adding-models
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.
Install
mkdir -p .claude/skills/adding-models && curl -L -o skill.zip "https://mcp.directory/api/skills/download/4248" && unzip -o skill.zip -d .claude/skills/adding-models && rm skill.zipInstalls to .claude/skills/adding-models
About this skill
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:
curl -s https://api.letta.com/v1/models/ | jq '.[] | .handle'
Or filter by provider:
curl -s https://api.letta.com/v1/models/ | jq '.[] | select(.handle | startswith("google_ai/")) | .handle'
Common provider prefixes:
anthropic/- Claude modelsopenai/- GPT modelsgoogle_ai/- Gemini modelsgoogle_vertex/- Vertex AIopenrouter/- Various providers
Step 2: Add to models.json
Add an entry to src/models.json:
{
"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--modelflag (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 selectordescription: Brief description shown in selectorisFeatured: If true, appears in featured models sectionupdateArgs: 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 AIopenrouter/- OpenRouter (various providers)
Step 3: Test the Model
Test with headless mode:
bun run src/index.ts --new --model <model-id> -p "hi, what model are you?"
Example:
bun 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:
# 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/*→codextoolsetgoogle_ai/*orgoogle_vertex/*→geminitoolset- Others →
defaulttoolset
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.
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