majiayu000 Unified Review Orchestration
Intelligently selects and executes appropriate review skills based on codebase analysis and context.
Quick Start
# Auto-detect and run appropriate reviews
/full-review
# Focus on specific areas
/full-review api # API surface review
/full-review architecture # Architecture review
/full-review bugs # Bug hunting
/full-review tests # Test suite review
/full-review all # Run all applicable skills
When to Use
- Starting a full code review
- Reviewing changes across multiple domains
- Need intelligent selection of review skills
- Want integrated reporting from multiple review types
- Before merging major feature branches
Review Skill Selection Matrix
| Codebase Pattern | Review Skills | Triggers |
|---|---|---|
Rust files (*.rs, Cargo.toml) |
rust-review, bug-review, api-review | Rust project detected |
API changes (openapi.yaml, routes/) |
api-review, architecture-review | Public API surfaces |
Test files (test_*.py, *_test.go) |
test-review, bug-review | Test infrastructure |
| Makefile/build system | makefile-review, architecture-review | Build complexity |
| Mathematical algorithms | math-review, bug-review | Numerical computation |
| Architecture docs/ADRs | architecture-review, api-review | System design |
| General code quality | bug-review, test-review | Default review |
Workflow
1. Analyze Repository Context
- Detect primary languages from extensions and manifests
- Analyze git status and diffs for change scope
- Identify project structure (monorepo, microservices, library)
- Detect build systems, testing frameworks, documentation
2. Select Review Skills
# Detection logic
if has_rust_files():
schedule_skill("rust-review")
if has_api_changes():
schedule_skill("api-review")
if has_test_files():
schedule_skill("test-review")
if has_makefiles():
schedule_skill("makefile-review")
if has_math_code():
schedule_skill("math-review")
if has_architecture_changes():
schedule_skill("architecture-review")
# Default
schedule_skill("bug-review")
3. Execute Reviews
- Run selected skills concurrently
- Share context between reviews
- Maintain consistent evidence logging
- Track progress via TodoWrite
4. Integrate Findings
- Consolidate findings across domains
- Identify cross-domain patterns
- Prioritize by impact and effort
- Generate unified action plan
Review Modes
Auto-Detect (default)
Automatically selects skills based on codebase analysis.
Focused Mode
Run specific review domains:
/full-review api→ api-review only/full-review architecture→ architecture-review only/full-review bugs→ bug-review only/full-review tests→ test-review only
Full Review Mode
Run all applicable review skills:
/full-review all→ Execute all detected skills
Quality Gates
Each review must:
- Establish proper context
- Execute all selected skills successfully
- Document findings with evidence
- Prioritize recommendations by impact
- Create action plan with owners
Deliverables
Executive Summary
- Overall codebase health assessment
- Critical issues requiring immediate attention
- Review frequency recommendations
Domain-Specific Reports
- API surface analysis and consistency
- Architecture alignment with ADRs
- Test coverage gaps and improvements
- Bug analysis and security findings
- Performance and maintainability recommendations
Integrated Action Plan
- Prioritized remediation tasks
- Cross-domain dependencies
- Assigned owners and target dates
- Follow-up review schedule
Modular Architecture
All review skills use a hub-and-spoke architecture with progressive loading:
pensive:shared: Common workflow, output templates, quality checklists- Each skill has
modules/: Domain-specific details loaded on demand - Cross-plugin deps:
imbue:evidence-logging,imbue:diff-analysis/modules/risk-assessment-framework
This reduces token usage by 50-70% for focused reviews while maintaining full capabilities.
Exit Criteria
- All selected review skills executed
- Findings consolidated and prioritized
- Action plan created with ownership
- Evidence logged per
pensive:shared/modules/output-format-templates