adding-models

Add new LLM models to Letta Code by updating models.json and CI test matrices.

3.0k|350|Updated Oct 25, 2025
One-click install
npx skills add https://github.com/letta-ai/letta-code --skill adding-models
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: adding-models
Source: https://github.com/letta-ai/letta-code/tree/main/.skills/adding-models
Command: npx skills add https://github.com/letta-ai/letta-code --skill adding-models

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill guides you through adding support for new LLM models to Letta Code, including updating src/models.json, CI test matrices, and model validation. It reduces configuration errors and speeds up onboarding of new providers.

Core Features & Use Cases

  • Model discovery: Identify valid model handles from common provider prefixes (e.g., openai/, anthropic/, google_ai/).
  • Configuration updates: Add entries to src/models.json with fields like id, handle, label, description, and provider-specific updateArgs.
  • CI & validation: Extend CI test matrices and validate model handles to prevent misconfigurations.
  • Use Case: When you want to add support for a new model (e.g., a new Claude, GPT, or Gemini variant), this skill walks you through the exact steps.

Quick Start

Use the skill to add a new model by updating the models configuration and ensuring CI validation. Example commands:

  • Update src/models.json with a new model entry
  • Run validation to verify the handle and configuration
  • Run CI tests to confirm compatibility

Frequently Asked Questions about adding-models

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I add a new LLM model to Letta Code?

Adding a new LLM model involves updating src/models.json with required fields (id, handle, label, description, isFeatured, updateArgs), ensuring the model handle uses the correct provider prefix (e.g., openai/, anthropic/), and running validation to confirm the configuration is correct before deploying.

What metadata fields are required when registering a new model in models.json?

Required fields are id, handle, label, description, isFeatured, and updateArgs. The handle must follow provider prefix conventions to ensure proper routing and integration with Letta's model discovery system.

How do I validate a new model configuration before deployment?

Run validation checks to verify the model handle matches the correct provider prefix and that all required metadata fields are populated. Then execute CI tests to confirm the new model integrates correctly with existing toolset mappings and doesn't break compatibility.

Can I add multiple model variants from the same provider at once?

Yes. The Skill handles batch model onboarding by allowing you to add multiple entries to models.json with consistent provider prefixes and settings. Validation and CI test matrices scale to cover all new models simultaneously.

What happens if I use an incorrect provider prefix when adding a model?

Validation will catch the misconfigured handle and prevent it from being registered. Provider prefixes are strictly enforced to maintain consistency across model discovery and toolset routing, reducing integration errors downstream.

Do I need to update CI test matrices when adding a new model?

Yes. Adding a new model requires extending the CI test matrix to include the new model handle. This ensures comprehensive testing and prevents regressions when the model is integrated into Letta Code's runtime environment.