Collaboration

中文

Chorus is an agent harness — the infrastructure that wraps around LLM agents to manage session lifecycle, task state, sub-agent orchestration, observability, and failure recovery. It lets multiple AI Agents (PM, Developer, Admin) and humans collaborate on a shared platform through the full workflow from requirements to delivery.

Inspired by the AI-DLC (AI-Driven Development Lifecycle) methodology. Core philosophy: Reversed Conversation — AI proposes, humans verify.

---

Table of Contents

• Why Agent Harness
• AI-DLC Workflow
• Screenshots
• Features
• Architecture
• Tech Stack
• Getting Started
• Skill Documentation
• Progress
• Documentation
• License

Why Agent Harness

An AI agent is only as reliable as the system around it. The model handles reasoning — but session boundaries, task state, context handoff, sub-agent coordination, and failure recovery all happen outside the model. That surrounding system is the agent harness.

Without a harness, agents drift across long tasks, lose context between sessions, duplicate work, and fail silently. A well-designed harness solves these problems:

Harness Capability	The Problem It Solves	How Chorus Handles It
Session Lifecycle	Agents lose track of work across restarts	Every agent gets a persistent session with heartbeats; the plugin auto-creates and closes sessions on spawn/exit
Task State Machine	No single source of truth for what's done	Tasks flow through a strict lifecycle — claimed, in progress, submitted, verified — visible to everyone in real time
Context Continuity	Fresh context windows start from zero	Each check-in restores the agent's persona, current assignments, and project state so it can resume without re-discovery
Sub-Agent Orchestration	Multi-agent work is chaotic without coordination	Lifecycle hooks wire up sub-agents automatically — sessions, context, and unblocked task discovery are handled, not hand-coded
Observability	Can't debug what you can't see	Every action is logged with session attribution; Kanban and worker badges show who is doing what, live
Failure Recovery	Stuck tasks block the entire pipeline	Idle sessions expire, orphaned tasks are released back to the pool, and any agent can pick them up again
Planning & Decomposition	Agents jump into coding without a plan	A PM agent builds a dependency graph of tasks before execution begins — no work starts without an approved plan

Chorus is not a framework — it doesn't provide building blocks for you to assemble. It is a complete harness with opinionated defaults: lifecycle hooks, ready-to-use MCP tools, role-based access, and a built-in human review loop.

---

AI-DLC Workflow

Idea ──> Proposal ──> [Document + Task DAG] ──> Execute ──> Verify ──> Done
  ^          ^               ^                     ^          ^         ^
Human     PM Agent       PM Agent              Dev Agent    Admin     Admin
creates   analyzes       drafts PRD            codes &      reviews   closes
          & plans        & tasks               reports      & verifies

Three Agent roles:

Role	Responsibility	MCP Tool Prefix
PM Agent	Analyze Ideas, create Proposals (PRD + task breakdown), manage documents	chorus_pm_*
Developer Agent	Claim tasks, write code, report work, submit for verification	chorus_*_task, chorus_report_work
Admin Agent	Create projects/Ideas, approve Proposals, verify tasks, manage lifecycle	chorus_admin_*

All roles share read-only and collaboration tools (chorus_get_*, chorus_checkin, chorus_add_comment, etc.).

---

Screenshots

Pixel Workspace — Real-time Agent Status

The left panel is a pixel workspace where pixel characters represent each Agent's real-time working status; the right panel shows live Agent terminal output.

Kanban — Real-time Task Flow