local-model-mcp

Route review tasks through run_helper with local-model MCP presets.

Updated Mar 22, 2026
One-click install
npx skills add https://github.com/bja2142/vibes --skill local-model-mcp
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: local-model-mcp
Source: https://github.com/bja2142/vibes/tree/main/model-mcp/skills/local-model-mcp
Command: npx skills add https://github.com/bja2142/vibes --skill local-model-mcp

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

The Local Model MCP provides a centralized way to obtain second opinions, reuse reusable presets, and perform cross-model comparisons with a local MCP server. It also supports session management, export, and handoffs across models to improve review quality and continuity.

Core Features & Use Cases

  • Second opinion from a single local model
  • Reusable presets such as security review or adversarial critique
  • Cross-model comparison or synthesis
  • Moving a stored session from one provider to another
  • Inspecting, labeling, exporting, or deleting stored sessions

Quick Start

Invoke the local-model-mcp via run_helper with a preset or raw provider to start a review.

Frequently Asked Questions about local-model-mcp

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

FAQPage Schema
How do I get a second opinion from a local model during code review?

To get a second opinion, route your task through the run_helper command with a raw provider or preset. This local-model workflow applies cross-model comparisons and preset-driven reviews to generate alternative feedback.

What are reusable presets for local model reviews?

Reusable presets are predefined review configurations like security review or adversarial critique. You apply them through the run_helper command to consistently execute specialized review tasks across different local models.

How do I manage and hand off sessions between different local models?

You manage and hand off sessions by using session management commands within run_helper to inspect, label, export, or move stored sessions. This allows moving a stored session from one provider to another for cross-model synthesis.

Can I compare outputs across multiple local models for the same prompt?

Yes, you can perform cross-model comparison by routing tasks through run_helper. The workflow supports calling different providers and synthesizing their outputs to compare responses directly within your local-model environment.

Do I need a local MCP server to run cross-model comparisons and presets?

Yes, a local MCP server is required. The skill coordinates preset-driven reviews and session handoffs by routing tasks through the local-model MCP, relying on the server to manage provider calls and stored sessions.