{
  "context": "Tests whether the agent uses asyncpg connection pool with proper lifecycle, $1/$2 parameterized queries, bulk insert for event ingestion, async context managers for connections, server-side cursors for large result sets, and transactions for multi-step operations. The task describes business requirements without naming these patterns.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "asyncpg pool with create_pool",
      "description": "Database setup uses 'await asyncpg.create_pool()' with min_size and max_size parameters, not individual connections per request or psycopg",
      "max_score": 14
    },
    {
      "name": "Pool lifecycle management",
      "description": "Pool is created in a startup handler (FastAPI lifespan or on_event) and closed in a shutdown handler -- not created at module import time",
      "max_score": 10
    },
    {
      "name": "Async context managers for connections",
      "description": "All database operations use 'async with pool.acquire() as conn:' context manager -- no bare acquire() calls without guaranteed release",
      "max_score": 12
    },
    {
      "name": "Bulk insert for event ingestion",
      "description": "Event batch ingestion uses copy_records_to_table or executemany for efficient bulk insert -- NOT individual INSERT statements in a loop",
      "max_score": 14
    },
    {
      "name": "$1/$2 parameterized queries",
      "description": "All queries use $1, $2, $N numbered placeholders with positional args -- no f-strings, .format(), string concatenation, or %s placeholders",
      "max_score": 12
    },
    {
      "name": "Transaction for daily summary generation",
      "description": "Daily summary generation wraps the read + upsert operations in 'async with conn.transaction():' for atomicity",
      "max_score": 10
    },
    {
      "name": "Server-side cursor for user activity",
      "description": "The user activity report function uses a cursor or streaming pattern (conn.cursor with async iteration or batched fetching) for large result sets -- not fetchall() which loads everything into memory",
      "max_score": 10
    },
    {
      "name": "DATABASE_URL from environment",
      "description": "Database connection string is read from an environment variable (os.getenv or os.environ), not hardcoded",
      "max_score": 8
    },
    {
      "name": "command_timeout on pool",
      "description": "Pool is configured with command_timeout or equivalent timeout to prevent queries from hanging indefinitely",
      "max_score": 5
    },
    {
      "name": "No SQL injection vectors",
      "description": "No dynamic SQL built with f-strings or string concatenation anywhere in the codebase -- all user inputs go through parameterized queries",
      "max_score": 5
    }
  ]
}