القائمة
Arthur onboarding sub-skill — Step 4: Analyze the target repository (language, framework, existing instrumentation). Writes detection results to .arthur-engine.env.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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.
| name | arthur-onboard-analyze |
| description | Arthur onboarding sub-skill — Step 4: Analyze the target repository (language, framework, existing instrumentation). Writes detection results to .arthur-engine.env. |
Goal: Detect language, framework, and existing instrumentation. Write results to .arthur-engine.env.
cat .arthur-engine.env 2>/dev/null || echo "(no state file)"
# Language detection
[ -f requirements.txt ] || [ -f pyproject.toml ] && echo "PYTHON=yes"
[ -f tsconfig.json ] || [ -f package.json ] && echo "NODE=yes"
# Framework detection
grep -r --include="*.py" --include="*.ts" --include="*.js" -l \
"mastra\|langchain\|openai\|anthropic\|crewai\|autogen" . 2>/dev/null | head -5
# Existing instrumentation
grep -r --include="*.py" --include="*.ts" --include="*.js" -l \
"arthur\.instrument\|arthur_observability\|ArthurExporter\|openinference" . 2>/dev/null | head -3
Also read requirements.txt, pyproject.toml, package.json, and the likely entry point (main.py, app.py, src/mastra/index.ts, src/index.ts, etc.).
Determine:
python | typescript | javascript | unknownmastra | langchain | openai | anthropic | crewai | other | unknown@mastra/arthur, or openinference already presentSTATE_FILE=".arthur-engine.env"
grep -v '^ARTHUR_DETECTED_LANGUAGE=\|^ARTHUR_DETECTED_FRAMEWORK=\|^ARTHUR_IS_INSTRUMENTED=' \
"$STATE_FILE" 2>/dev/null > /tmp/ae_env_tmp && mv /tmp/ae_env_tmp "$STATE_FILE" || true
echo "ARTHUR_DETECTED_LANGUAGE=<language>" >> "$STATE_FILE"
echo "ARTHUR_DETECTED_FRAMEWORK=<framework>" >> "$STATE_FILE"
echo "ARTHUR_IS_INSTRUMENTED=<true|false>" >> "$STATE_FILE"
Report the detected values to the user before exiting.