listener

Maintain a perpetual conversational loop with ARCHE-based premise tracing.

Updated Jun 19, 2026
One-click install
npx skills add https://github.com/gg686-jkl/listener-skill --skill listener
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: listener
Source: https://github.com/gg686-jkl/listener-skill/tree/main/claude-code/listener
Command: npx skills add https://github.com/gg686-jkl/listener-skill --skill listener

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Maintains an endless, productive dialogue by keeping the AI in a LISTEN state and using ARCHE-based Trace/Push to surface hidden premises and drive forward reasoning.

Core Features & Use Cases

  • ARCHE-driven reasoning: surface unstated premises, identify contradictions, and propose concrete directions.
  • Stateful conversation: never-ending loop with safety gates; exit only via /listener-stop.
  • Applicable to long-running reasoning, coaching, and decision-support tasks requiring first-principles analysis.

Quick Start

Enter the loop by sending /listener to begin and return to LISTEN after each turn.

Frequently Asked Questions about listener

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

FAQPage Schema
How does stateful conversation management improve long-running AI dialogue?

Stateful conversation management maintains a perpetual loop that keeps AI agents in a LISTEN state, surfacing unstated premises and driving forward reasoning for long-running dialogue scenarios. It ensures continuous, productive interaction without losing context.

How do I trace first principles in conversational AI for decision support?

You trace first principles in conversational AI by applying ARCHE-based reasoning to surface hidden premises and identify contradictions. This stateful decision engine pushes reasoning forward, ensuring clarity controls during research, coaching, or decision-support tasks.

Can I run a continuous reasoning loop with safety gates for AI agents?

Yes, you can run a continuous reasoning loop with built-in safety gates by initiating the stateful conversation with a command. The loop remains active and endless, returning to a LISTEN state after each turn until explicitly stopped by the user.

What is the best way to surface hidden premises in AI coaching sessions?

The best way to surface hidden premises in AI coaching sessions is using ARCHE-driven reasoning within a perpetual conversational loop. This stateful engine applies comprehension and clarity controls to identify unstated assumptions and propose concrete directions.

How to stop a perpetual conversational loop during long-running dialogue?

To stop a perpetual conversational loop during long-running dialogue, you must explicitly issue the dedicated stop command. The stateful decision engine only exits the continuous LISTEN cycle and safety gates when it receives this specific exit instruction.

Does this stateful decision engine work for research and decision support?

Yes, the stateful decision engine works for research and decision support. It applies first-principles tracing and ARCHE-based reasoning to long-running dialogue scenarios, maintaining comprehension and clarity controls to ensure safe, continuous interaction across these domains.