aqua-coord 0.5.0

Autonomous QUorum of Agents - Lightweight coordinator for CLI AI agents

Aqua - Autonomous QUorum of Agents

Aqua is a lightweight, agent-agnostic coordinator for CLI AI agents. It enables multiple AI agents (Claude Code, Codex CLI, Gemini CLI, or any CLI tool) running in separate terminal sessions to collaborate on tasks within a shared codebase. Built with Claude ❤️

Why Aqua?

When working with AI coding agents, you often want multiple agents working in parallel on different tasks. But without coordination, agents can:

• Work on the same task simultaneously
• Edit the same files and create conflicts
• Lack visibility into what other agents are doing

Aqua solves this by providing:

• Shared task queue with atomic claiming
• File locking to prevent conflicts
• Inter-agent messaging for coordination
• Live monitoring to see all agent activity

Features

• Task Queue: Priority-based task management with dependencies
• Circular Dependency Detection: Prevents deadlocks by rejecting cyclic task dependencies
• File Locking: Prevent multiple agents from editing the same file
• Blocking Messages: Ask questions and wait for replies from other agents
• Live Monitoring: Real-time dashboard and event stream
• Leader Election: First agent becomes leader; leadership is heartbeat-integrated
• Crash Recovery: Automatic detection of dead agents (5min heartbeat timeout) and task reassignment
• Agent Agnostic: Works with Claude Code, Codex CLI, Gemini CLI, or any CLI tool
• Zero External Dependencies: Uses SQLite - no Redis, Docker, or external services
• JSON Mode: Full --json support and AQUA_JSON=1 env var for programmatic access
• Agent Roles: Assign specializations (frontend, backend, reviewer) so agents self-select appropriate tasks

Agent Roles

Roles let you spawn specialized agents that prioritize tasks matching their expertise. This is completely optional - agents without roles work on any available task.

Assigning Roles

# Distribute roles across agents (round-robin)
aqua spawn 3 --roles frontend,backend,testing
# worker-1: frontend, worker-2: backend, worker-3: testing

# Auto-assign predefined roles
aqua spawn 4 --assign-roles
# Cycles through: reviewer, frontend, backend, testing, devops

# Single role for all agents
aqua spawn 2 --role reviewer

How Role Matching Works

1. Tag your tasks with role-relevant tags:

   aqua add "Fix login button styling" -t frontend -p 7
   aqua add "Add user API endpoint" -t backend -p 6
   aqua add "Review authentication PR" -t review -p 8
   

2. Agents prioritize matching tasks: A frontend agent will claim tasks tagged frontend before claiming untagged tasks.

3. Fallback behavior: If no matching tasks exist, agents can still claim any available task (they're informed when doing so).

Predefined Roles

Role	Focuses on tags
reviewer	review, pr, code-review
frontend	frontend, ui, css, react, component
backend	backend, api, database, server
testing	test, testing, qa, e2e
devops	devops, deploy, ci, infra

Custom Roles

Any string works as a role - agents will match against tasks with that tag:

aqua spawn 2 --roles security,performance
aqua add "Audit auth module" -t security
aqua add "Optimize database queries" -t performance

Example: Role-Based Team

# Add tasks with appropriate tags
aqua add "Review PR #42" -t review -p 9
aqua add "Fix navbar responsiveness" -t frontend -p 7
aqua add "Add /products endpoint" -t backend -p 7
aqua add "Write integration tests" -t testing -p 6

# Spawn specialized team
aqua spawn 4 --assign-roles -b

# Each agent claims tasks matching their role first

Long-Running Projects (Serialize + Loop)

For projects that exceed a single agent's context window, Aqua provides serialize and loop mode to manage context automatically.

The Problem

AI agents have limited context windows. On multi-day projects with 10-20 tasks, the agent's context fills up with implementation details, causing mistakes and forgotten decisions.

The Solution

1. Serialize tasks into a linear chain with checkpoints
2. Loop mode respawns fresh agents at each checkpoint

# 1. Add your tasks
aqua add "Set up project structure" -p 10
aqua add "Create data models" -p 9
aqua add "Build API endpoints" -p 8
aqua add "Write tests" -p 7

# 2. Serialize into linear sequence with checkpoints
aqua serialize

# 3. Run with loop mode (single agent, auto-respawn)
aqua spawn 1 -b --loop

How It Works

aqua serialize creates a linear chain:

Task1 → Checkpoint → Task2 → Checkpoint → Task3 → Checkpoint → ...

When an agent completes a task and claims a checkpoint:

1. Agent runs aqua done for the checkpoint
2. Agent exits the session
3. Loop mode detects the exit and respawns a fresh agent
4. Fresh agent has full context window (200k tokens)
5. Agent runs aqua refresh to restore context from database

Important Constraints

• Single agent only: --loop requires count=1 because serialized tasks form a linear chain. Only one task is claimable at any time.
• Sequential execution: Tasks run one at a time with checkpoints between them
• Context in database: Task summaries survive in SQLite, restored via aqua refresh

Serialize Options

aqua serialize                  # Checkpoint after every task
aqua serialize --every 2        # Checkpoint every 2 tasks
aqua serialize --dry-run        # Preview without making changes

Adding Checkpoints to Individual Tasks

aqua add "Complex refactoring task" --checkpoint

When to Use

✅ Use serialize + loop for:

• Multi-day projects with many sequential tasks
• Projects where context accumulation causes issues
• Single-agent workflows that need fresh context

❌ Don't use for:

• Parallel work (multiple agents on independent tasks)
• Short projects that fit in one context window
• Tasks that don't have a natural sequence

For parallel work, use regular aqua spawn N without --loop.

Installation

pip install aqua-coord

Quick Start

1. Initialize Aqua in your project

cd your-project
aqua init
aqua setup --all  # Add instructions to CLAUDE.md, AGENTS.md, GEMINI.md

2. Add tasks with dependencies

aqua add "Set up project structure" -p 9
aqua add "Implement data models" -p 8 --after "Set up project structure"
aqua add "Build API endpoints" -p 7 --depends-on abc123
aqua add "Write tests" -p 6 -t tests

3. Spawn agents automatically

# Open 3 new terminal windows, each with an AI agent
aqua spawn 3

# Or run agents in background (fully autonomous)
# ⚠️  Prompts for confirmation - agents get full permissions!
aqua spawn 3 -b

# Use a specific CLI (auto-detects by default)
aqua spawn 2 --codex

# Mix agents with round-robin assignment
aqua spawn 4 -b --claude --codex  # 2 Claude + 2 Codex

# Assign roles to agents (see Agent Roles section below)
aqua spawn 3 --roles frontend,backend,testing

# Skip confirmation (for programmatic use or leader agents)
aqua spawn 2 -b -y

⚠️ Background Mode Warning: The -b flag grants agents full autonomous control using dangerous flags like --dangerously-skip-permissions (Claude) and --approval-mode full-auto (Codex). Agents can read, write, and execute ANY code without asking. Use -y to skip the confirmation prompt.

4. Monitor progress

aqua status   # Show current state
aqua watch    # Live dashboard (updates every 2s)
aqua logs     # Tail event stream in real-time

Alternative: Let the Agent Do It

After running aqua setup --all, you can simply start your AI agent and ask it to plan the project:

aqua init
aqua setup --all

# Start your AI agent (Claude Code, Codex, Gemini)
claude  # or: codex, gemini

# Then ask:
> "Plan this project and spawn workers to build it"

The agent reads the instructions from CLAUDE.md (or AGENTS.md/GEMINI.md), understands Aqua's capabilities, and handles task breakdown, agent spawning, and coordination autonomously.

Complete Command Reference

Core Commands

Command	Description
aqua init	Initialize Aqua in current directory
aqua status	Show dashboard with agents, tasks, and leader info
aqua refresh	Restore agent identity after context reset

Task Management

Command	Description
aqua add <title>	Add a new task
aqua show [task_id]	Show task details
aqua claim [task_id]	Claim next pending task (or specific task)
aqua done [--summary]	Mark current task complete
aqua fail --reason	Mark current task as failed
aqua progress <msg>	Report progress (saves state for refresh)

Options for aqua add:

aqua add "Title" \
  -d "Description" \
  -p 8 \                      # Priority 1-10 (higher = more urgent)
  -t backend \                # Tag (repeatable)
  --context "Use FastAPI" \   # Additional context
  --depends-on abc123 \       # Depends on task ID (repeatable)
  --after "Setup project"     # Depends on task by title match

Agent Management

Command	Description
aqua join [-n name]	Register as an agent
aqua leave	Leave the quorum
aqua ps	Show all agent processes
aqua kill [name|--all]	Kill agent(s)
aqua spawn <count>	Spawn AI agents in new terminals

Options for aqua spawn:

aqua spawn 3 \
  --claude \                # Use Claude Code (default: auto-detect)
  --codex \                 # Use Codex CLI
  --gemini \                # Use Gemini CLI
  --role frontend \         # Assign role (repeatable, round-robin)
  --roles fe,be,test \      # Comma-separated roles
  --assign-roles \          # Auto-assign predefined roles
  -b \                      # Background mode (autonomous)
  --loop \                  # Respawn on checkpoint exit (requires -b, count=1)
  --worktree               # Each agent gets own git worktree

Serialize (Long-Running Projects)

Command	Description
aqua serialize	Convert tasks to linear chain with checkpoints
aqua serialize --every N	Insert checkpoint every N tasks
aqua serialize --dry-run	Preview without making changes

File Locking

Prevent multiple agents from editing the same file:

aqua lock src/handlers.py     # Lock a file for exclusive editing
aqua unlock src/handlers.py   # Release a file lock
aqua locks                    # Show all current file locks

Communication

# Fire-and-forget messages
aqua msg "Need help with auth" --to worker-2
aqua msg "Starting deployment" --to @all
aqua inbox --unread

# Blocking questions (waits for reply)
aqua ask "Should I use Redis or SQLite?" --to @leader --timeout 60
# Other agent replies with:
aqua reply 42 "Use SQLite, it's simpler"

Monitoring & Recovery

aqua watch                    # Live dashboard (Ctrl+C to exit)
aqua logs                     # Tail event stream (like tail -f)
aqua logs --agent worker-1    # Filter by agent
aqua logs --json              # Machine-readable output
aqua log -n 50                # View last 50 events
aqua doctor                   # Run health checks
aqua doctor --fix             # Fix issues (recover orphaned tasks)
aqua recover                  # Recover tasks from dead agents

Setup

aqua setup --claude           # Add instructions to CLAUDE.md
aqua setup --codex            # Add instructions to AGENTS.md
aqua setup --gemini           # Add instructions to GEMINI.md
aqua setup --all              # All of the above
aqua setup --print            # Print instructions without writing

Workflow Example

Here's a typical multi-agent workflow:

# 1. Initialize and add tasks
aqua init
aqua setup --all

aqua add "Set up FastAPI project" -p 9
aqua add "Create User model" -p 8 --after "Set up FastAPI project"
aqua add "Build /users endpoints" -p 7 --after "Create User model"
aqua add "Write API tests" -p 6 -t tests

# 2. Spawn 2 agents
aqua spawn 2

# 3. In another terminal, monitor progress
aqua watch

Each spawned agent will:

1. Join with a unique name (worker-1, worker-2, etc.)
2. Claim tasks respecting dependencies
3. Lock files before editing
4. Report progress periodically
5. Mark tasks done when complete
6. Claim the next available task

JSON Mode

All commands support --json for programmatic access:

# Per-command
aqua status --json | jq .tasks
aqua claim --json | jq .id
aqua doctor --json | jq .healthy

# Global mode (affects all commands)
export AQUA_JSON=1
aqua status | jq .agents

Programmatic Integration

import subprocess
import json

def aqua(args):
    result = subprocess.run(
        ['aqua'] + args + ['--json'],
        capture_output=True, text=True
    )
    return json.loads(result.stdout) if result.returncode == 0 else None

# Join and work on tasks
agent = aqua(['join', '--name', 'my-bot'])
while True:
    task = aqua(['claim'])
    if not task:
        break
    # Do work...
    aqua(['progress', 'Working on implementation'])
    aqua(['done', '--summary', 'Implemented feature X'])

Architecture

┌─────────────────────────────────────────────────────────────┐
│                      Aqua CLI (aqua)                        │
├─────────────────────────────────────────────────────────────┤
│  Task Queue │ File Locks │ Messages │ Agent Registry        │
└─────────────────────────┬───────────────────────────────────┘
                          │
┌─────────────────────────▼───────────────────────────────────┐
│                    Coordinator Core                          │
│  • Leader Election (heartbeat-integrated with fencing)      │
│  • Task Scheduler (priority + dependencies + cycles)        │
│  • Crash Recovery (5min heartbeat + PID monitoring)         │
└─────────────────────────┬───────────────────────────────────┘
                          │
┌─────────────────────────▼───────────────────────────────────┐
│                   SQLite Database                            │
│                 .aqua/aqua.db (WAL mode)                    │
└─────────────────────────────────────────────────────────────┘

Supported Agents

CLI	Instruction File
Claude Code	CLAUDE.md
Codex CLI	AGENTS.md
Gemini CLI	GEMINI.md

Aqua auto-detects which CLI is available when using aqua spawn. Each CLI uses its own default model - override with --model if needed.

Development

# Clone and install
git clone https://github.com/vignesh07/aqua.git
cd aqua
pip install -e ".[dev]"

# Run tests
pytest

# Run with coverage
pytest --cov=aqua

# Lint
ruff check src/

License

MIT License - see LICENSE for details.

Contributing

Not accepting contributions at the moment.

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Made for the multi-agent future.