Can I use Claudish for UI and visual design tasks?

Absolutely. You can select vision-capable models like Qwen or Gemini through Claudish to handle UI implementation and design-to-code tasks.

Why should I use Claudish through a sub-agent instead of directly?

Running Claudish through a sub-agent prevents your main context window from being flooded with thousands of tokens of reasoning and tool output, maintaining the efficiency of your main conversation.

Which models are best for coding with Claudish?

Currently, x-ai/grok-code-fast-1 is recommended for speed and agentic tasks, while google/gemini-2.5-flash and openai/gpt-5 are preferred for complex reasoning and architecture.

Do I need an OpenRouter API key to use this skill?

Yes, an OpenRouter API key is required and should be set as the OPENROUTER_API_KEY environment variable to access alternative models.

How do I prevent Claude Code from asking for an Anthropic key when using Claudish?

It is recommended to set a placeholder ANTHROPIC_API_KEY environment variable to prevent the CLI from triggering credential dialogs while Claudish is handling the proxying.

Claudish Multi-Model Integration

Name: Claudish Multi-Model Integration
Author: MadAppGang

byMadAppGang

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177

开发者工具

Enables Claude Code to execute tasks using alternative models like Grok, GPT-5, and Gemini through a specialized sub-agent workflow.

关于

This skill provides a comprehensive framework for integrating the Claudish CLI with Claude Code, allowing developers to leverage any OpenRouter-compatible model within their existing workflow. By enforcing a strict sub-agent delegation pattern, it prevents context window pollution and ensures that heavy reasoning or multi-step implementations don't overwhelm the main conversation. It includes a detailed agent selection matrix, file-based instruction patterns, and model management tools to help developers switch seamlessly between providers like xAI, Google, and OpenAI for specialized coding tasks.

主要功能

177 GitHub stars
Multi-model support for Grok, GPT-5, Gemini, and MiniMax via OpenRouter proxying.
Automated agent selection matrix for coding, architecture, and testing tasks.
Strict sub-agent delegation rules to prevent 10K+ token context pollution.
File-based instruction patterns for complex, multi-phase development workflows.
Integrated model discovery and fuzzy search for OpenRouter's curated coding models.

使用场景

Comparing implementation patterns across different LLM providers for the same architectural problem.
Executing rapid code iterations using Grok's fast-coding capabilities via isolated sub-agents.
Delegating complex logic implementation to high-reasoning models like GPT-5 without losing main context.

关于

主要功能

177 GitHub stars
Multi-model support for Grok, GPT-5, Gemini, and MiniMax via OpenRouter proxying.
Automated agent selection matrix for coding, architecture, and testing tasks.
Strict sub-agent delegation rules to prevent 10K+ token context pollution.
File-based instruction patterns for complex, multi-phase development workflows.
Integrated model discovery and fuzzy search for OpenRouter's curated coding models.

使用场景

Comparing implementation patterns across different LLM providers for the same architectural problem.
Executing rapid code iterations using Grok's fast-coding capabilities via isolated sub-agents.
Delegating complex logic implementation to high-reasoning models like GPT-5 without losing main context.