Manage AGREE, COUNTER, and CLARIFY consensus loops for Hive framework modules.
npx skills add https://github.com/inhyoe/hive-plugin --skill hive-consensus
Please help me install this Agent Skill. Skill: hive-consensus Source: https://github.com/inhyoe/hive-plugin/tree/main/skills/hive-consensus Command: npx skills add https://github.com/inhyoe/hive-plugin --skill hive-consensus
This Skill streamlines the process of reaching a mutual agreement between AI agents and human leads on the technical approach for developing specific software modules, preventing misunderstandings and ensuring alignment before implementation begins.
Initiate the consensus protocol for the 'authentication' module by sending a task proposal.
High-intent search queries and answers about installing and using this skill.
You can achieve technical agreement by using a bidirectional consensus protocol that facilitates structured debates between human leads and AI agents. This ensures mutual alignment on implementation plans before the development phase begins.
The consensus process uses AGREE, COUNTER, and CLARIFY loops to manage structured debates between agents and leads. This handles technical agreement sequentially for specific modules, ensuring alignment on implementation strategies.
You handle consensus for dependent modules sequentially within the Hive framework. This ensures that technical agreements for foundational modules are established before proceeding to dependent ones.
You need a bidirectional consensus protocol when developing new features that require explicit agreement from AI agents on the implementation strategy for each part. It prevents misunderstandings and ensures team collaboration before coding starts.
Yes, the consensus protocol ensures each agent focuses on reaching technical agreement specifically for their designated software module. You initiate the process by sending a task proposal for the target module.
Yes, the Hive framework supports a CLARIFY loop within its bidirectional consensus protocol to resolve technical misunderstandings. This allows agents and leads to request clarification and ensure alignment before implementation.
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