Medical GraphRAG Assistant

# Specification Quality Checklist: FHIR GraphRAG Knowledge Graph **Purpose**: Validate specification completeness and quality before proceeding to planning **Created**: 2025-11-05 **Feature**: [spec.md](../spec.md) ## Content Quality - [x] No implementation details (languages, frameworks, APIs) - [x] Focused on user value and business needs - [x] Written for non-technical stakeholders - [x] All mandatory sections completed ## Requirement Completeness - [x] No [NEEDS CLARIFICATION] markers remain - [x] Requirements are testable and unambiguous - [x] Success criteria are measurable - [x] Success criteria are technology-agnostic (no implementation details) - [x] All acceptance scenarios are defined - [x] Edge cases are identified - [x] Scope is clearly bounded - [x] Dependencies and assumptions identified ## Feature Readiness - [x] All functional requirements have clear acceptance criteria - [x] User scenarios cover primary flows - [x] Feature meets measurable outcomes defined in Success Criteria - [x] No implementation details leak into specification ## Validation Notes ### Content Quality Assessment ✅ **PASS** - Specification avoids implementation details. The spec mentions rag-templates library, IRIS database, and Python libraries in Dependencies and Constraints sections (appropriate), but user stories and requirements focus on WHAT (extract entities, perform multi-modal search) not HOW. ✅ **PASS** - Focused on user value: Medical researchers extracting knowledge, clinicians getting better search results, system administrators ensuring performance. ✅ **PASS** - Written for non-technical stakeholders: User stories describe roles (medical researcher, clinician, system administrator) and value propositions in domain language. ✅ **PASS** - All mandatory sections completed: User Scenarios & Testing, Requirements, Success Criteria all present with substantial content. ### Requirement Completeness Assessment ✅ **PASS** - No [NEEDS CLARIFICATION] markers in the spec. All requirements are fully specified with informed defaults documented in Assumptions section. ✅ **PASS** - Requirements are testable and unambiguous: - FR-001: Testable by querying FHIR native tables and verifying no data duplication - FR-003: Testable by running entity extraction and verifying entity types match expected categories - FR-009: Testable by executing multi-modal search and verifying RRF fusion algorithm is used - All 20 functional requirements have clear, verifiable criteria ✅ **PASS** - Success criteria are measurable: - SC-001: "100+ medical entities" - specific numeric target - SC-002: "80%+ precision" - percentage metric - SC-005: "under 5 minutes" - time-based metric - All 10 success criteria have quantifiable thresholds ✅ **PASS** - Success criteria are technology-agnostic: - SC-004: "Query response time improves by 20%+ in relevance" (user outcome, not system metric) - SC-006: "Zero modifications to FHIR native table schema" (outcome-focused) - SC-007: "Existing script continues to function" (backward compatibility outcome) - No mention of database query plans, API response codes, or framework-specific metrics ✅ **PASS** - All acceptance scenarios defined: Each user story (P1, P2, P3) has 4 Given-When-Then scenarios covering main flow, variations, and edge cases. ✅ **PASS** - Edge cases identified: 10 edge cases listed covering empty notes, ambiguous entities, malformed data, missing libraries, concurrency, etc. ✅ **PASS** - Scope clearly bounded: Out of Scope section explicitly excludes real-time extraction, external ontologies, UI, multi-language, auth, deployment, etc. ✅ **PASS** - Dependencies and assumptions identified: - Dependencies: 6 items (rag-templates, IRIS, Python libraries, existing implementation, FHIR data, LLM service) - Assumptions: 10 items covering library availability, credentials, data quality, language, thresholds, etc. ### Feature Readiness Assessment ✅ **PASS** - Functional requirements have clear acceptance criteria through User Scenarios. Each FR can be mapped to at least one acceptance scenario: - FR-003 (extract entities) → User Story 1, Scenario 1 - FR-008 (multi-modal search) → User Story 2, Scenario 1 - FR-018 (zero FHIR modifications) → User Story 1, Scenario 4 ✅ **PASS** - User scenarios cover primary flows: - P1: Foundation (entity extraction) - P2: Primary value (multi-modal search) - P3: Production readiness (performance) All critical paths covered with independent test criteria. ✅ **PASS** - Feature meets measurable outcomes: 10 success criteria (SC-001 through SC-010) cover entity extraction, accuracy, multi-modal fusion, performance, backward compatibility. ✅ **PASS** - No implementation details in specification: Technology mentions (rag-templates, IRIS, Python) confined to Dependencies/Assumptions/Constraints sections as required context, not in user stories or functional requirements. ## Overall Assessment **STATUS**: ✅ **READY FOR PLANNING** All 13 checklist items pass validation. The specification is: - Complete with all mandatory sections - Free of clarification markers - Testable with unambiguous requirements - Focused on user value and business outcomes - Technology-agnostic in success criteria - Well-scoped with clear boundaries **RECOMMENDATION**: Proceed to `/speckit.plan` to create implementation plan. ## Issues Found None - specification passes all quality checks.