system-reviewer
System Reviewer
Overview
system-reviewer performs meta-level reviews of the skill development ecosystem itself, assessing the health and effectiveness of the entire system rather than individual skills.
Purpose: Meta-level ecosystem assessment and system optimization
The 5 System Review Operations:
- Ecosystem Health Check - Assess overall ecosystem quality and completeness
- Toolkit Effectiveness Review - Evaluate how well the toolkit works
- Process Efficiency Review - Review development processes for optimization
- Coverage Gap Analysis - Identify missing capabilities or skills
- System Optimization Recommendations - Recommend system-level improvements
Key Distinction: Reviews the SYSTEM, not individual skills
When to Use
- Periodic ecosystem health checks (monthly/quarterly)
- After completing major layers (Layer 2, 3, 4, 5)
- When suspecting systemic issues (not individual skill problems)
- Planning next ecosystem developments
- Optimizing the development system itself
Operations
Operation 1: Ecosystem Health Check
Purpose: Assess overall ecosystem quality, completeness, and consistency
Process:
-
Count and Categorize Skills
- Total skills built
- Skills per layer
- Pattern distribution (workflow/task/reference)
- Completion percentage
-
Assess Structural Quality
- Run review-multi validation on all skills
- Calculate average quality scores
- Identify outliers (very high/low quality)
- Check consistency across ecosystem
-
Evaluate Completeness
- Are all planned layers complete?
- Are there gaps in capabilities?
- Is toolkit comprehensive?
- Missing critical functionality?
-
Check Integration
- Do skills work together well?
- Are there integration issues?
- Workflow compositions effective?
- Dependencies clear and working?
-
Generate Health Report
- Overall health score (healthy/good/needs attention/critical)
- Strengths (what's working well)
- Weaknesses (what needs improvement)
- Trends (improving/stable/degrading)
Outputs:
- Ecosystem health score
- Skill inventory and metrics
- Quality assessment aggregate
- Completeness analysis
- Integration assessment
- Health report with recommendations
Time Estimate: 1-2 hours
Example:
Ecosystem Health Check: 2025-11-07
====================================
Skill Inventory:
- Total Skills: 23
- Layer 2: 10/10 (100%)
- Layer 3: 7/7 (100%)
- Layer 4: 6/6 (100%)
- Layer 5: 0/5 (0%)
Quality Assessment:
- Average Structure Score: 5.0/5.0 (all 23 skills Grade A)
- Quality Range: 5/5 (no variation - excellent consistency)
- Quick Reference Coverage: 100% (all 23 skills)
- Anti-Patterns: 10 total identified, 3 fixed
Completeness:
✅ Research capability: Complete (skill-researcher + research-workflow)
✅ Planning capability: Complete (planning-architect + task-development + planning-workflow)
✅ Execution capability: Complete (todo-management + momentum-keeper)
✅ Quality capability: Complete (review-multi + skill-validator + skill-tester + review-workflow)
✅ Improvement capability: Complete (skill-reviewer + skill-updater + improvement-workflow)
⬜ Self-improvement: 0% (Layer 5 not built)
⬜ Comprehensive testing: Partial (skill-tester exists, testing-validator missing)
Integration Assessment:
✅ Skills compose well (development-workflow, review-workflow, improvement-workflow working)
✅ Dependencies clear (YAML + documentation)
✅ Workflows effective (proven through usage)
Ecosystem Health: ✅ HEALTHY
Strengths:
- 100% structural excellence
- Complete Layers 2-4
- Validated continuous improvement cycle
- 85% efficiency gain proven
Weaknesses:
- Layer 5 incomplete (missing self-improvement automation)
- testing-validator missing (validation incomplete without it)
- Some minor anti-patterns in 4 skills (vague validation criteria)
Trends:
✅ Improving: Efficiency compounding, quality consistent, standards evolving
✅ Stable: Structural quality (all 5/5)
Recommendations:
1. [High] Complete Layer 5 for full self-improvement capability
2. [Medium] Build testing-validator for complete validation suite
3. [Low] Refine vague validation criteria in 4 skills
Operation 2: Toolkit Effectiveness Review
Purpose: Evaluate how well the development toolkit enables skill building
Process:
-
Measure Efficiency Gains
- Build time progression (skills 1-23)
- Efficiency vs baseline
- Time saved calculation
- Trend analysis (improving/plateauing?)
-
Assess Tool Utilization
- Which tools used most? (high value)
- Which tools rarely used? (low value or unknown)
- Which tools most effective? (biggest impact)
- Are there gaps? (missing tools)
-
Evaluate Workflow Effectiveness
- Is development-workflow actually used?
- Does it save time as promised?
- Are workflows followed or bypassed?
- Improvements to workflows needed?
-
Check Tool Quality
- Are tools themselves high quality?
- Do they achieve stated purposes?
- User satisfaction with tools?
- Tools needing improvement?
-
Generate Toolkit Assessment
- Most valuable tools
- Least utilized tools
- Effectiveness metrics
- Improvement opportunities
Outputs:
- Toolkit effectiveness assessment
- Tool utilization metrics
- High-value vs low-value tools identified
- Toolkit improvement recommendations
Time Estimate: 1-1.5 hours
Operation 3: Process Efficiency Review
Purpose: Review development processes for optimization opportunities
Process:
-
Document Current Processes
- How are skills currently built?
- What's the typical workflow?
- What steps are always followed?
- What steps are sometimes skipped?
-
Measure Process Metrics
- Average build time per skill complexity
- Rework rate (how often redo work?)
- Blocker frequency (how often stuck?)
- Completion rate (how many finished?)
-
Identify Bottlenecks
- Longest steps in process
- Most frequent blockers
- Highest rework areas
- Inefficient patterns
-
Assess Automation
- What's automated? (scripts, workflows)
- What's manual? (still required human input)
- Automation opportunities? (could be automated)
- Automation effectiveness? (actually saves time?)
-
Generate Process Recommendations
- Process simplifications
- Automation opportunities
- Bottleneck elimination
- Efficiency improvements
Outputs:
- Process efficiency assessment
- Bottleneck analysis
- Automation opportunities
- Process optimization recommendations
Time Estimate: 1-2 hours
Operation 4: Coverage Gap Analysis
Purpose: Identify missing capabilities, skills, or functionality in ecosystem
Process:
-
Review Original Plan
- What was planned? (39 skills originally)
- What's built? (23 skills currently)
- What's missing? (16 skills remaining)
-
Assess Current Capabilities
- Research: Complete ✅
- Planning: Complete ✅
- Execution: Complete ✅
- Quality: Mostly complete (missing testing-validator)
- Improvement: Complete ✅
- Automation: Partial (Layer 5 missing)
-
Identify Critical Gaps
- Must-have missing capabilities
- High-value skills not built
- Ecosystem limitations without them
-
Prioritize Remaining Work
- Critical (must build)
- High value (should build)
- Nice to have (optional)
- Low priority (defer)
-
Generate Coverage Report
- Gap analysis (what's missing)
- Impact assessment (what's the cost of gap)
- Prioritized build recommendations
Outputs:
- Coverage gap analysis
- Missing capabilities identified
- Prioritized skill build recommendations
Time Estimate: 45-90 minutes
Operation 5: System Optimization Recommendations
Purpose: Recommend system-level improvements (not individual skill improvements)
Process:
-
Aggregate Findings
- From Operations 1-4
- From analysis of all skills
- From usage patterns
- From feedback
-
Identify System-Level Issues
- Structural issues (ecosystem organization)
- Process issues (development workflow problems)
- Tool issues (toolkit gaps or inefficiencies)
- Integration issues (skills not composing well)
-
Generate Recommendations
- System reorganization needs
- Process improvements
- Toolkit enhancements
- Integration optimizations
-
Prioritize by Impact
- Critical (affects ecosystem viability)
- High (significantly improves system)
- Medium (moderate improvement)
- Low (nice to have)
-
Create Action Plan
- What to build next
- What to improve
- What to refactor
- What to deprecate (if anything)
Outputs:
- System optimization recommendations
- Prioritized action plan
- Impact assessments
- Next development priorities
Time Estimate: 1-2 hours
Best Practices
1. Regular Health Checks
Practice: Run ecosystem health check monthly or after major milestones
Rationale: Early detection of systemic issues prevents compounding
2. Data-Driven Assessment
Practice: Use metrics and evidence, not opinion
Rationale: Objective assessment enables better decisions
3. System-Level Focus
Practice: Focus on ecosystem patterns, not individual skill issues
Rationale: system-reviewer is for systemic issues, review-multi for individual skills
4. Act on Findings
Practice: Use recommendations to guide next development priorities
Rationale: Reviews without action don't improve anything
Quick Reference
The 5 System Review Operations
| Operation | Focus | Time | Output |
|---|---|---|---|
| Ecosystem Health | Overall quality, completeness | 1-2h | Health score, strengths/weaknesses |
| Toolkit Effectiveness | Tool utilization, efficiency | 1-1.5h | Tool assessment, utilization metrics |
| Process Efficiency | Development process optimization | 1-2h | Bottlenecks, automation opportunities |
| Coverage Gaps | Missing capabilities | 45-90m | Gap analysis, prioritized builds |
| System Optimization | System-level improvements | 1-2h | Recommendations, action plan |
Total Time: 5-8 hours for complete system review
System vs Individual Skill Reviews
system-reviewer (this skill):
- Reviews the ECOSYSTEM
- Systemic issues and patterns
- System-level optimization
- Meta-level assessment
review-multi:
- Reviews INDIVIDUAL SKILLS
- Skill-specific issues
- Individual skill improvements
- Skill-level assessment
Use Both: system-reviewer for ecosystem health, review-multi for individual quality
Integration with Continuous Improvement
system-reviewer → Identify systemic issues
↓
process-optimizer → Optimize processes
↓
feedback-analyzer → Analyze effectiveness
↓
auto-updater → Apply system improvements
↓
evolution-reporter → Report progress
↓
Improved ecosystem → Better skills
system-reviewer enables meta-level ecosystem assessment and system optimization for continuous ecosystem improvement.