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•

데이터 과학 및 ML

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.

주요 기능

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

사용 사례

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

주요 기능

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

사용 사례

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