{
  "context": "This criteria evaluates how well the engineer uses the PostHog Python SDK to track AI interactions with Claude via AWS Bedrock, focusing on the SDK's AI observability capabilities for automatic analytics tracking.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Bedrock client wrapper",
      "description": "Uses the posthog.ai.anthropic module to wrap the Anthropic client for Bedrock integration (e.g., from posthog.ai.anthropic import Anthropic or AsyncAnthropic with appropriate AWS Bedrock configuration)",
      "max_score": 30
    },
    {
      "name": "PostHog client initialization",
      "description": "Properly initializes a PostHog client and passes it to the Anthropic wrapper using the posthog_client parameter",
      "max_score": 20
    },
    {
      "name": "User identification",
      "description": "Associates AI interactions with a user by passing the distinct_id (user_id) to the API call or setting it via posthog_distinct_id parameter",
      "max_score": 20
    },
    {
      "name": "Automatic metrics tracking",
      "description": "Relies on automatic tracking of AI metrics (tokens, latency, model) without manually calling posthog.capture() for AI events",
      "max_score": 20
    },
    {
      "name": "Client cleanup",
      "description": "Properly manages PostHog client lifecycle by calling posthog.flush() or posthog.shutdown() to ensure events are sent before program termination",
      "max_score": 10
    }
  ]
}