Checklists

requirements.md

Specification Quality Checklist: Workspace-per-Work-Package for Parallel Development

Purpose: Validate specification completeness and quality before proceeding to planning Created: 2026-01-07 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

Validation Results

Content Quality ✅

No implementation details: PASS - Specification describes workspace creation, dependency handling, and merge behavior without mentioning specific Python modules, classes, or data structures.

User value focus: PASS - Executive summary and user stories clearly articulate the problem (sequential development bottleneck) and solution (parallel multi-agent work).

Stakeholder language: PASS - Written for users and project managers (agents, worktrees, dependencies) rather than developers (git_ops.py, subprocess calls, pathlib).

Mandatory sections: PASS - All required sections present: User Scenarios (6 stories), Requirements (25 FRs), Success Criteria (10 measurable outcomes), Edge Cases (11 scenarios).

Requirement Completeness ✅

No clarifications pending: PASS - "Open Questions" section explicitly states all decisions resolved during discovery. No [NEEDS CLARIFICATION] markers in spec.

Testable requirements: PASS - All 25 functional requirements use concrete verbs (MUST create, MUST validate, MUST commit) with specific validation criteria.

Measurable success criteria: PASS - All 10 success criteria include quantifiable validation (100% error rate, git log verification, 1/3 time reduction, etc.).

Technology-agnostic success criteria: PASS - Success criteria focus on user outcomes (parallel work, dependency correctness, backward compatibility) without mentioning implementation specifics.

Acceptance scenarios defined: PASS - 6 user stories with 22 total acceptance scenarios covering primary flows (parallel work, dependencies, planning workflow) and edge cases (review feedback, legacy compatibility).

Edge cases identified: PASS - 11 edge case scenarios across 4 categories (workspace creation failures, dependency validation, planning artifact workflow, legacy/new model detection) with explicit resolutions.

Scope boundaries: PASS - Clear in-scope/out-of-scope sections. Notable out-of-scope: incremental WP merging, dashboard implementation, automatic rebase, dependency visualization.

Dependencies listed: PASS - 3 external dependencies (Git CLI 2.5.0+, Python 3.11+, existing Git repo) and 5 key assumptions (main branch target, worktree support, filesystem isolation, DAG dependencies, external agent coordination).

Feature Readiness ✅

Requirements with acceptance criteria: PASS - Each of 25 functional requirements maps directly to acceptance scenarios in user stories 1-6. Example: FR-007 (--base flag) validated by User Story 2, Scenario 2.

Primary flows covered: PASS - User stories prioritized correctly: P1 (parallel development, dependency handling, planning workflow, WP prompts), P2 (backward compatibility), P3 (review warnings).

Measurable outcomes aligned: PASS - Success criteria directly validate user story scenarios. SC-001 (parallel work) validates User Story 1, SC-003 (correct branching) validates User Story 2.

No implementation leakage: PASS - Spec avoids Python code, function names, module structure, or specific library references.

Notes

Strengths:

1. Clear problem statement: Executive summary articulates current bottleneck (one worktree per feature) and solution (workspace-per-WP for parallel work).

2. Comprehensive dependency handling: User Story 2 and FR-007/FR-008 fully specify --base flag behavior, validation, and error handling.

3. Backward compatibility designed upfront: User Story 5 and FR-022 through FR-025 ensure legacy worktrees (features 001-008) continue working.

4. Dashboard compatibility considered: SC-008 and edge cases acknowledge dashboard must handle both models, setting up future dashboard feature.

5. Review feedback warnings: User Story 6 addresses git limitation (manual rebase required) with explicit warnings in prompts, setting expectations correctly.

6. Self-documenting WP prompts: FR-010/FR-011 specify WP prompt files contain correct implementation commands, reducing user error.

Design Decisions Validated:

  • ✅ Planning artifacts in main (FR-001 through FR-003) - enables all WPs to branch from common base
  • ✅ On-demand workspace creation (FR-004) - only creates workspaces actually needed
  • ✅ --base flag for explicit dependencies (FR-007) - prevents accidental wrong branching
  • ✅ Keep existing merge behavior (FR-019) - incremental merging deferred to future version
  • ✅ Non-retroactive (FR-025) - legacy worktrees frozen, no forced migration

Risk Mitigation:

  • High risk: Breaking change to planning workflow - Mitigation: Clear docs, updated prompts
  • High risk: Dependency detection accuracy - Mitigation: Conservative parsing, validation
  • Medium risk: Review feedback rebase complexity - Mitigation: Prominent warnings
  • Medium risk: Dashboard compatibility - Mitigation: Explicit detection logic

Ready for Next Phase: ✅ This specification is complete, unambiguous, and ready for /spec-kitty.plan (design/architecture phase).

Recommendation: Proceed to planning phase to design:

  • Worktree creation logic (when to create, validation, error handling)
  • Dependency parsing from tasks.md (detection algorithm, circular dependency checks)
  • Planning workflow changes (commit to main, no initial worktree)
  • Backward compatibility detection (legacy vs new model)
  • Warning system for review feedback (when to display, what commands to suggest)