safety-packs

Manage safety rule packs and block/allow policies for AI harnesses.

Updated May 11, 2026
One-click install
npx skills add https://github.com/AesopScott/mojo --skill safety-packs
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: safety-packs
Source: https://github.com/AesopScott/mojo/tree/main/harnesses/skills/safety-packs
Command: npx skills add https://github.com/AesopScott/mojo --skill safety-packs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a structured framework for managing safety enforcement, allowing operators to define, test, and implement granular capability controls and block/allow policies without accidental overreach.

Core Features & Use Cases

  • Capability Control: Define specific rule packs to govern what actions or content the AI is permitted to execute.
  • Policy Enforcement: Manage block/allow lists to ensure strict adherence to safety boundaries.
  • Use Case: When deploying a new AI feature, use this skill to define a safety rule pack that prevents the model from accessing sensitive internal APIs while allowing it to interact with public-facing documentation.

Quick Start

Use the safety-packs skill to inspect the current safety harness and propose a new block policy for the specified capability boundary.

Frequently Asked Questions about safety-packs

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I enforce AI safety boundaries and policy rules within a system harness?

AI safety boundaries are enforced by managing safety rule packs and block/allow policies to govern capability controls, preventing models from executing unauthorized actions or accessing restricted APIs.

What is a safety rule pack for capability control and when do I need it?

A safety rule pack is a structured framework defining specific block or allow policies for AI actions. You need it when deploying new AI features to ensure strict adherence to operational risk mitigation boundaries.

How do I configure block and allow policies to prevent AI access to sensitive APIs?

You configure block and allow policies by defining granular capability controls within the safety harness, explicitly blocking sensitive internal APIs while permitting interaction with approved public-facing resources.

Can I use safety rule packs for system configuration auditing and risk mitigation?

Yes, safety rule packs apply directly to system configuration auditing and risk mitigation workflows, requiring precise definition of failure modes, control levers, and verification tests to ensure safe operational changes.

What is the best way to define failure modes and control levers for AI governance?

The best way to define failure modes and control levers for AI governance is using a structured safety pack framework to propose, inspect, and test block policies against specified capability boundaries.

What are the limitations of managing AI safety policies without precise verification tests?

Without precise verification tests, managing AI safety policies risks accidental overreach or boundary failures, as operators cannot ensure safe operational changes or validate that capability controls function correctly.