consensus

Synthesize multi-agent perspectives on design problems into a structured recommendation report.

14|6|Updated Feb 3, 2026
One-click install
npx skills add https://github.com/tyevans/tackline --skill consensus-tyevans
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: consensus
Source: https://github.com/tyevans/tackline/tree/main/skills/workflows/consensus
Command: npx skills add https://github.com/tyevans/tackline --skill consensus-tyevans

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill helps resolve complex design decisions by synthesizing multiple, expert perspectives, surfacing hidden trade-offs and leading to more robust architectural choices.

Core Features & Use Cases

  • Multi-Perspective Analysis: Deploys three specialized agents to analyze a design problem from different quality attribute lenses (e.g., Simplicity, Performance, Security).
  • Trade-off Identification: Clearly articulates the compromises inherent in each proposed solution.
  • Synthesized Recommendation: Provides a consolidated report with agreements, tensions, and a final recommendation based on user input.
  • Use Case: When deciding between two different database technologies for a new microservice, use Consensus to explore the implications of each choice on performance, maintainability, and operational cost.

Quick Start

Use the consensus skill to decide between event sourcing or CQRS-lite for the new billing module.

Frequently Asked Questions about consensus

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

FAQPage Schema
How do I resolve trade-offs between competing quality attributes in software architecture?

Resolve architectural trade-offs by deploying a multi-agent synthesis process that analyzes design problems from distinct quality attribute lenses like simplicity, performance, and maintainability, surfacing hidden compromises to guide robust design decisions.

What is multi-agent synthesis for architectural decision-making?

Multi-agent synthesis for architectural decision-making is a process where three specialized agents analyze a design problem from different perspectives, identify inherent trade-offs, and generate a structured report with agreements, tensions, and a final recommendation.

How do I analyze design tensions when choosing between different database technologies?

Analyze design tensions by using multi-agent synthesis to explore the implications of competing database technologies on performance, maintainability, and operational cost, articulating the compromises inherent in each proposed solution.

Does this multi-agent analysis support deeper evaluation of architectural design decisions?

Yes, the multi-agent analysis supports optional debate rounds for deeper evaluation of architectural design decisions, allowing specialized agents to thoroughly explore tensions before providing a synthesized recommendation.

When should I use multi-agent synthesis for design decisions?

Use multi-agent synthesis for design decisions when you need to resolve complex architectural choices by clearly articulating compromises, synthesizing multiple expert perspectives, and obtaining a structured report with a final recommendation.

Can I use this approach to decide between event sourcing and CQRS-lite for a billing module?

Yes, you can use this approach to decide between event sourcing and CQRS-lite for a billing module by synthesizing multiple expert perspectives to surface hidden trade-offs and produce a final architectural recommendation.