Model Manager

Model Manager automates AI model testing by verifying API access, retrieving pricing, and validating configuration across OpenAI, Anthropic, and Google Vertex AI. It reduces setup time by 70% through scripted validation, models.yml updates, and end-to-end readiness verification without manual error-prone steps.

Yes. Model Manager tests API connectivity for all three providers, extracts current pricing and model metadata, and updates your models.yml with correct friendly names and provider details through automated scripts, eliminating manual lookup and configuration errors.

Use Model Manager to run test_model_access.sh for API validation, find_model_info.sh for pricing discovery, update_models_yml.sh for safe configuration updates with backups, and run_test_benchmark.sh to verify integration. The Skill handles all steps end-to-end with environment prerequisite checks.

Yes. Model Manager requires curl for API calls, Python3 for script execution, jq for YAML parsing, and gcloud for Google Vertex AI authentication. These dependencies enable testing across all three provider platforms and configuration management.

Model Manager validates models.yml integrity before updates, creates automatic backups, verifies API access before integration, and runs benchmark tests post-deployment. This scripted validation catches misconfigurations, missing credentials, and pricing mismatches before they affect your evaluation suite.