consensus

Generate varied framings and aggregate sub-agent outputs into ranked decisions.

Updated Mar 12, 2026

Search Tags:#multi-agent #aggregation #consensus #ranking #decision-support #framing

Ready to run

npx skills add https://github.com/arvidfcjarfalla-prog/atlas --skill consensus-arvidfcjarfalla-prog

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: consensus
Source: https://github.com/arvidfcjarfalla-prog/atlas/tree/main/.claude/skills/consensus
Command: npx skills add https://github.com/arvidfcjarfalla-prog/atlas --skill consensus-arvidfcjarfalla-prog

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Explore a problem from multiple angles simultaneously by spawning N sub-agents with different framings, collecting their answers, and ranking by agreement to surface robust insights.

Core Features & Use Cases

Spawns multiple framings (neutral, risk-averse, growth-oriented, contrarian, etc.) to diversify analysis.
Aggregates agent outputs via predefined schemas (Ranking, Recommendation, Scoring, Binary) for clear decision support.
Applies to user questions across product, strategy, design, and process problems to surface top consensus actions and notable divergences.

Quick Start

Provide a clear problem statement and let the skill generate framings, spawn sub-agents, and return a ranked consensus with justification.

Frequently Asked Questions about consensus

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

FAQPage Schema

How do I aggregate diverse viewpoints to reach a decision on a complex strategy problem?▼

You provide a clear problem statement, and the system automatically generates diverse framings, spawns sub-agents to evaluate them, and returns an aggregated ranking, recommendation, scoring, or binary decision.

What is multi-agent consensus ranking and how does it work for decision support?▼

Multi-agent consensus ranking spawns sub-agents with distinct perspectives like risk-averse or growth-oriented, gathers their outputs, and ranks them by agreement to surface robust decision-support insights.

Can I use multi-agent framing to evaluate product decisions from different perspectives?▼

Yes, multi-agent framing evaluates product decisions by spawning sub-agents with varied perspectives such as contrarian or neutral, collecting their analyses, and producing an aggregated recommendation.

What is the best way to analyze a problem from multiple angles simultaneously?▼

The best way to analyze a problem from multiple angles is to spawn sub-agents with diverse framings simultaneously, gather their outputs, and aggregate them into a clear ranking or binary decision.

What output formats can I get from aggregating sub-agent framings for decision support?▼

Aggregating sub-agent framings yields decision support outputs via predefined schemas, specifically returning a ranking, recommendation, scoring, or binary decision based on the gathered agent analyses.