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pig-farm-controller/bmad/bmm/workflows/3-solutioning/architecture/checklist.md
2025-11-01 19:22:39 +08:00

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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: **___**




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.