vibe-check-mcp/data/cognee_case_study.json

Vibe Check MCP - Anti-pattern detection and mentoring for better engineering decisions

{
  "case_study": {
    "id": "cognee_integration_failure",
    "title": "Cognee Integration: Learning from Unnecessary Complexity",
    "pattern_type": "infrastructure_without_implementation", 
    "timeline": "Several days",
    "outcome": "Eventually found simpler approach",
    "impact": {
      "technical_debt": "Some unnecessary complexity added",
      "opportunity_cost": "Days of development time",
      "functionality": "Delayed working vector search integration"
    },
    "root_cause": "Built custom HTTP servers instead of using cognee.add() → cognee.cognify() → cognee.search()",
    "lesson": "Always test standard API approach before building custom infrastructure",
    "prevention_checklist": [
      "Research official SDK documentation first",
      "Test basic integration with 10 lines of code",
      "Document why standard approach is insufficient (if at all)",
      "Get second opinion on custom vs standard approach"
    ]
  },
  "example_detection_text": "We need to integrate with Cognee for vector search. I'm planning to build a custom HTTP client with proper error handling and retry logic since their SDK might be limiting. We'll implement our own vector processing pipeline to ensure we have full control.",
  "expected_detection": {
    "should_detect": true,
    "minimum_confidence": 0.7,
    "expected_evidence": [
      "mentions building custom infrastructure",
      "assumes SDK limitations without testing",
      "planning custom implementation"
    ]
  }
}