Which models are used by the local and remote tools?

The 'ask-local' tool utilizes Qwen3-4B for fast, local processing, while the 'ask-remote' tool queries GPT-4.1-mini for more complex reasoning tasks.

What is the benefit of bypassing the consensus protocol?

Bypassing consensus with direct-query reduces latency and API costs for tasks that only require a single model's perspective, such as simple pattern matching or classification.

How does dissent testing work in this skill?

Dissent testing identifies a minority view among models and explicitly tasks a 'surgeon' to build the strongest possible case for that view (steelmanning) before a final verdict is reached.

What are the possible verdicts of a dissent test?

A dissent test can return three statuses: 'dissent_valid' (the minority was correct), 'dissent_partially_valid' (needs more investigation), or 'dissent_unfounded' (the majority view holds).

Can I use this for automated error resolution?

Yes, the 'resolve_disagreement' function can be used within your workflow to automatically handle conflicting model opinions using the dissent protocol.

3-Surgeons Direct Query

Name: 3-Surgeons Direct Query
Author: supportersimulator

bysupportersimulator

0•

数据科学与机器学习

Accesses specific LLM models directly and manages dissent testing to eliminate reasoning blind spots without full consensus overhead.

The Direct Query skill provides targeted access to the 3-Surgeons multi-model ecosystem, allowing developers to bypass the full consensus protocol for faster, more cost-effective results. It enables localized queries via Qwen3-4B for rapid pattern matching and remote queries via GPT-4.1-mini for complex reasoning. Most uniquely, it features a specialized dissent protocol that 'steelmans' minority opinions, forcing the system to build the strongest possible argument for a dissenting view to ensure critical decisions are not undermined by model-specific hallucinations or majority bias.

主要功能

01Cost-efficient model selection for quick classifications and sanity checks

02Targeted local querying using Qwen3-4B for zero-cost pattern recognition

03Remote access to GPT-4.1-mini for high-reasoning evidence evaluation

04Steelmanning protocol to rigorously test and validate minority viewpoints

05Automated disagreement resolution tools for multi-model conflicts

060 GitHub stars

使用场景

01Validating a controversial architectural decision by building the strongest possible case for the minority view

02Executing deep evidence analysis using high-reasoning remote models without triggering a full three-model consensus

03Performing rapid keyword extraction or severity classification using local models

主要功能

01Cost-efficient model selection for quick classifications and sanity checks

02Targeted local querying using Qwen3-4B for zero-cost pattern recognition

03Remote access to GPT-4.1-mini for high-reasoning evidence evaluation

04Steelmanning protocol to rigorously test and validate minority viewpoints

05Automated disagreement resolution tools for multi-model conflicts

060 GitHub stars

使用场景

01Validating a controversial architectural decision by building the strongest possible case for the minority view

02Executing deep evidence analysis using high-reasoning remote models without triggering a full three-model consensus

03Performing rapid keyword extraction or severity classification using local models