claudish-usage
Execute Claude Code with external models via sub-agents.
Install
mkdir -p .claude/skills/claudish-usage && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1278" && unzip -o skill.zip -d .claude/skills/claudish-usage && rm skill.zipInstalls to .claude/skills/claudish-usage
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
CRITICAL - Guide for using Claudish CLI ONLY through sub-agents to run Claude Code with any AI model (OpenRouter, Gemini, OpenAI, local models). NEVER run Claudish directly in main context unless user explicitly requests it. Use when user mentions external AI models, Claudish, OpenRouter, Gemini, OpenAI, Ollama, or alternative models. Includes mandatory sub-agent delegation patterns, agent selection guide, file-based instructions, and strict rules to prevent context window pollution.Key capabilities
- →Delegate tasks to sub-agents for model execution
- →Route tasks to OpenRouter, Gemini, or OpenAI models
- →Use file-based instructions to prevent context pollution
- →Select specialized agents based on task type
- →Manage cost tracking and model selection
How it works
It enforces a delegation pattern where the main agent creates instruction files and triggers sub-agents to run Claudish, keeping the main context clean.
Inputs & outputs
When to use claudish-usage
- →Use an alternative AI model for a task
- →Delegate code review to a sub-agent
- →Maintain main context window efficiency
About this skill
Claudish Usage Skill
Version: 2.0.0 Purpose: Guide AI agents on how to use Claudish CLI to run Claude Code with any AI model Status: Production Ready
⚠️ CRITICAL RULES - READ FIRST
🚫 NEVER Run Claudish from Main Context
Claudish MUST ONLY be run through sub-agents unless the user explicitly requests direct execution.
Why:
- Running Claudish directly pollutes main context with 10K+ tokens (full conversation + reasoning)
- Destroys context window efficiency
- Makes main conversation unmanageable
When you can run Claudish directly:
- ✅ User explicitly says "run claudish directly" or "don't use a sub-agent"
- ✅ User is debugging and wants to see full output
- ✅ User specifically requests main context execution
When you MUST use sub-agent:
- ✅ User says "use Grok to implement X" (delegate to sub-agent)
- ✅ User says "ask GPT-5.3 to review X" (delegate to sub-agent)
- ✅ User mentions any model name without "directly" (delegate to sub-agent)
- ✅ Any production task (always delegate)
📋 Workflow Decision Tree
User Request
↓
Does it mention Claudish/OpenRouter/model name? → NO → Don't use this skill
↓ YES
↓
Does user say "directly" or "in main context"? → YES → Run in main context (rare)
↓ NO
↓
Find appropriate agent or create one → Delegate to sub-agent (default)
🤖 Agent Selection Guide
Step 1: Find the Right Agent
When user requests Claudish task, follow this process:
- Check for existing agents that support proxy mode or external model delegation
- If no suitable agent exists:
- Suggest creating a new proxy-mode agent for this task type
- Offer to proceed with generic
general-purposeagent if user declines
- If user declines agent creation:
- Warn about context pollution
- Ask if they want to proceed anyway
Step 2: Agent Type Selection Matrix
| Task Type | Recommended Agent | Fallback | Notes |
|---|---|---|---|
| Code implementation | Create coding agent with proxy mode | general-purpose | Best: custom agent for project-specific patterns |
| Code review | Use existing code review agent + proxy | general-purpose | Check if plugin has review agent first |
| Architecture planning | Use existing architect agent + proxy | general-purpose | Look for architect or planner agents |
| Testing | Use existing test agent + proxy | general-purpose | Look for test-architect or tester agents |
| Refactoring | Create refactoring agent with proxy | general-purpose | Complex refactors benefit from specialized agent |
| Documentation | general-purpose | - | Simple task, generic agent OK |
| Analysis | Use existing analysis agent + proxy | general-purpose | Check for analyzer or detective agents |
| Other | general-purpose | - | Default for unknown task types |
Step 3: Agent Creation Offer (When No Agent Exists)
Template response:
I notice you want to use [Model Name] for [task type].
RECOMMENDATION: Create a specialized [task type] agent with proxy mode support.
This would:
✅ Provide better task-specific guidance
✅ Reusable for future [task type] tasks
✅ Optimized prompting for [Model Name]
Options:
1. Create specialized agent (recommended) - takes 2-3 minutes
2. Use generic general-purpose agent - works but less optimized
3. Run directly in main context (NOT recommended - pollutes context)
Which would you prefer?
Step 4: Common Agents by Plugin
Frontend Plugin:
typescript-frontend-dev- Use for UI implementation with external modelsfrontend-architect- Use for architecture planning with external modelssenior-code-reviewer- Use for code review (can delegate to external models)test-architect- Use for test planning/implementation
Bun Backend Plugin:
backend-developer- Use for API implementation with external modelsapi-architect- Use for API design with external models
Code Analysis Plugin:
codebase-detective- Use for investigation tasks with external models
No Plugin:
general-purpose- Default fallback for any task
Step 5: Example Agent Selection
Example 1: User says "use Grok to implement authentication"
Task: Code implementation (authentication)
Plugin: Bun Backend (if backend) or Frontend (if UI)
Decision:
1. Check for backend-developer or typescript-frontend-dev agent
2. Found backend-developer? → Use it with Grok proxy
3. Not found? → Offer to create custom auth agent
4. User declines? → Use general-purpose with file-based pattern
Example 2: User says "ask GPT-5.3 to review my API design"
Task: Code review (API design)
Plugin: Bun Backend
Decision:
1. Check for api-architect or senior-code-reviewer agent
2. Found? → Use it with GPT-5.3 proxy
3. Not found? → Use general-purpose with review instructions
4. Never run directly in main context
Example 3: User says "use Gemini to refactor this component"
Task: Refactoring (component)
Plugin: Frontend
Decision:
1. No specialized refactoring agent exists
2. Offer to create component-refactoring agent
3. User declines? → Use typescript-frontend-dev with proxy
4. Still no agent? → Use general-purpose with file-based pattern
Overview
Claudish is a CLI tool that allows running Claude Code with any AI model via prefix-based routing. Supports OpenRouter (100+ models), direct Google Gemini API, direct OpenAI API, and local models (Ollama, LM Studio, vLLM, MLX).
Key Principle: ALWAYS use Claudish through sub-agents with file-based instructions to avoid context window pollution.
What is Claudish?
Claudish (Claude-ish) is a proxy tool that:
- ✅ Runs Claude Code with any AI model via prefix-based routing
- ✅ Supports OpenRouter, Gemini, OpenAI, and local models
- ✅ Uses local API-compatible proxy server
- ✅ Supports 100% of Claude Code features
- ✅ Provides cost tracking and model selection
- ✅ Enables multi-model workflows
Model Routing
| Prefix | Backend | Example |
|---|---|---|
| (none) | OpenRouter | openai/gpt-5.3 |
g/ gemini/ | Google Gemini | g/gemini-2.0-flash |
oai/ openai/ | OpenAI | oai/gpt-4o |
ollama/ | Ollama | ollama/llama3.2 |
lmstudio/ | LM Studio | lmstudio/model |
http://... | Custom | http://localhost:8000/model |
Use Cases:
- Run tasks with different AI models (Grok for speed, GPT-5.3 for reasoning, Gemini for large context)
- Use direct APIs for lower latency (Gemini, OpenAI)
- Use local models for free, private inference (Ollama, LM Studio)
- Compare model performance on same task
- Reduce costs with cheaper models for simple tasks
Requirements
System Requirements
- Claudish CLI - Install with:
npm install -g claudishorbun install -g claudish - Claude Code - Must be installed
- At least one API key (see below)
Environment Variables
# API Keys (at least one required)
export OPENROUTER_API_KEY='sk-or-v1-...' # OpenRouter (100+ models)
export GEMINI_API_KEY='...' # Direct Gemini API (g/ prefix)
export OPENAI_API_KEY='sk-...' # Direct OpenAI API (oai/ prefix)
# Placeholder (required to prevent Claude Code dialog)
export ANTHROPIC_API_KEY='sk-ant-api03-placeholder'
# Custom endpoints (optional)
export GEMINI_BASE_URL='https://...' # Custom Gemini endpoint
export OPENAI_BASE_URL='https://...' # Custom OpenAI/Azure endpoint
export OLLAMA_BASE_URL='http://...' # Custom Ollama server
export LMSTUDIO_BASE_URL='http://...' # Custom LM Studio server
# Default model (optional)
export CLAUDISH_MODEL='openai/gpt-5.3' # Default model
Get API Keys:
- OpenRouter: https://openrouter.ai/keys (free tier available)
- Gemini: https://aistudio.google.com/apikey
- OpenAI: https://platform.openai.com/api-keys
- Local models: No API key needed
Quick Start Guide
Step 1: Install Claudish
# With npm (works everywhere)
npm install -g claudish
# With Bun (faster)
bun install -g claudish
# Verify installation
claudish --version
Step 2: Get Available Models
# List ALL OpenRouter models grouped by provider
claudish --models
# Fuzzy search models by name, ID, or description
claudish --models gemini
claudish --models "grok code"
# Show top recommended programming models (curated list)
claudish --top-models
# JSON output for parsing
claudish --models --json
claudish --top-models --json
# Force update from OpenRouter API
claudish --models --force-update
Step 3: Run Claudish
Interactive Mode (default):
# Shows model selector, persistent session
claudish
Single-shot Mode:
# One task and exit (requires --model)
claudish --model x-ai/grok-code-fast-1 "implement user authentication"
With stdin for large prompts:
# Read prompt from stdin (useful for git diffs, code review)
git diff | claudish --stdin --model openai/gpt-5-codex "Review these changes"
Recommended Models
Top Models for Development (v3.1.1):
| Model | Provider | Best For |
|---|---|---|
openai/gpt-5.3 | OpenAI | Default - Most advanced reasoning |
minimax/minimax-m2.1 | MiniMax | Budget-friendly, fast |
z-ai/glm-4.7 | Z.AI | Balanced performance |
google/gemini-3-pro-preview | 1M context window | |
moonshotai/kimi-k2-thinking | MoonShot | Extended thinking |
deepseek/deepseek-v3.2 | DeepSeek | Code specialist |
qwen/qwen3-vl-235b-a22b-thinking | Alibaba | Vision + reasoning |
Direct API Options (lower latency):
| Model | Backend | Best For |
|---|---|---|
g/gemini-2.0-flash | Gemini | Fast tasks, large context |
oai/gpt-4o | OpenAI | General purpose |
ollama/llama3.2 | Local | Free, private |
Get Latest Models:
# List all models (auto-updates every 2 days)
claudish --models
# Search for specific m
---
*Content truncated.*
When not to use it
- →When the user explicitly requests direct execution
- →When the task does not involve external AI models
Prerequisites
Limitations
- →Requires sub-agent delegation for production tasks
- →Requires valid API keys for external models
How it compares
It prevents context window bloat by offloading heavy AI model interactions to isolated sub-agent processes.
Compared to similar skills
claudish-usage side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| claudish-usage (this skill) | 4 | 6mo | Review | Advanced |
| skill-creator | 128 | 3mo | Review | Advanced |
| skill-development | 17 | 8mo | Review | Intermediate |
| agent-identifier | 15 | 8mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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