guard

Validate negotiation decisions against floor price and profit margin guardrails.

3|2|Updated Jan 24, 2026
One-click install
npx skills add https://github.com/zaebee/aura --skill guard-zaebee
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: guard
Source: https://github.com/zaebee/aura/tree/main/core/src/hive/proteins/guard
Command: npx skills add https://github.com/zaebee/aura --skill guard-zaebee

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill acts as a critical safety net, preventing AI agents from making financially unsound decisions by enforcing predefined economic rules like floor prices and profit margins.

Core Features & Use Cases

  • Decision Validation: Ensures proposed actions (accepting or countering an offer) adhere to strict financial guardrails.
  • Safe Price Calculation: Automatically generates a safe counter-offer if a proposed price violates safety parameters.
  • Use Case: An AI agent is negotiating to sell an item. The Guard Skill ensures the offered price is above the minimum floor price and meets the required profit margin, preventing losses.

Quick Start

Use the guard skill to validate the safety of a proposed decision with a price of 100 and a floor price of 90.

Frequently Asked Questions about guard

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

FAQPage Schema
How do I enforce floor prices and profit margins in AI negotiation decisions?

Calculating a safe price in automated negotiation involves enforcing financial guardrails like floor prices and profit margins. When a proposed price violates these safety parameters, the system automatically generates a deterministic safe counter-offer to prevent losses.

What is a safety guardrail for AI-driven financial negotiations?

To validate a proposed negotiation offer, you check it against strict financial guardrails such as floor prices and minimum profit margins. If the proposed price violates these parameters, the system automatically calculates a deterministic safe counter-offer.

How do I calculate a safe price when an AI agent's offer violates profit margin requirements?

To prevent economic losses in automated negotiations, you enforce strict financial guardrails. By validating proposed decisions against minimum floor prices and required profit margins, the system ensures AI agents do not accept financially unsound offers.

Does this negotiation validation approach require external dependencies to enforce economic boundaries?

Validating negotiation decisions against safety guardrails works by checking a proposed price against a minimum floor price and required profit margin. If the validation fails, it generates a deterministic safe counter-offer to enforce financial integrity.