military-commissar

Enforce agent accountability using a five-step methodology and rigorous checklists.

322|29|Updated Aug 18, 2025
One-click install
npx skills add https://github.com/linkerlin/PUAX --skill military-commissar
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: military-commissar
Source: https://github.com/linkerlin/PUAX/tree/main/skills/military-commissar
Command: npx skills add https://github.com/linkerlin/PUAX --skill military-commissar

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses issues of accountability and responsibility within AI agent teams, preventing "blame-shifting" and ensuring tasks are completed with a strong sense of ownership.

Core Features & Use Cases

  • Accountability Framework: Implements a five-step methodology (Accountability, Education, Motivation, Supervision, Summary) to systematically address problems.
  • Rigorous Checklists: Utilizes detailed checklists to ensure thoroughness in debugging and review processes.
  • Use Case: When an AI agent fails to debug an issue, the military-commissar skill can be invoked to enforce ownership, guide the agent through a structured problem-solving process, and ensure lessons are learned.

Quick Start

Invoke the military-commissar skill to enforce ownership and accountability for the current task.

Frequently Asked Questions about military-commissar

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

FAQPage Schema
How do I enforce accountability and stop blame-shifting in AI agent debugging tasks?▼

Accountability in AI agent debugging is enforced by applying a five-step methodology of accountability, education, motivation, supervision, and summary to systematically hold agents responsible for completing the task.

What is the structured methodology for enforcing ownership consciousness during code review?▼

The structured methodology for enforcing ownership consciousness during code review uses a five-step framework: Accountability, Education, Motivation, Supervision, and Summary, supported by rigorous checklists to ensure thoroughness and prevent blame-shifting.

How to systematically hold AI agents responsible for failed debugging issues?▼

To systematically hold AI agents responsible for failed debugging issues, apply the five-step accountability framework to educate, motivate, and supervise the agent through the debugging process, ensuring lessons are summarized afterward.

Can I use this accountability framework with enterprise AI agent workflows like Alibaba or Huawei?▼

Yes, you can use this accountability framework with enterprise AI agent workflows like Alibaba and Huawei, as the military-commissar skill is explicitly compatible with specific enterprise flavors and supports aggressive, high-intensity enforcement tones.

When do I need to invoke an aggressive accountability skill for AI agent teamwork?▼

You need to invoke an aggressive accountability skill for AI agent teamwork when agents fail to debug issues, shift blame, or lack ownership, requiring rigorous checklists and high-intensity supervision to ensure task completion.