council

Coordinate three specialized agents to research and synthesize consensus answers.

1|Updated May 17, 2026

Search Tags:#agent collaboration #multi-model analysis #collaborative research #consensus-driven answer #council-based analysis

Ready to run

npx skills add https://github.com/djimit/djimitflo --skill council-djimit

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: council
Source: https://github.com/djimit/djimitflo/tree/main/.opencode/skills/council
Command: npx skills add https://github.com/djimit/djimitflo --skill council-djimit

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a structured approach to collaborative research and analysis, leveraging a General Council of agents to ensure a well-reasoned, consensus-driven answer to a question.

Core Features & Use Cases

General Council Collaboration: Utilizes a council of three specialized agents (generalist, skeptic, domain expert) to tackle a research question.
Research Context Formation: Assembles relevant research context based on user queries.
Parallel Execution: Concurrently dispatches the agents to perform research.
Disagreement Resolution: Handles discrepancies in findings with targeted follow-up discussions.
Synthesis: Integrates the research from all agents into a final answer.

Quick Start

Run the 'council' skill to obtain an analysis on the latest AI advancements in the field of computer vision.

Frequently Asked Questions about council

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

FAQPage Schema

How does multi-agent consensus analysis work for collaborative research?▼

Multi-agent consensus analysis works by dispatching a council of three specialized agents—a generalist, a skeptic, and a domain expert—to research a query in parallel. The system resolves disagreements through targeted follow-up discussions and synthesizes the findings into a single consensus-driven answer.

How do I get a consensus-driven answer using a multi-model research council?▼

To get a consensus-driven answer, you provide a research query to the council skill. The system forms a research context, concurrently dispatches the three agents to perform research, resolves any discrepancies in their findings, and integrates the results into a final synthesized answer.

What is the best way to resolve disagreements in multi-agent collaborative research?▼

The best way to resolve disagreements in multi-agent collaborative research is through targeted follow-up discussions. The council mechanism handles discrepancies in findings between the generalist, skeptic, and domain expert automatically before aggregating the results into a final synthesis.

Can I use this multi-agent council approach for any type of research inquiry?▼

Yes, you can use the multi-agent council approach for any research inquiry requiring a well-reasoned answer. It is particularly effective for complex subjects where multiple perspectives—such as general knowledge, critical analysis, and domain expertise—are needed to reach a reliable consensus.

When should I use a council-based analysis instead of a single-agent approach?▼

You should use a council-based analysis instead of a single-agent approach when your research question demands a well-reasoned, consensus-driven answer. The parallel execution of generalist, skeptic, and domain expert agents ensures comprehensive context formation and disagreement resolution that a single agent cannot provide.

Does collaborative research with a specialized agent council require external dependencies?▼

No, collaborative research with a specialized agent council does not require external dependencies. The skill operates independently using its internal scripts and references to manage context formation, parallel research execution, disagreement resolution, and final synthesis.