Coordinate three AI workers to reach consensus decisions via majority vote.
npx skills add https://github.com/kentanakae/claude-code-plugins --skill magi-kentanakae
Please help me install this Agent Skill. Skill: magi Source: https://github.com/kentanakae/claude-code-plugins/tree/main/plugins/core/skills/magi Command: npx skills add https://github.com/kentanakae/claude-code-plugins --skill magi-kentanakae
This Skill facilitates decision-making by three AI consensus, mimicking the MAGI system from Evangelion. It is suitable for critical judgment scenarios such as design decisions, code reviews, and policy-making.
Create a MAGI system team and initiate a decision-making process for a specific task.
High-intent search queries and answers about installing and using this skill.
AI consensus decision-making works by simulating three distinct AI workers evaluating a task from unique perspectives and resolving the final decision through a majority vote system. This mechanism ensures balanced outcomes for design choices, code reviews, and policy-making.
To set up an AI consensus team for design decisions, create a team environment and initiate a specific task. The system automatically automates task creation and execution for each AI worker, evaluating the task to reach a final decision.
Yes, you need task management and messaging tools to run AI consensus code reviews. The system requires tools for team creation, task listing, updating, retrieving, messaging, and deletion to automate worker execution and finalize decisions.
The best way to resolve critical judgment scenarios in software engineering is using a three AI consensus system. It handles design decisions, code reviews, and policy-making by aggregating multiple perspectives through a majority vote.
Yes, you can use Python scripts for deterministic tasks within an AI consensus workflow. The system executes Python scripts to handle deterministic operations while the three AI workers focus on evaluation and decision-making.
YH-05Validate Agent Teams API team creation, task dependencies, messaging, and lifecycle.
raykCoordinate subagents with parallel calls, token budgets, and voting.
proofoftomCoordinate autonomous agents via A2A protocol with Agent Card discovery and task lifecycles.
jimmymalhanResolve multi-agent disagreements using deterministic rules for consensus decisions.
