# Architecture Document Validation Checklist **Purpose**: Validate the architecture document itself is complete, implementable, and provides clear guidance for AI agents. **Note**: This checklist validates the ARCHITECTURE DOCUMENT only. For cross-workflow validation (PRD → Architecture → Stories alignment), use the solutioning-gate-check workflow. --- ## 1. Decision Completeness ### All Decisions Made - [ ] Every critical decision category has been resolved - [ ] All important decision categories addressed - [ ] No placeholder text like "TBD", "[choose]", or "{TODO}" remains - [ ] Optional decisions either resolved or explicitly deferred with rationale ### Decision Coverage - [ ] Data persistence approach decided - [ ] API pattern chosen - [ ] Authentication/authorization strategy defined - [ ] Deployment target selected - [ ] All functional requirements have architectural support --- ## 2. Version Specificity ### Technology Versions - [ ] Every technology choice includes a specific version number - [ ] Version numbers are current (verified via WebSearch, not hardcoded) - [ ] Compatible versions selected (e.g., Node.js version supports chosen packages) - [ ] Verification dates noted for version checks ### Version Verification Process - [ ] WebSearch used during workflow to verify current versions - [ ] No hardcoded versions from decision catalog trusted without verification - [ ] LTS vs. latest versions considered and documented - [ ] Breaking changes between versions noted if relevant --- ## 3. Starter Template Integration (if applicable) ### Template Selection - [ ] Starter template chosen (or "from scratch" decision documented) - [ ] Project initialization command documented with exact flags - [ ] Starter template version is current and specified - [ ] Command search term provided for verification ### Starter-Provided Decisions - [ ] Decisions provided by starter marked as "PROVIDED BY STARTER" - [ ] List of what starter provides is complete - [ ] Remaining decisions (not covered by starter) clearly identified - [ ] No duplicate decisions that starter already makes --- ## 4. Novel Pattern Design (if applicable) ### Pattern Detection - [ ] All unique/novel concepts from PRD identified - [ ] Patterns that don't have standard solutions documented - [ ] Multi-epic workflows requiring custom design captured ### Pattern Documentation Quality - [ ] Pattern name and purpose clearly defined - [ ] Component interactions specified - [ ] Data flow documented (with sequence diagrams if complex) - [ ] Implementation guide provided for agents - [ ] Edge cases and failure modes considered - [ ] States and transitions clearly defined ### Pattern Implementability - [ ] Pattern is implementable by AI agents with provided guidance - [ ] No ambiguous decisions that could be interpreted differently - [ ] Clear boundaries between components - [ ] Explicit integration points with standard patterns --- ## 5. Implementation Patterns ### Pattern Categories Coverage - [ ] **Naming Patterns**: API routes, database tables, components, files - [ ] **Structure Patterns**: Test organization, component organization, shared utilities - [ ] **Format Patterns**: API responses, error formats, date handling - [ ] **Communication Patterns**: Events, state updates, inter-component messaging - [ ] **Lifecycle Patterns**: Loading states, error recovery, retry logic - [ ] **Location Patterns**: URL structure, asset organization, config placement - [ ] **Consistency Patterns**: UI date formats, logging, user-facing errors ### Pattern Quality - [ ] Each pattern has concrete examples - [ ] Conventions are unambiguous (agents can't interpret differently) - [ ] Patterns cover all technologies in the stack - [ ] No gaps where agents would have to guess - [ ] Implementation patterns don't conflict with each other --- ## 6. Technology Compatibility ### Stack Coherence - [ ] Database choice compatible with ORM choice - [ ] Frontend framework compatible with deployment target - [ ] Authentication solution works with chosen frontend/backend - [ ] All API patterns consistent (not mixing REST and GraphQL for same data) - [ ] Starter template compatible with additional choices ### Integration Compatibility - [ ] Third-party services compatible with chosen stack - [ ] Real-time solutions (if any) work with deployment target - [ ] File storage solution integrates with framework - [ ] Background job system compatible with infrastructure --- ## 7. Document Structure ### Required Sections Present - [ ] Executive summary exists (2-3 sentences maximum) - [ ] Project initialization section (if using starter template) - [ ] Decision summary table with ALL required columns: - Category - Decision - Version - Rationale - [ ] Project structure section shows complete source tree - [ ] Implementation patterns section comprehensive - [ ] Novel patterns section (if applicable) ### Document Quality - [ ] Source tree reflects actual technology decisions (not generic) - [ ] Technical language used consistently - [ ] Tables used instead of prose where appropriate - [ ] No unnecessary explanations or justifications - [ ] Focused on WHAT and HOW, not WHY (rationale is brief) --- ## 8. AI Agent Clarity ### Clear Guidance for Agents - [ ] No ambiguous decisions that agents could interpret differently - [ ] Clear boundaries between components/modules - [ ] Explicit file organization patterns - [ ] Defined patterns for common operations (CRUD, auth checks, etc.) - [ ] Novel patterns have clear implementation guidance - [ ] Document provides clear constraints for agents - [ ] No conflicting guidance present ### Implementation Readiness - [ ] Sufficient detail for agents to implement without guessing - [ ] File paths and naming conventions explicit - [ ] Integration points clearly defined - [ ] Error handling patterns specified - [ ] Testing patterns documented --- ## 9. Practical Considerations ### Technology Viability - [ ] Chosen stack has good documentation and community support - [ ] Development environment can be set up with specified versions - [ ] No experimental or alpha technologies for critical path - [ ] Deployment target supports all chosen technologies - [ ] Starter template (if used) is stable and well-maintained ### Scalability - [ ] Architecture can handle expected user load - [ ] Data model supports expected growth - [ ] Caching strategy defined if performance is critical - [ ] Background job processing defined if async work needed - [ ] Novel patterns scalable for production use --- ## 10. Common Issues to Check ### Beginner Protection - [ ] Not overengineered for actual requirements - [ ] Standard patterns used where possible (starter templates leveraged) - [ ] Complex technologies justified by specific needs - [ ] Maintenance complexity appropriate for team size ### Expert Validation - [ ] No obvious anti-patterns present - [ ] Performance bottlenecks addressed - [ ] Security best practices followed - [ ] Future migration paths not blocked - [ ] Novel patterns follow architectural principles --- ## Validation Summary ### Document Quality Score - Architecture Completeness: [Complete / Mostly Complete / Partial / Incomplete] - Version Specificity: [All Verified / Most Verified / Some Missing / Many Missing] - Pattern Clarity: [Crystal Clear / Clear / Somewhat Ambiguous / Ambiguous] - AI Agent Readiness: [Ready / Mostly Ready / Needs Work / Not Ready] ### Critical Issues Found - [ ] Issue 1: **\*\***\_\_\_**\*\*** - [ ] Issue 2: **\*\***\_\_\_**\*\*** - [ ] Issue 3: **\*\***\_\_\_**\*\*** ### Recommended Actions Before Implementation 1. *** 2. *** 3. *** --- **Next Step**: Run the **solutioning-gate-check** workflow to validate alignment between PRD, Architecture, and Stories before beginning implementation. --- _This checklist validates architecture document quality only. Use solutioning-gate-check for comprehensive readiness validation._