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Specification Quality Checklist: DeepEval Metrics Integration

Purpose: Validate specification completeness and quality before proceeding to planning Created: 2025-01-30 Feature: spec.md

Content Quality

  • No implementation details (languages, frameworks, APIs)
  • Focused on user value and business needs
  • Written for non-technical stakeholders
  • All mandatory sections completed

Requirement Completeness

  • No [NEEDS CLARIFICATION] markers remain
  • Requirements are testable and unambiguous
  • Success criteria are measurable
  • Success criteria are technology-agnostic (no implementation details)
  • All acceptance scenarios are defined
  • Edge cases are identified
  • Scope is clearly bounded
  • Dependencies and assumptions identified

Feature Readiness

  • All functional requirements have clear acceptance criteria
  • User scenarios cover primary flows
  • Feature meets measurable outcomes defined in Success Criteria
  • No implementation details leak into specification

Notes

  • All items pass validation
  • Specification is ready for clarification or implementation planning
  • Key scope boundaries:
  • DeepEval integration for multi-provider support (OpenAI, Azure, Anthropic, Ollama)
  • G-Eval for custom criteria evaluation
  • RAG metrics (Faithfulness, ContextualRelevancy, ContextualPrecision, ContextualRecall)
  • Azure AI evaluator provider validation enhancement
  • Assumptions documented regarding DeepEval version and provider API availability