skills.rest
arvidfcjarfalla-prog
arvidfcjarfalla-progCOMMUNITY
Explore all skills by this author →
GitHub

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
One-click install
npx skills add https://github.com/arvidfcjarfalla-prog/atlas --skill consensus-arvidfcjarfalla-prog
Or copy as Structured Prompt for Agent▼
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.

Related Skills

Explore More Data & Analytics Skills→
superfhpsuperfhp

one-three-one-rule

Generate a 1-3-1 decision document with problem, options, and recommendation.

Community
Intermediate
cyberswatcyberswat

decide

Present viable decision paths with structured records and reversal triggers.

Community
Advanced
vuralserhat86vuralserhat86
43

python_data_stack

Build Python data pipelines with Polars, DuckDB, Statsmodels, and Prefect.

Community
Advanced
ezjonlineezjonline
1

stochastic-multi-agent-consensus

Aggregate multiple agent analyses into consensus, divergence, and outlier sections.

Community
Advanced