I Built a CLI Tool That Auto-Switches Between AI Agents When One Fails

AiAgentCreater — Tue, 28 Apr 2026 14:46:56 +0000

I Built a CLI Tool That Auto-Switches Between AI Agents When One Fails

Stop manually switching between Claude, OpenCode, Copilot, Codex, and Gemini. Let your CLI handle it.

The Problem

I was copy-pasting the same prompt into 5 different AI chat windows.

Claude was great for architecture, but when it hit rate limits, I had to switch to OpenCode. Then OpenCode had an outage, so I tried Copilot. Each switch meant:

Re-authenticating
Losing context
Wasting 2-3 minutes per switch
Getting frustrated

Sound familiar?

The Solution

I built agent-delegator — a Python CLI that monitors all your AI agents and automatically routes to the best available one.

No more manual switching. No more downtime. Just describe what you want and let the delegator pick the best agent.

What It Actually Does

1. Health Checks Every Agent

$ python -m agent_delegator health

[OK] claude: available=True, cli_found=True
[OK] opencode: available=True, cli_found=True
[OK] copilot: available=True, cli_found=True
[OK] codex: available=True, cli_found=True
[OK] antigravity: available=True, cli_found=True

Every 30 seconds, it pings all agents. If one goes down, it's marked unhealthy and skipped.

2. Smart Routing Based on Task Type

$ python -m agent_delegator routes

subagent-driven/implementation -> opencode:federated-coding
subagent-driven/testing -> opencode:federated-coding
subagent-driven/code_review -> opencode:federated-coding
subagent-driven/research -> claude:federated-sonnet
brainstorming/requirements -> claude:claude-sonnet-4-6
brainstorming/architecture -> claude:federated-sonnet
brainstorming/design -> claude:claude-sonnet-4-6
verification/testing -> opencode:federated-coding
verification/linting -> opencode:federated-free
verification/security_audit -> claude:claude-sonnet-4-6

Code review → Claude. Implementation → OpenCode. Testing → OpenCode. You define the routing matrix, the delegator follows it.

3. Automatic Failover

$ python -m agent_delegator status

=== delegator status ===
Agents: ['claude', 'opencode', 'copilot', 'codex', 'antigravity']
Active cooldowns: 0
Recent delegations: 5
  [OK] opencode:minimax-m2.5-free - implementation
  [OK] opencode:minimax-m2.5-free - implementation
  [OK] opencode:minimax-m2.5-free - implementation
  [OK] opencode:minimax-m2.5-free - implementation
  [FAIL] opencode:minimax-m2.5-free - implementation
7-day success rate: 80.0%

When OpenCode fails (see that [FAIL]?), it instantly falls back to the next agent in the priority list. No manual intervention.

Features

Feature	What It Does
Federated Failover	Auto-switches to next best agent on failure
Intelligent Routing	Different tasks → different agents based on config
Health Monitoring	Continuously checks if agents are online
Circuit Breaker	Temporarily disables failing agents (cooldowns)
Auto-Learning	Optimizes agent rankings based on success rates
Real-Time Dashboard	Local web UI at `http://127.0.0.1:8765`
Metrics Tracking	Success rates, duration, fallback counts per agent
Zero Cloud	100% local — no data leaves your machine

How to Use It

Install

pip install agent-delegator

Configure (one-time)

python -m agent_delegator init

This creates .agent-delegator.json in your project:

{
  "agents": ["claude", "opencode", "copilot", "codex", "antigravity"],
  "routes": {
    "implementation": ["opencode", "claude"],
    "code_review": ["claude", "opencode"],
    "testing": ["opencode"]
  }
}

Run a Task

python -m agent_delegator exec "Write a Python function to parse JSONL files"

The delegator will:

Check which agents are healthy
Pick the best one for "implementation" tasks
Run the task
Track success/failure
Show results

Launch Dashboard

python -m agent_delegator dashboard

Opens Mission Control at http://127.0.0.1:8765:

Live task monitor
Agent health cards with success rates
Delegation history with replay
Cost tracking
A/B model comparison

Supported Agents

Agent	CLI Command	Best For
Claude	`claude`	Architecture, security reviews
OpenCode	`opencode`	Implementation, testing
GitHub Copilot	`copilot`	Inline code completion
Codex	`codex`	Quick prototyping
Gemini	`antigravity`	Research, exploration

Adding a new agent takes 2 lines in the config.

Why I Built This

I was tired of:

Rate limits interrupting my flow
Downtime breaking my CI/CD pipeline
Manual switching wasting 10-15 minutes per session
Losing context when changing agents

Now I just run one command and the delegator handles everything.

Try It

pip install agent-delegator
python -m agent_delegator init
python -m agent_delegator exec "Your task here"

GitHub: https://github.com/amardeep434/agent-delegator

PyPI: https://pypi.org/project/agent-delegator/

What's Next

[ ] Webhook notifications (Slack, Telegram)
[ ] Cost optimization (pick cheapest capable agent)
[ ] Multi-modal support (images, documents)
[ ] Team sharing (shared routing configs)

Built with Python and too much coffee ☕

What's your agent switching workflow? Do you use multiple AI agents or stick to one?

DEV Community: AiAgentCreater

I Built a CLI Tool That Auto-Switches Between AI Agents When One Fails

I Built a CLI Tool That Auto-Switches Between AI Agents When One Fails

The Problem

The Solution

What It Actually Does

1. Health Checks Every Agent

2. Smart Routing Based on Task Type

3. Automatic Failover

Features

How to Use It

Install

Configure (one-time)

Run a Task

Launch Dashboard

Supported Agents

Why I Built This

Try It

What's Next