Tool-agnostic multi-agent workflow coordinator. Orchestrate AI coding agents through a structured handoff protocol.
Project description
Agent Coordinator
Coordinate multiple AI coding agents — architect, developer, QA — on the same codebase. Agents pass work through handoff.md; the coordinator reads who's next, builds the prompt, dispatches to the backend, verifies the handoff, and repeats.
Works with GitHub Copilot CLI, Claude Code, OpenCode, or any CLI tool. Mix backends freely. Zero third-party dependencies.
Shared files:
handoff.md— agent conversation history, append-onlytasks.json— task state, updated automatically.agent-coordinator/— coordinator state (sessions, event log, debug log)
Install
pip install agent-coordinator
uv run pipx install agent-coordinator
From source:
git clone https://github.com/zkucekovic/agent-coordinator.git
cd agent-coordinator
pip install -e .
Requires Python 3.10+. Install whichever backend CLI you plan to use.
Quick start
Option A — Start from scratch
# Initialise a new workspace (creates handoff.md + agents.json automatically)
agent-coordinator --workspace ./my-project
The coordinator creates two files in ./my-project/:
agents.json — ready to run, no editing needed:
{
"default_backend": "copilot",
"retry_policy": { "max_rework": 3, "on_exceed": "needs_human" },
"agents": {
"architect": { "backend": "copilot", "model": "claude-sonnet-4.6", "prompt_file": "prompts/architect.md", "supportsStatelessMode": false },
"developer": { "backend": "copilot", "model": "claude-sonnet-4.6", "prompt_file": "prompts/developer.md", "supportsStatelessMode": true },
"qa_engineer": { "backend": "copilot", "model": "claude-sonnet-4.6", "prompt_file": "prompts/qa_engineer.md", "supportsStatelessMode": true }
}
}
handoff.md — initial handoff directing the architect to start planning.
Then drop in your project context and hit Start:
# Add a spec and/or plan (optional — agents will work from handoff.md otherwise)
cp SPECIFICATION.md ./my-project/
cp plan.md ./my-project/
# Run — the startup menu appears; press Enter to start
agent-coordinator --workspace ./my-project
Option B — Import specs and plans, then run
Import your existing documents and let the architect pick up immediately:
# Import a single spec or plan (auto-detected)
agent-coordinator --import SPECIFICATION.md --workspace ./my-project
agent-coordinator --import plan.md --workspace ./my-project
# Import entire folders
agent-coordinator --import-specs ./specs/ --workspace ./my-project
agent-coordinator --import-plans ./plans/ --workspace ./my-project
# Then start the coordinator
agent-coordinator --workspace ./my-project
On first run the coordinator injects all spec/plan files into the architect's prompt. The architect reads them, decomposes the work into tasks.json, and hands off task-001 to the developer.
The development loop
Once running, each turn follows this cycle:
architect → reads spec/plan, creates tasks.json, assigns task-001 to developer
developer → implements the task, writes code, updates handoff.md (STATUS: review_required)
architect → reviews the work (STATUS: approved or rework_required)
qa_engineer → validates, runs tests, writes handoff.md (STATUS: continue or blocked)
↑ repeat for each task
Working through a task list:
The coordinator tracks tasks.json automatically. After each approved task the architect assigns the next one. You can watch progress live in the TUI or check tasks.json:
{ "id": "task-001", "title": "...", "status": "done" },
{ "id": "task-002", "title": "...", "status": "in_engineering" },
{ "id": "task-003", "title": "...", "status": "planned" }
To skip to a specific task or add context, press Ctrl+C → m (add message to handoff) and type your instruction.
Skip the menu — run immediately
agent-coordinator --workspace ./my-project --auto # skip startup menu
agent-coordinator --workspace ./my-project --max-turns 20 # stop after 20 turns
agent-coordinator --workspace ./my-project --reset # clear sessions and restart
How it works
---HANDOFF---
ROLE: developer
STATUS: review_required
NEXT: architect
TASK_ID: task-001
TITLE: Implement login endpoint
SUMMARY: Added POST /auth/login with JWT signing. Used existing User model.
ACCEPTANCE:
- login endpoint returns a signed JWT — PASS
- input validation on email/password — PASS
CHANGED_FILES:
- src/auth/login.py
- tests/test_login.py
VALIDATION:
- python3 -m pytest tests/test_login.py -- 6 passed
BLOCKERS:
- none
---END---
Each turn: read NEXT: → build prompt → dispatch → verify new block appended (retry if not) → sync tasks.json → log to .agent-coordinator/events.jsonl.
Status values
| Status | Effect |
|---|---|
continue |
Hand off to the next agent |
review_required |
Developer finished, architect should review |
rework_required |
Changes needed, back to developer |
approved |
Architect accepts the work |
blocked |
Cannot proceed, needs intervention |
needs_human |
Escalate to human operator |
plan_complete |
All work done, workflow ends |
Task lifecycle
planned → in_engineering → ready_for_architect_review → done
↑ ↓
rework_requested ←── (architect decides)
Configuration
agents.json
{
"default_backend": "copilot",
"retry_policy": { "max_rework": 3, "on_exceed": "needs_human" },
"agents": {
"architect": {
"backend": "claude",
"model": "claude-sonnet-4",
"prompt_file": "prompts/architect.md",
"supportsStatelessMode": false
},
"developer": {
"backend": "copilot",
"prompt_file": "prompts/developer.md",
"supportsStatelessMode": true
},
"qa_engineer": {
"backend": "opencode",
"prompt_file": "prompts/qa_engineer.md",
"supportsStatelessMode": true
}
}
}
Each agent can use a different backend. Built-in: copilot, claude, opencode, manual (human-in-the-loop). Any other value is resolved from PATH, or use backend_config for full control — see docs/custom-backends.md. Set supportsStatelessMode: false for agents that should keep their session even when the CLI runs with --stateless.
CLI flags
| Flag | Default | Description |
|---|---|---|
--workspace PATH |
. (cwd) |
Directory with handoff.md and project files |
--max-turns N |
0 (unlimited) |
Stop after N agent turns (0 = run until done) |
--reset |
Clear saved sessions and start fresh | |
--auto |
Skip the startup menu and run immediately | |
--quiet |
Suppress TUI output | |
--output-lines N |
10 |
Agent output lines shown in TUI |
--no-streaming |
Show output all at once instead of streaming | |
--stateless |
Run supported agents without session persistence (fresh context every turn) | |
--import FILE |
Import a single specification or plan file into workspace | |
--import-specs PATH |
Import a directory (or file) of specs into <workspace>/specs/ |
|
--import-plans PATH |
Import a directory (or file) of plans into <workspace>/plans/ (also extracts tasks.json) |
|
--type spec|plan |
auto | Force document type when using --import |
--force |
Overwrite existing files when importing | |
--no-handoff |
Skip creating handoff.md when importing | |
--no-tasks |
Skip creating tasks.json when importing a plan |
Project files
Drop these in your workspace — they're injected into agent prompts on the first turn:
- Spec folder:
specs/,spec/, orspecifications/— all.mdfiles loaded - Plan folder:
plans/,plan/, orimplementation_plans/— all.mdfiles loaded - Single spec file (fallback):
SPECIFICATION.md,spec.md,PRD.md,requirements.md - Single plan file (fallback):
IMPLEMENTATION_PLAN.md,plan.md - Project rules:
AGENTS.md— coding standards, conventions, and constraints
Folders take priority over single files. Use --import-specs / --import-plans to populate these from outside the workspace.
Sessions
Session IDs are saved in <workspace>/.agent-coordinator/sessions.json. Re-running resumes where you left off. Use --reset to start clean. With --stateless, only agents whose config allows stateless mode get a fresh context every turn; agents with supportsStatelessMode: false keep using their saved sessions.
Interactive control
Press Ctrl+C during any turn:
c - Continue execution
r - Retry current turn
e - Edit handoff.md in $EDITOR
m - Add message to handoff
i - Inspect current state
q - Quit
The workflow also pauses automatically on NEXT: human or when max_rework is exceeded.
Adding agents
No code changes needed. Create a prompt file, add the agent to agents.json, and route to it by writing NEXT: <role> in a handoff block.
"security_reviewer": {
"backend": "claude",
"prompt_file": "prompts/security_reviewer.md"
}
Adding backends
For CLI tools, use backend_config in agents.json — no Python needed:
"developer": {
"backend": "custom",
"backend_config": {
"command": ["my-cli", "run"],
"message_arg": "{message}",
"workspace_arg": ["--dir", "{workspace}"],
"session_arg": ["--session", "{session_id}"],
"output_format": "json",
"json_text_field": "result"
}
}
Or implement the AgentRunner interface in Python:
from agent_coordinator.application.runner import AgentRunner
from agent_coordinator.domain.models import RunResult
class MyRunner(AgentRunner):
def run(self, message, workspace, session_id=None, model=None, on_output=None):
response = call_my_tool(message)
return RunResult(session_id="some-id", text=response)
Register in agent_coordinator/cli.py and reference as "backend": "my_runner" in agents.json.
Retry behavior
If an agent doesn't update handoff.md, the coordinator retries with a reminder. If max_rework is exceeded, it escalates per the on_exceed policy.
Demo
agent-coordinator --workspace examples/tetris-demo --max-turns 30
Builds a playable HTML Tetris game through the full architect → developer → QA loop. See examples/tetris-demo/.
Tests
python3 -m unittest discover tests/ -v # unit tests
python3 -m unittest tests.test_handoff_parser -v # single file
RUN_INTEGRATION_TESTS=1 python3 -m unittest discover tests/integration/ -v # requires API tokens
Project structure
agent_coordinator/
cli.py entry point and orchestration loop
domain/ models, task lifecycle, retry policy (no I/O)
application/ router, prompt builder, task service, runner interface
infrastructure/ backend runners, PTY subprocess, TUI, file I/O
handoff_parser.py regex parser for handoff blocks
prompts/ role instructions and shared protocol rules
helpers/ import/export utilities
tests/ unit and integration tests
docs/ protocol spec, workflow details, backend guide
examples/ tetris demo, sample configs
Further reading
- ARCHITECTURE.md — hexagonal design, data flow, extension points
- docs/protocol.md — handoff block specification
- docs/workflow.md — coordinator loop and task lifecycle
- docs/custom-backends.md — any CLI as a backend
- docs/interactive-control.md — Ctrl+C menu and human intervention
License
MIT
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