decision-mode

Coordinate human-in-the-loop decision gating during automated sessions.

4|2|Updated Feb 21, 2026
One-click install
npx skills add https://github.com/px-pride/axi-assistant --skill decision-mode
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: decision-mode
Source: https://github.com/px-pride/axi-assistant/tree/main/.claude/skills/decision-mode
Command: npx skills add https://github.com/px-pride/axi-assistant --skill decision-mode

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill turns AI-driven sessions into explicit, human-guided decision processes, ensuring approvals before material actions.

Core Features & Use Cases

  • Decision-point discovery and gating with user oversight and auditability
  • Intensity controls (--strict, --balanced, --light) to tailor interaction depth
  • Structured work phases and decision logging for traceability across conversations

Quick Start

Begin with a chosen intensity and present the first decision point to the user for approval

Frequently Asked Questions about decision-mode

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

FAQPage Schema
How do I add human-in-the-loop approval gates to an AI workflow?

Human-in-the-loop approval gates can be added to an AI workflow by enforcing decision discovery and gated execution, ensuring explicit user oversight before material actions are taken.

What is decision gating in automated AI sessions?

Decision gating in automated AI sessions is the process of pausing multi-step tasks at critical decision points to require explicit human approval, ensuring traceability and governance before proceeding.

How do I control the interaction depth of human oversight during AI tasks?

You can control interaction depth during AI tasks using intensity enums like --strict, --balanced, and --light, which tailor the frequency and strictness of required human approvals.

Can I maintain decision logs for AI task governance and traceability?

Yes, decision logs for AI task governance are maintained throughout the workflow phases, providing full traceability and auditability for all gated decisions across multi-step conversations.

What is the best way to enforce risk management before an AI agent takes material actions?

The best way to enforce risk management before an AI agent takes material actions is to implement structured workflow phases with strict intensity controls and mandatory gated approvals.

When should I avoid using strict decision gating for my AI workflow?

Strict decision gating should be avoided for low-risk, repetitive AI tasks where manual approval overhead outweighs governance benefits, making the --light or --balanced intensity modes more suitable.