Frame Check — Meta-Module Orchestrator

Analyzes conversation history to identify framing effects and proposes an alternative question for reframing.

16|Updated Feb 20, 2026
One-click install
npx skills add https://github.com/worksystems-design/libertee --skill frame-check-meta-module-orchestrator
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Frame Check — Meta-Module Orchestrator
Source: https://github.com/worksystems-design/libertee/tree/main/skills/frame-check
Command: npx skills add https://github.com/worksystems-design/libertee --skill frame-check-meta-module-orchestrator

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Frame Check reveals how prompt framing shapes the answer space, enabling precise evaluation of thought processes.

Core Features & Use Cases

  • Frame analysis after a thinking session to surface framing effects.
  • Meta-Module orchestration to coordinate a Frame Analyst and other agents.
  • Guidance for reframing questions to expand solution spaces and improve reasoning quality.

Quick Start

Run /libertee:frame-check after a thinking session to reveal framing effects and provide a reframed question for broader exploration.

Frequently Asked Questions about Frame Check — Meta-Module Orchestrator

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

FAQPage Schema
What is prompt framing and how does it shape AI responses?▼

Prompt framing shapes the space of possible answers by implicitly directing the reasoning path. Frame Check identifies these framing mechanisms after a thinking session to reveal hidden biases and guide reframe prompts for broader exploration.

How do I analyze framing effects in a multi-agent AI discussion?▼

You can analyze framing effects in multi-agent discussions by running Frame Check after a thinking session. It reads conversation history, enumerates active framing mechanisms, and presents an alternative question to expand the solution space.

Can I use metacognition techniques to improve reasoning quality in AI assistants?▼

Yes, applying metacognition through frame analysis improves reasoning quality. Frame Check acts as a meta-module orchestrator, evaluating how questions were framed and suggesting reframed prompts to avoid constrained answer spaces.

What is the best way to reframe a question to expand the solution space?▼

The best way to reframe a question is to use a Frame Analyst agent to review the conversation history and identify specific framing mechanisms. Frame Check then generates a single alternative question to guide broader exploration.

Does frame analysis work after a reasoning session or during prompt generation?▼

Frame analysis works specifically after a reasoning session. Frame Check is applied to the completed conversation history to surface framing effects that shaped the answers, rather than acting during initial prompt generation.

When should I avoid using a meta-module orchestrator for prompt framing?▼

You should avoid using a meta-module orchestrator like Frame Check if you need real-time prompt generation or lack a completed conversation history. It requires existing multi-agent discussions to analyze framing effects effectively.