arthur-ai/arthur-engine/arthur-onboard-platform

Claude Code and agent skill by arthur-ai/arthur-engine

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Checking that the SKILL.md file is still in the repository.

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.

Install

npx vskill@latest install arthur-ai/arthur-engine/arthur-onboard-platform

SKILL.md

Onboard to Arthur Platform

You are guiding the user through the complete Arthur Platform onboarding workflow. Work through each step in order. Be conversational — ask the user before making changes to their code or configuration.

Target repository: The current working directory, unless the user specifies a different path.


Step 0 — Check for skill updates

Invoke the arthur-skills-upgrade skill. It will check all installed arthur-onboard-* and arthur-skills-upgrade skills against GitHub main. If stale skills are found, the user is given three choices:

  • Yes — upgrade now
  • Not now — skip this time (will prompt again on the next run)
  • Skip version — don't prompt again for these specific versions; prompts resume when a newer version is released

If the skill is not installed, skip this step silently.

When upgrades are applied, report the version transition for each updated skill:

"Updated <skill-name>: <old-version> → <new-version>"

If multiple skills were updated, list each one. If everything was already up to date, a brief "All skills up to date" is sufficient.


State File

Persist all state to .arthur-engine.env in the root of the target repository. This file is per-project and should be gitignored.

Before starting: Read the state file:

bash
cat .arthur-engine.env 2>/dev/null || echo "(no state file)"

Parse existing values for ARTHUR_PLATFORM_URL, ARTHUR_ENGINE_URL, ARTHUR_API_KEY, ARTHUR_TASK_ID.

If ARTHUR_ENGINE_URL, ARTHUR_API_KEY, and ARTHUR_TASK_ID all exist, display them and ask:

"Found existing Arthur Platform configuration. Continue with these settings, or start fresh?"

Writing state: Use this pattern to update individual values without clobbering others:

bash
STATE_FILE=".arthur-engine.env"
grep -v '^ARTHUR_PLATFORM_URL=' "$STATE_FILE" 2>/dev/null > /tmp/ae_env_tmp && mv /tmp/ae_env_tmp "$STATE_FILE" || true
echo 'ARTHUR_PLATFORM_URL=https://platform.arthur.ai' >> "$STATE_FILE"

Also ensure the file is gitignored:

bash
grep -qxF '.arthur-engine.env' .gitignore 2>/dev/null || echo '.arthur-engine.env' >> .gitignore

Step 1/13 — Pre-flight Checks + Identify Platform

Check git status in the target repo:

bash
git status --porcelain
  • Unstaged/untracked changes → warn the user (do NOT block — staged changes are fine)
  • Not a git repo → note it but continue

Skip Claude Code auth check — the user is already authenticated (they are talking to you right now).

Identify Arthur Platform URL: Ask the user:

"Are you onboarding to the Arthur SaaS Platform at https://platform.arthur.ai?
Or do you have a self-hosted Arthur Platform at a different URL?"

Default to https://platform.arthur.ai if the user confirms. Save ARTHUR_PLATFORM_URL to state.

Verify the platform is reachable:

bash
HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" \
"${ARTHUR_PLATFORM_URL}/api/v1/auth/oidc/.well-known/openid-configuration" 2>/dev/null || echo "000")
echo "PLATFORM_REACHABLE=$HTTP_STATUS"
  • 200 → proceed
  • anything else → warn the user ("Platform not reachable at <ARTHUR_PLATFORM_URL>"); ask to check the URL or network before continuing

Steps 2–7: Platform Sub-skills

Each step is handled by a dedicated sub-skill. Invoke them in sequence using the Skill tool. Each sub-skill reads its inputs from .arthur-engine.env and writes its outputs back to the same file.

Invoke in order:

  1. Step 2 — arthur-onboard-platform-access

Guides service account creation, collects credentials, acquires an OAuth2 token. Establishes ARTHUR_PLATFORM_CLIENT_ID and ARTHUR_PLATFORM_TOKEN in state.

  1. Step 3 — arthur-onboard-platform-workspace

Lists or creates a workspace. Establishes ARTHUR_PLATFORM_WORKSPACE_ID and ARTHUR_PLATFORM_WORKSPACE_NAME in state.

  1. Step 4 — arthur-onboard-platform-engine

Lists registered engines (data planes) or deploys a new one (Docker Compose, CloudFormation, or Kubernetes). Establishes ARTHUR_PLATFORM_ENGINE_ID and ARTHUR_PLATFORM_ENGINE_URL in state.

  1. Step 5–7 — arthur-onboard-platform-model

Gates on application type (Agentic only continues; ML/GenAI models are routed to the platform UI). Creates a Project and Agentic Model on the platform, then retrieves task connection info. Establishes ARTHUR_PLATFORM_PROJECT_ID, ARTHUR_PLATFORM_MODEL_ID, ARTHUR_ENGINE_URL, ARTHUR_API_KEY, and ARTHUR_TASK_ID in state.


Steps 8–13: Reused Sub-skills

After the platform setup is complete, the remaining steps are identical to the OSS onboarding flow. Each sub-skill reads ARTHUR_ENGINE_URL, ARTHUR_API_KEY, and ARTHUR_TASK_ID from state — exactly as set by arthur-onboard-platform-model.

Invoke in order:

  1. Step 8 — arthur-onboard-analyze

Analyzes the target repository for language, framework, and existing instrumentation. Writes ARTHUR_DETECTED_LANGUAGE, ARTHUR_DETECTED_FRAMEWORK, ARTHUR_IS_INSTRUMENTED to state.

  1. Step 9 — arthur-onboard-instrument

Instruments the application code (Python arthur-sdk, Mastra TypeScript, or OpenInference/OTel).

  1. Step 10 — arthur-onboard-prompts

Extracts prompt definitions from the repo and registers them with Arthur Engine.

  1. Step 11 — arthur-onboard-verify

Asks the user to run the app, then polls for traces to confirm instrumentation is working.

  1. Step 12 — arthur-onboard-eval-provider

Configures an LLM model provider for continuous evals. Writes ARTHUR_EVAL_PROVIDER and ARTHUR_EVAL_MODEL to state.

  1. Step 13 — arthur-onboard-evals

Recommends and creates continuous LLM evals for the task.

Sub-skill not found? If a sub-skill is not installed, its step instructions appear in the
system's available-skills list. If missing entirely, ask the user to install all arthur-onboard-*
and arthur-onboard-platform-* skills alongside this one (see README.md for install commands).

Step 13/13 — Done

After all sub-skills complete, read the final state:

bash
cat .arthur-engine.env 2>/dev/null

Provide a completion summary:

Onboarding complete!
Arthur Platform: <ARTHUR_PLATFORM_URL>
Workspace: <ARTHUR_PLATFORM_WORKSPACE_NAME> (<ARTHUR_PLATFORM_WORKSPACE_ID>)
Engine: <ARTHUR_PLATFORM_ENGINE_ID>
Engine URL: <ARTHUR_ENGINE_URL>
Model: <ARTHUR_PLATFORM_MODEL_ID>
Task: <ARTHUR_TASK_ID>
Continuous evals: <N> monitoring your application
Next: Run your application with the Arthur env vars set to start seeing traces and
eval scores in the Arthur Platform UI at <ARTHUR_PLATFORM_URL>.

Note any steps that were skipped or require manual follow-up (e.g., model provider configuration not set, prompts not registered, trace verification pending).

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

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