Approval
An approval is an explicit human confirmation that authorizes an AI agent to proceed with a proposed action. Approvals are a foundational mechanism of human-in-the-loop agent design, ensuring that consequential or irreversible actions are reviewed before execution.
Why Approvals Matter
AI agents can act quickly and autonomously — which is powerful, but risky. Without approval gates, an agent might:
- → Delete files or records it shouldn't
- → Deploy code to production prematurely
- → Send messages or emails on your behalf
- → Make API calls with real-world side effects
Approval checkpoints give humans the opportunity to catch mistakes before they become costly.
How Approvals Work in AgentRQ
When a Claude Code agent determines it needs human sign-off, it uses the AgentRQ MCP tool to pause and send a notification to your task board. You review the proposed action, then reply with approval or rejection. The agent resumes or adjusts based on your response.
This flow looks like:
- Agent reaches a decision point
- Agent calls
createTaskorreplyvia AgentRQ MCP - You receive a real-time notification
- You approve, reject, or provide feedback
- Agent continues with updated context
Approval vs. Notification
| Mechanism | Description |
|---|---|
| Notification | Informational — agent keeps running |
| Approval | Blocking — agent waits for your response |
Designing Good Approval Gates
- → Approve before irreversible actions — database migrations, file deletions, deployments
- → Approve before ambiguous decisions — when the agent is uncertain about intent
- → Don't over-gate — too many approvals break flow; focus on high-stakes moments