agent-logic

Structure multi-agent debates with Optimist and Critic personas.

Updated Jan 16, 2026
One-click install
npx skills add https://github.com/JuelHossain/kalshi-trading-team --skill agent-logic
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: agent-logic
Source: https://github.com/JuelHossain/kalshi-trading-team/tree/main/ai-env/skills/agent-logic
Command: npx skills add https://github.com/JuelHossain/kalshi-trading-team --skill agent-logic

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Solves fragmented AI decision making by providing structured reasoning frameworks and debate personas.

Core Features & Use Cases

  • Optimist persona focusing on positive expected value and alignment with news
  • Critic persona focusing on variance, slippage, and liquidity risks
  • Debate gate with consensus, confidence, and variance thresholds
  • Evolution-aware prompts and traceability for Brain/Gateway cycles

Quick Start

Load the agent-logic skill to enable Optimist and Critic personas for the Brain's Gemini cycle and to guide prompt construction.

Frequently Asked Questions about agent-logic

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

FAQPage Schema
How do I fix fragmented AI decision making in multi-agent systems?

Fix fragmented AI decision making by applying structured reasoning frameworks and debate personas to multi-agent cycles. This enforces modular persona loading and debate gating, resulting in traceable, consensus-driven decisions rather than scattered outputs.

What is structured multi-agent debate for AI reasoning?

Structured multi-agent debate is a reasoning mechanism where Optimist and Critic personas evaluate decisions against risk and alignment thresholds. It applies debate gating to guide the Brain's reasoning, yielding traceable and consensus-driven AI outputs.

How do I implement Optimist and Critic personas for AI evaluation?

Implement Optimist and Critic personas by loading a reasoning skill that assigns positive expected value evaluation to the Optimist and variance risk analysis to the Critic. This enforces debate gating with confidence thresholds to generate traceable consensus.

Can I enforce debate gating and consensus thresholds in AI agent cycles?

Yes, you can enforce debate gating in AI agent cycles by applying structured reasoning frameworks with defined consensus, confidence, and variance thresholds. This mechanism gates the Brain's reasoning process to ensure decisions meet strict evaluation criteria before proceeding.

How do I log evolution and traceability for AI multi-agent reasoning?

Log evolution and traceability for AI multi-agent reasoning by applying evolution-aware prompts and structured persona debates during Brain/Gateway cycles. This process records the decision trajectory, yielding a traceable history of how consensus was reached.

What are the limitations of using structured personas for AI debate?

A limitation of using structured personas for AI debate is the dependency on predefined Optimist and Critic roles, which restricts reasoning to binary risk and value evaluations. This basic framework may lack flexibility for complex, multi-dimensional AI agent governance.