arthur-ai/arthur-engine/arthur-onboard-oss-engine
Claude Code and agent skill by arthur-ai/arthur-engine
- community
Checking that the SKILL.md file is still in the repository.
Arthur onboarding sub-skill — Step 2: Ensure Arthur GenAI Engine is available (local install or remote). Reads/writes .arthur-engine.env.
Install
npx vskill@latest install arthur-ai/arthur-engine/arthur-onboard-oss-engineSKILL.md
Arthur Onboard — Step 2: Ensure Arthur GenAI Engine Is Available
Goal: Establish ARTHUR_ENGINE_URL and ARTHUR_API_KEY in .arthur-engine.env.
Read State
Parse ARTHUR_ENGINE_URL and ARTHUR_API_KEY from the output.
State write helper — use this pattern to update individual values without clobbering others:
If Both Values Exist — Verify Reachability
200→ confirm reuse with user, then exit this skill (engine step done)401→ engine reachable but key is wrong; ask user to re-enter API key, update state, then exit- anything else → engine unreachable; proceed to setup below
Set Up Engine (No Config or Unreachable)
Ask the user: "How would you like to connect to Arthur GenAI Engine?"
- A) Install locally on this machine (requires Docker)
- B) Connect to a remote Arthur Engine
Option A — Local Install
Detect OS:
Darwin = Mac, Linux = Linux, anything else = Windows.
Ask the user for OpenAI/Azure OpenAI config for guardrails:
"Do you have an OpenAI or Azure OpenAI API key to configure for Arthur Engine guardrails?This is used for hallucination and sensitive data checks. You can skip and add it manually to~/.arthur-engine/local-stack/genai-engine/.envlater."
If yes, collect:
- Provider —
OpenAIorAzure(default:OpenAI) - Model name (default:
gpt-4o-mini-2024-07-18) - Endpoint — required for Azure; leave blank for standard OpenAI
- API key — show the user this message and wait for their confirmation before proceeding (do not ask them to type the key in chat; do not run getpass via the Bash tool — it has no TTY):
> To keep your API key secure, please run this command directly in your terminal (the ! prefix runs it in your shell where input is masked): > > ! python3 -c "import getpass, os, stat; p=os.path.expanduser('~/.ae_tmp_key'); key=getpass.getpass('OpenAI API key (hidden): '); open(p,'w').write(key); os.chmod(p, 0o600); print('Key saved.')" > > Let me know once you've run it and I'll continue.
After the user confirms, use ~/.ae_tmp_key as <KEY_FILE_PATH> in the sub-agent prompt below.
If no, set SETUP_SKIP_OPENAI=true.
Note: This key goes into the Docker .env and configures the engine's built-in guardrails. It is separate from the eval model provider in Step 8, which is configured via the Arthur Engine API.
Before launching the sub-agent, tell the user:
"Starting the Arthur GenAI Engine installer now. Note: the first time the engine starts, it needs to download several AI models (this can take 10–15 minutes depending on your connection). I'll keep you updated as it boots."
Then run this to capture a timestamp before the installer starts (you'll use it later to display startup logs):
Remember this value as PRE_INSTALL_TIME.
Now delegate to a sub-agent using the Agent tool. IMPORTANT: set `run_in_background=false` (the default) — do NOT background this agent. Fill in the values collected above:
Mac/Linux sub-agent prompt:
Windows sub-agent prompt:
After sub-agent:
- Set
ARTHUR_API_KEYto extracted key (or ask user if not found) - Set
ARTHUR_ENGINE_URL=http://localhost:3030 - Save both to state file
Then poll for engine readiness by making individual Bash calls — one per check cycle, NOT a single long loop. Each completed call's output is immediately visible in the conversation. Make calls roughly 10 seconds apart until the engine is ready or 10 minutes have elapsed.
Use PRE_INSTALL_TIME (captured before the installer ran) as the initial --since value so the first check shows all startup logs. Each call prints NEXT_LOG_SINCE — use that as --since for the next call.
Each individual Bash call (Mac/Linux):
Replace <LAST_LOG_SINCE> with PRE_INSTALL_TIME on the first call, then with NEXT_LOG_SINCE from the previous call on each subsequent call.
Each individual Bash call (Windows):
Stop when ENGINE_STATUS=200 or ENGINE_STATUS=401. Max 60 calls (~10 min). If not ready after 60 calls: inform the user and ask if they want to keep waiting.
Option B — Remote
Ask user for URL and API key. Verify:
200 → save to state file. Other → report error and ask user to recheck.
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
- SKILL.md in the repositoryCheckingintegrations/claude-code-skills/arthur-onboard/arthur-onboard-oss-engine/SKILL.md
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