model-researcher

To add a new AI model to opencode.json, research the model's ID, context limits, and API requirements from official documentation, then generate the correct JSON snippet for integration. This verifies specifications before configuration.

Yes, you can configure self-hosted or custom endpoint models in opencode.json. The Skill verifies API requirements and specifications from authoritative sources to integrate bleeding-edge, non-standard, or custom deployments accurately.

The best way to verify API requirements for a newly announced LLM is checking official documentation for model IDs and context limits. This ensures accurate integration into your configuration without manual guessing.

You find the correct model ID and context limits for a custom AI model by researching official documentation. This confirms critical details required to generate an accurate configuration snippet for your setup.

Yes, this approach works for integrating non-standard models from small research labs by discovering the model, verifying its API endpoint and token limits, and generating the correct configuration for opencode.json.