---

name: adding-models description: Guide for adding new LLM models to Letta Code. Use when the user wants to add support for a new model, needs to know valid model handles, or wants to update the model configuration. Covers models.json configuration, CI test matrix, and handle validation.

Adding Models

This skill guides you through adding a new LLM model to Letta Code.

Quick Reference

Key files:

• src/models.json - Model definitions (required)
• .github/workflows/ci.yml - CI test matrix (optional)
• src/tools/manager.ts - Toolset detection logic (rarely needed)

Workflow

Step 1: Find Valid Model Handles

Query the Letta API to see available models:

Copycurl -s https://api.letta.com/v1/models/ | jq '.[] | .handle'

Or filter by provider:

Copycurl -s https://api.letta.com/v1/models/ | jq '.[] | select(.handle | startswith("google_ai/")) | .handle'

Common provider prefixes:

• anthropic/ - Claude models
• openai/ - GPT models
• google_ai/ - Gemini models
• google_vertex/ - Vertex AI
• openrouter/ - Various providers

Step 2: Add to models.json

Add an entry to src/models.json:

Copy{
  "id": "model-shortname",
  "handle": "provider/model-name",
  "label": "Human Readable Name",
  "description": "Brief description of the model",
  "isFeatured": true,  // Optional: shows in featured list
  "updateArgs": {
    "context_window": 180000,
    "temperature": 1.0  // Optional: provider-specific settings
  }
}

Field reference:

• id: Short identifier used with --model flag (e.g., gemini-3-flash)
• handle: Full provider/model path from the API (e.g., google_ai/gemini-3-flash-preview)
• label: Display name in model selector
• description: Brief description shown in selector
• isFeatured: If true, appears in featured models section
• updateArgs: Model-specific configuration (context window, temperature, reasoning settings, etc.)

Provider prefixes:

• anthropic/ - Anthropic (Claude models)
• openai/ - OpenAI (GPT models)
• google_ai/ - Google AI (Gemini models)
• google_vertex/ - Google Vertex AI
• openrouter/ - OpenRouter (various providers)

Step 3: Test the Model

Test with headless mode:

Copybun run src/index.ts --new --model <model-id> -p "hi, what model are you?"

Example:

Copybun run src/index.ts --new --model gemini-3-flash -p "hi, what model are you?"

Step 4: Add to CI Test Matrix (Optional)

To include the model in automated testing, add it to .github/workflows/ci.yml:

Copy# Find the headless job matrix around line 122
model: [gpt-5-minimal, gpt-4.1, sonnet-4.5, gemini-pro, your-new-model, glm-4.6, haiku]

Toolset Detection

Models are automatically assigned toolsets based on provider:

• openai/* → codex toolset
• google_ai/* or google_vertex/* → gemini toolset
• Others → default toolset

This is handled by isGeminiModel() and isOpenAIModel() in src/tools/manager.ts. You typically don't need to modify this unless adding a new provider.

Common Issues

"Handle not found" error: The model handle is incorrect. Run the validation script to see valid handles.

Model works but wrong toolset: Check src/tools/manager.ts to ensure the provider prefix is recognized.