Use Latch to put an MCP policy and approval layer between agents and tools so risky calls pause for review while safe calls continue automatically.
Scanned 6/8/2026
Install via CLI
openskills install agentskillexchange/skills---
name: "Gate risky agent actions behind approval checkpoints with Latch"
slug: "gate-risky-agent-actions-behind-approval-checkpoints-with-latch"
description: "Use Latch to put an MCP policy and approval layer between agents and tools so risky calls pause for review while safe calls continue automatically."
github_stars: 8
verification: "security_reviewed"
source: "https://github.com/latchagent/latch"
author: "Latch"
publisher_type: "organization"
category: "Security & Verification"
framework: "MCP"
tool_ecosystem:
github_repo: "latchagent/latch"
github_stars: 8
---
# Gate risky agent actions behind approval checkpoints with Latch
Use Latch to put an MCP policy and approval layer between agents and tools so risky calls pause for review while safe calls continue automatically.
## Prerequisites
Docker, Latch CLI, an upstream MCP server to wrap
## Installation
Use the upstream install or setup path that matches your environment:
- git clone https://github.com/latchagent/latch
- docker compose up -d
- npx @latchagent/cli@latest run \
Requirements and caveats from upstream:
- **Risky actions** (shell commands, external sends) → Require human approval
- # Start Latch with Docker
- Policy is evaluated (allow / deny / require approval)
Basic usage or getting-started notes:
- Security guardrails for AI agents. Safe actions run automatically. Risky actions wait for approval.
- bash
- cd latch
- Source: https://github.com/latchagent/latch
- Extracted from upstream docs: https://raw.githubusercontent.com/latchagent/latch/HEAD/README.md
## Documentation
- https://latch.mintlify.app/docs/introduction
## Source
- [Agent Skill Exchange](https://agentskillexchange.com/skills/gate-risky-agent-actions-behind-approval-checkpoints-with-latch/)
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Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.