OpenClaude Multi-LLM Skill

Skill by ara.so — Daily 2026 Skills collection.

OpenClaude is a fork of Claude Code that routes all LLM calls through an OpenAI-compatible shim (

openaiShim.ts

), letting you use any model that speaks the OpenAI Chat Completions API — GPT-4o, DeepSeek, Gemini via OpenRouter, Ollama, Groq, Mistral, Azure, and more — while keeping every Claude Code tool intact (Bash, FileRead, FileWrite, FileEdit, Glob, Grep, WebFetch, Agent, MCP, Tasks, LSP, NotebookEdit).

Installation

npm (recommended)

bash

npm install -g @gitlawb/openclaude
# CLI command installed: openclaude

From source (requires Bun)

bash

git clone https://node.gitlawb.com/z6MkqDnb7Siv3Cwj7pGJq4T5EsUisECqR8KpnDLwcaZq5TPr/openclaude.git
cd openclaude
bun install
bun run build
# optionally link globally
npm link

Run without build

bash

bun run dev       # run directly with Bun, no build step

Activation — Required Environment Variables

You must set

CLAUDE_CODE_USE_OPENAI=1

to enable the shim. Without it, the tool falls back to the Anthropic SDK.

Variable	Required	Purpose
`CLAUDE_CODE_USE_OPENAI`	Yes	Set to `1` to activate OpenAI provider
`OPENAI_API_KEY`	Yes*	API key (*omit for local Ollama/LM Studio)
`OPENAI_MODEL`	Yes	Model identifier
`OPENAI_BASE_URL`	No	Custom endpoint (default: `https://api.openai.com/v1` )
`CODEX_API_KEY`	Codex only	ChatGPT/Codex access token
`CODEX_AUTH_JSON_PATH`	Codex only	Path to Codex CLI `auth.json`

OPENAI_MODEL

takes priority over

ANTHROPIC_MODEL

if both are set.

Provider Configuration Examples

OpenAI

bash

export CLAUDE_CODE_USE_OPENAI=1
export OPENAI_API_KEY=$OPENAI_API_KEY
export OPENAI_MODEL=gpt-4o
openclaude

DeepSeek

bash

export CLAUDE_CODE_USE_OPENAI=1
export OPENAI_API_KEY=$DEEPSEEK_API_KEY
export OPENAI_BASE_URL=https://api.deepseek.com/v1
export OPENAI_MODEL=deepseek-chat
openclaude

Google Gemini (via OpenRouter)

bash

export CLAUDE_CODE_USE_OPENAI=1
export OPENAI_API_KEY=$OPENROUTER_API_KEY
export OPENAI_BASE_URL=https://openrouter.ai/api/v1
export OPENAI_MODEL=google/gemini-2.0-flash
openclaude

Ollama (local, no API key needed)

bash

ollama pull llama3.3:70b

export CLAUDE_CODE_USE_OPENAI=1
export OPENAI_BASE_URL=http://localhost:11434/v1
export OPENAI_MODEL=llama3.3:70b
openclaude

Groq

bash

export CLAUDE_CODE_USE_OPENAI=1
export OPENAI_API_KEY=$GROQ_API_KEY
export OPENAI_BASE_URL=https://api.groq.com/openai/v1
export OPENAI_MODEL=llama-3.3-70b-versatile
openclaude

Mistral

bash

export CLAUDE_CODE_USE_OPENAI=1
export OPENAI_API_KEY=$MISTRAL_API_KEY
export OPENAI_BASE_URL=https://api.mistral.ai/v1
export OPENAI_MODEL=mistral-large-latest
openclaude

Azure OpenAI

bash

export CLAUDE_CODE_USE_OPENAI=1
export OPENAI_API_KEY=$AZURE_OPENAI_KEY
export OPENAI_BASE_URL=https://your-resource.openai.azure.com/openai/deployments/your-deployment/v1
export OPENAI_MODEL=gpt-4o
openclaude

Codex (ChatGPT backend)

bash

export CLAUDE_CODE_USE_OPENAI=1
export OPENAI_MODEL=codexplan   # or codexspark for faster loops
# reads ~/.codex/auth.json automatically if present
# or set: export CODEX_API_KEY=$CODEX_TOKEN
openclaude

LM Studio (local)

bash

export CLAUDE_CODE_USE_OPENAI=1
export OPENAI_BASE_URL=http://localhost:1234/v1
export OPENAI_MODEL=your-model-name
openclaude

Together AI

bash

export CLAUDE_CODE_USE_OPENAI=1
export OPENAI_API_KEY=$TOGETHER_API_KEY
export OPENAI_BASE_URL=https://api.together.xyz/v1
export OPENAI_MODEL=meta-llama/Llama-3.3-70B-Instruct-Turbo
openclaude

Architecture — How the Shim Works

The shim file is

src/services/api/openaiShim.ts

(724 lines). It duck-types the Anthropic SDK interface so the rest of Claude Code is unaware it's talking to a different provider.

Claude Code Tool System
        │
        ▼
Anthropic SDK interface (duck-typed)
        │
        ▼
openaiShim.ts  ← format translation layer
        │
        ▼
OpenAI Chat Completions API
        │
        ▼
Any compatible model

What the shim translates

Anthropic message content blocks → OpenAI
```
messages
```
array
Anthropic
```
tool_use
```
/
```
tool_result
```
blocks → OpenAI
```
function_calls
```
/
```
tool
```
messages
OpenAI SSE streaming chunks → Anthropic stream events
Anthropic system prompt arrays → OpenAI
```
system
```
role messages

Files changed from upstream

src/services/api/openaiShim.ts   ← NEW: the shim (724 lines)
src/services/api/client.ts       ← routes to shim when CLAUDE_CODE_USE_OPENAI=1
src/utils/model/providers.ts     ← added 'openai' provider type
src/utils/model/configs.ts       ← added openai model mappings
src/utils/model/model.ts         ← respects OPENAI_MODEL for defaults
src/utils/auth.ts                ← recognizes OpenAI as valid 3rd-party provider

Developer Workflow — Key Commands

bash

# Run in dev mode (no build)
bun run dev

# Build distribution
bun run build

# Launch with persisted profile (.openclaude-profile.json)
bun run dev:profile

# Launch with OpenAI profile (requires OPENAI_API_KEY in shell)
bun run dev:openai

# Launch with Ollama profile (localhost:11434, llama3.1:8b default)
bun run dev:ollama

# Launch with Codex profile
bun run dev:codex

# Quick startup sanity check
bun run smoke

# Validate provider env + reachability
bun run doctor:runtime

# Machine-readable runtime diagnostics
bun run doctor:runtime:json

# Persist diagnostics report to reports/doctor-runtime.json
bun run doctor:report

# Full local hardening check (typecheck + smoke + runtime doctor)
bun run hardening:check

# Strict hardening (includes project-wide typecheck)
bun run hardening:strict

Profile Bootstrap — One-Time Setup

Profiles save provider config to

.openclaude-profile.json

so you don't repeat env exports.

bash

# Auto-detect provider (ollama if running, otherwise openai)
bun run profile:init

# Bootstrap for OpenAI
bun run profile:init -- --provider openai --api-key $OPENAI_API_KEY

# Bootstrap for Ollama with custom model
bun run profile:init -- --provider ollama --model llama3.1:8b

# Bootstrap for Codex
bun run profile:init -- --provider codex --model codexspark
bun run profile:codex

After bootstrapping, run the app via the persisted profile:

bash

bun run dev:profile

TypeScript Integration — Using the Shim Directly

If you want to use the shim in your own TypeScript code:

typescript

// src/services/api/client.ts pattern — routing to the shim
import { openaiShim } from './openaiShim.js';

const useOpenAI = process.env.CLAUDE_CODE_USE_OPENAI === '1';

const client = useOpenAI
  ? openaiShim({
      apiKey: process.env.OPENAI_API_KEY,
      baseURL: process.env.OPENAI_BASE_URL ?? 'https://api.openai.com/v1',
      model: process.env.OPENAI_MODEL ?? 'gpt-4o',
    })
  : new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });

typescript

// Streaming usage pattern (mirrors Anthropic SDK interface)
const stream = await client.messages.stream({
  model: process.env.OPENAI_MODEL!,
  max_tokens: 32000,
  system: 'You are a helpful coding assistant.',
  messages: [
    { role: 'user', content: 'Refactor this function for readability.' }
  ],
  tools: myTools, // Anthropic-format tool definitions — shim translates them
});

for await (const event of stream) {
  // events arrive in Anthropic format regardless of underlying provider
  if (event.type === 'content_block_delta') {
    process.stdout.write(event.delta.text ?? '');
  }
}

Model Quality Reference

Model	Tool Calling	Code Quality	Speed
GPT-4o	Excellent	Excellent	Fast
DeepSeek-V3	Great	Great	Fast
Gemini 2.0 Flash	Great	Good	Very Fast
Llama 3.3 70B	Good	Good	Medium
Mistral Large	Good	Good	Fast
GPT-4o-mini	Good	Good	Very Fast
Qwen 2.5 72B	Good	Good	Medium
Models < 7B	Limited	Limited	Very Fast

For agentic multi-step tool use, prefer models with strong native function/tool calling (GPT-4o, DeepSeek-V3, Gemini 2.0 Flash).

What Works vs. What Doesn't

Fully supported

All tools: Bash, FileRead, FileWrite, FileEdit, Glob, Grep, WebFetch, WebSearch, Agent, MCP, LSP, NotebookEdit, Tasks
Streaming (real-time token output)
Multi-step tool chains
Vision/images (base64 and URL) for models that support them
Slash commands:
```
/commit
```
,
```
/review
```
,
```
/compact
```
,
```
/diff
```
,
```
/doctor
```
Sub-agents (AgentTool spawns sub-agents using the same provider)
Persistent memory

Not supported (Anthropic-specific features)

Extended thinking / reasoning mode
Prompt caching (Anthropic cache headers skipped)
Anthropic beta feature headers
Token output defaults to 32K max (gracefully capped if model is lower)

Troubleshooting

doctor:runtime

fails with placeholder key error

Error: OPENAI_API_KEY looks like a placeholder (SUA_CHAVE)

Set a real key:

export OPENAI_API_KEY=$YOUR_ACTUAL_KEY

Ollama connection refused

Ensure Ollama is running before launching:

bash

ollama serve &
ollama pull llama3.3:70b
bun run dev:ollama

Tool calls not working / model ignores tools

Switch to a model with strong tool calling support (GPT-4o, DeepSeek-V3). Models under 7B parameters often fail at multi-step agentic tool use.

Azure endpoint format

The

OPENAI_BASE_URL

for Azure must include the deployment path:

https://<resource>.openai.azure.com/openai/deployments/<deployment>/v1

Codex auth not found

~/.codex/auth.json

doesn't exist, set the token directly:

bash

export CODEX_API_KEY=$YOUR_CODEX_TOKEN

Or point to a custom auth file:

bash

export CODEX_AUTH_JSON_PATH=/path/to/auth.json

Run diagnostics for any issue

bash

bun run doctor:runtime       # human-readable
bun run doctor:runtime:json  # machine-readable JSON
bun run doctor:report        # saves to reports/doctor-runtime.json

openclaude-multi-llm

NPX Install

Tags

SKILL.md Content

OpenClaude Multi-LLM Skill

Installation

npm (recommended)

From source (requires Bun)

Run without build

Activation — Required Environment Variables

Provider Configuration Examples

OpenAI

DeepSeek

Google Gemini (via OpenRouter)

Ollama (local, no API key needed)

Groq

Mistral

Azure OpenAI

Codex (ChatGPT backend)

LM Studio (local)

Together AI

Architecture — How the Shim Works

What the shim translates

Files changed from upstream

Developer Workflow — Key Commands

Profile Bootstrap — One-Time Setup

TypeScript Integration — Using the Shim Directly

Model Quality Reference

What Works vs. What Doesn't

Fully supported

Not supported (Anthropic-specific features)

Troubleshooting

`doctor:runtime`
fails with placeholder key error

Ollama connection refused

Tool calls not working / model ignores tools

Azure endpoint format

Codex auth not found

Run diagnostics for any issue