arthur-engine

Arthur onboarding sub-skill — Step 4: Analyze the target repository (language, framework, existing instrumentation). Writes detection results to .arthur-engine.env.

Arthur onboarding sub-skill — Step 8: Configure an LLM provider for continuous evals (OpenAI, Anthropic, Gemini, Bedrock, or Vertex AI). Reads/writes .arthur-engine.env.

Arthur onboarding sub-skill — Step 9: Recommend and configure continuous LLM evals for the Arthur task. Reads credentials and eval provider from .arthur-engine.env.

Arthur onboarding sub-skill — Step 5: Instrument the target repository with Arthur tracing (Python SDK, Mastra TS, or OpenInference). Reads detection results from .arthur-engine.env.

Arthur onboarding sub-skill — Step 2: Ensure Arthur GenAI Engine is available (local install or remote). Reads/writes .arthur-engine.env.

Onboard an agentic application to Arthur GenAI Engine. Guides through engine connection, task setup, code instrumentation, trace verification, and eval configuration. Invoke from any agentic application repository.

Arthur onboarding sub-skill — Platform Step 2: Authenticate to Arthur Platform using service account credentials (OAuth2 client credentials). Reads/writes .arthur-engine.env.

Arthur onboarding sub-skill — Platform Step 4: Ensure an Arthur Engine (data plane) is registered and active in the selected workspace. Reads/writes .arthur-engine.env.

Arthur onboarding sub-skill — Platform Step 5: Gate on application type, create an Agentic Model on Arthur Platform, and retrieve GenAI Engine task connection info. Reads/writes .arthur-engine.env.

Onboard an agentic application to the Arthur SaaS Platform (platform.arthur.ai). Guides through authentication, workspace selection, engine deployment, model creation, code instrumentation, trace verification, and eval configuration.

Arthur onboarding helper — Refresh Arthur Platform OAuth2 token using arthur_client. Reads CLIENT_ID/SECRET from .arthur-engine.env, writes ARTHUR_PLATFORM_TOKEN back to state.

Arthur onboarding sub-skill — Platform Step 3: Select or create a workspace in Arthur Platform. Reads/writes .arthur-engine.env.

Arthur onboarding sub-skill — Step 6: Extract prompts from the target repository and register them with Arthur Engine. Reads credentials from .arthur-engine.env.

Arthur onboarding sub-skill — Step 3: Set up an Arthur Task (create or select). Reads/writes .arthur-engine.env.

Arthur onboarding sub-skill — Step 7: Verify that traces are flowing from the instrumented application to Arthur Engine. Reads credentials from .arthur-engine.env.

Upgrade locally installed arthur-onboard-* and arthur-skills-upgrade skills to the latest version from GitHub main branch. Checks version fields, reports stale skills, and updates in place after confirmation.

Regenerate the arthur_genai_client package from the GenAI Engine OpenAPI spec. Use when the GenAI Engine API has changed, or when python/src/arthur_genai_client/ is missing after a fresh clone.

Run the arthur-observability-sdk integration tests. These build the SDK wheel into a fresh venv and verify OTLP telemetry delivery end-to-end. Use when you want to confirm the installable wheel works correctly.

Run the arthur-observability-sdk unit tests. Use when you want to verify SDK logic without building a wheel or spinning up external services.

Set up the GenAI Engine development environment. Use when starting work on the project for the first time, or when environment needs to be reset. Handles uv, PostgreSQL, migrations, and environment variables.

Start the GenAI Engine backend server and frontend UI. Use when you need to launch the API server and the frontend locally.

Start the GenAI Engine frontend UI dev server. Use when you need to launch the React app locally.