arthur-onboard-oss

name	arthur-onboard-oss
description	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.
allowed-tools	Bash, Read, Write, Edit, Task, Skill
version	1.0.0

Onboard to Arthur GenAI Engine

You are guiding the user through the complete Arthur GenAI Engine 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:

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

Parse existing values for ARTHUR_ENGINE_URL, ARTHUR_API_KEY, ARTHUR_TASK_ID.

If all three exist, display them and ask:

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

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

STATE_FILE=".arthur-engine.env"
grep -v '^ARTHUR_ENGINE_URL=' "$STATE_FILE" 2>/dev/null > /tmp/ae_env_tmp && mv /tmp/ae_env_tmp "$STATE_FILE" || true
echo 'ARTHUR_ENGINE_URL=http://localhost:3030' >> "$STATE_FILE"

Also ensure the file is gitignored:

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

---

Step 1/10 — Pre-flight Checks

Check git status in the target repo:

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).

---

Steps 2–9: Modular Sub-skills

Each remaining 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, so state flows automatically between steps.

Invoke in order:

1. Step 2 — arthur-onboard-oss-engine Ensures Arthur GenAI Engine is available (local Docker install or remote connection). Establishes ARTHUR_ENGINE_URL and ARTHUR_API_KEY in the state file.

2. Step 3 — arthur-onboard-task Creates or selects an Arthur Task. Establishes ARTHUR_TASK_ID in the state file.

3. Step 4 — 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.

4. Step 5 — arthur-onboard-instrument Instruments the application code (Python SDK, Mastra TS, or OpenInference). Reads detection results from the state file.

5. Step 6 — arthur-onboard-prompts Extracts prompt definitions from the repo and registers them with Arthur Engine.

6. Step 7 — arthur-onboard-verify Asks the user to run the app, then polls for traces to confirm instrumentation is working.

7. Step 8 — arthur-onboard-eval-provider Configures an LLM model provider for continuous evals. Writes ARTHUR_EVAL_PROVIDER and ARTHUR_EVAL_MODEL to state.

8. Step 9 — arthur-onboard-evals Recommends and creates continuous LLM evals for the task.

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

---

Step 10/10 — Done

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

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

Provide a completion summary:

Onboarding complete!

  Arthur Engine:     <ARTHUR_ENGINE_URL>
  Task:              <task_name> (<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.

Note any steps that were skipped or require manual follow-up (e.g., model provider configuration, prompt registration, trace verification).