Why should I use a local LLM instead of Claude?

Local LLMs are faster for lightweight reasoning, provide a private environment for brainstorming, and help you save Claude API credits for more complex tasks.

How do I configure which local model to use?

Ensure Ollama is running and set the env.OLLAMA_MODEL variable to your desired model in your .claude/settings.local.json file.

Can I use this for security-sensitive code analysis?

It is not recommended for security audits or sensitive auth flows; it is best used for general architecture planning and implementation logic.

Does Ollama Consult replace Claude for technical decisions?

No, it acts as a fast sounding board for planning and brainstorming; you should always validate final technical decisions with Claude or official documentation.

Does it support large-scale multi-file reasoning?

Local models typically have smaller context windows than Claude, so this skill is best suited for specific questions or focused component logic.

Ollama Consult

Name: Ollama Consult
Author: UtakataKyosui

byUtakataKyosui

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生产力与工作流

Consults local LLMs via Ollama to brainstorm implementation strategies, validate architectural plans, and reduce API costs.

Ollama Consult bridges the gap between Claude's high-level reasoning and local LLM efficiency by providing a private, fast sounding board for development decisions. It allows users to offload lightweight tasks, compare multiple implementation approaches, and brainstorm technical trade-offs without consuming Claude's API quota. Ideal for early-stage planning and architectural 'rubber ducking,' this skill helps developers refine their direction and explore alternative perspectives before committing to a specific implementation path in their codebase.

主要功能

01Structured output support for clear pros/cons and decision matrices

023 GitHub stars

03Context-aware querying to provide local models with relevant project background

04Trade-off analysis for comparing multiple implementation strategies

05Local LLM integration via Ollama for private, fast brainstorming

06Cost-efficient reasoning by offloading lightweight tasks to local hardware

使用场景

01Brainstorming alternative perspectives on design problems before writing code

02Validating technical plans against specific constraints like performance and simplicity

03Comparing architectural patterns like Redis vs. in-memory caching for specific scenarios

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add utakatakyosui/c2lab ollama-consult

For use in Claude.ai and ChatGPT