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robwestz
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disabled-skill

Disable model invocation in AI workflows for policy compliance.

Updated Feb 25, 2026
Search Tags:#safety#privacy#prompt-security#disable#model-invocation#ai-control
One-click install
npx skills add https://github.com/robwestz/bacowr_b --skill disabled-skill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: disabled-skill
Source: https://github.com/robwestz/bacowr_b/tree/main/every-marketplace/tests/fixtures/sample-plugin/skills/disabled-skill
Command: npx skills add https://github.com/robwestz/bacowr_b --skill disabled-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Disable model invocation within AI workflows to prevent prompts from triggering unintended actions and to protect prompts from hijacking or leakage.

Core Features & Use Cases

  • Invocation control: Prevents automatic model invocation within orchestration, ensuring prompts are not executed by the model.
  • Safer testing and sandboxing: Ideal for development and QA where prompt execution must be isolated.
  • Policy compliance and privacy: Helps enforce internal policies by blocking external or unsafe invocation paths.

Quick Start

Disable the model invocation when running AI tasks.

Frequently Asked Questions about disabled-skill

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

FAQPage Schema
How do I disable model invocation in AI workflows to prevent prompt execution?▼

To disable model invocation, you configure the workflow to block automatic prompt execution by the AI model. This ensures prompts are not triggered inadvertently, protecting the system from hijacking or leakage during orchestration.

What is model invocation control used for in prompt security and AI isolation?▼

Model invocation control is used to prevent automatic prompt execution within AI orchestration. It enforces prompt security and privacy by ensuring no prompt invocation is executed by the model without explicit authorization.

Can I use model disabling for sandboxed testing and QA environments?▼

Yes, disabling model invocation is ideal for sandboxed testing and QA environments. It isolates prompt execution during development, ensuring that test prompts do not trigger unintended actions or interact with external systems.

Does blocking model invocation help enforce AI policy compliance in production?▼

Blocking model invocation helps enforce policy compliance in production workflows. It prevents prompts from triggering unintended actions and blocks external or unsafe invocation paths, ensuring strict adherence to internal policies.

What are the limitations of disabling model invocation in AI orchestration?▼

Disabling model invocation halts prompt execution entirely within the workflow. Consequently, it prevents the AI model from processing or acting on any prompts, making it unsuitable for tasks requiring dynamic model responses or active generation.

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