chore: import upstream snapshot with attribution
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wehub-resource-sync
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# Orchestration Optimize Command
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Analyze and optimize task orchestrations to improve efficiency, reduce bottlenecks, and maximize team productivity.
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## Usage
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```
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/orchestration/optimize [options]
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```
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## Description
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Performs comprehensive analysis of active and historical orchestrations to identify optimization opportunities, suggest workflow improvements, and provide actionable insights for better task management.
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## Basic Commands
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### Analyze Current Orchestration
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```
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/orchestration/optimize
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```
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Analyzes the most recently active orchestration for bottlenecks and inefficiencies.
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### Optimize Specific Orchestration
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```
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/orchestration/optimize --date 03_15_2024 --project auth_system
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```
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Deep analysis of a specific orchestration with detailed recommendations.
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### Performance Analysis
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```
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/orchestration/optimize --performance
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```
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Focuses on timing, velocity, and resource utilization metrics.
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### Dependency Optimization
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```
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/orchestration/optimize --dependencies
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```
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Analyzes task dependencies for parallelization opportunities.
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## Analysis Areas
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### Bottleneck Detection
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```
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## Identified Bottlenecks
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Critical Path Analysis:
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- TASK-003 (JWT validation): Blocking 4 downstream tasks
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- Duration: 5.5h (150% of estimate)
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- Impact: 12h of parallel work delayed
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Queue Analysis:
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- on_hold queue: 6 tasks (avg 2.3 days waiting)
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- QA queue: 3 tasks (avg 8h waiting)
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- Recommendation: Add QA capacity or parallel testing
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Resource Constraints:
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- dev-backend: 3 active tasks (overloaded)
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- dev-frontend: 0 active tasks (underutilized)
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- Suggestion: Cross-train or reassign suitable tasks
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```
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### Velocity Metrics
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```
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## Velocity Analysis
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Current Metrics:
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- Tasks/day: 2.1 (target: 3.0)
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- Avg task duration: 4.2h (vs 3.5h estimate)
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- Status transitions: todos→in_progress (2h avg wait)
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Historical Comparison:
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- Last week: 2.8 tasks/day (33% faster)
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- Best week: 3.4 tasks/day (optimal conditions)
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Trending Issues:
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- Estimate accuracy declining (65% vs 80% last month)
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- QA feedback loop increased by 40%
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```
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### Dependency Analysis
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```
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## Dependency Optimization
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Parallelization Opportunities:
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1. TASK-007, TASK-008 can run concurrently with TASK-003
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Potential time saving: 6 hours
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2. Frontend tasks independent of current backend work
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Parallelizable: TASK-009, TASK-010, TASK-011
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Critical Path Optimization:
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- Current: 24 hours (sequential)
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- Optimized: 16 hours (parallel execution)
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- Savings: 8 hours (33% improvement)
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Dependency Simplification:
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- Remove false dependency: TASK-012 → TASK-004
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- Merge related tasks: TASK-014 + TASK-015
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```
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## Optimization Strategies
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### Resource Reallocation
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```
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/orchestration/optimize --rebalance
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```
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Suggests optimal task assignments:
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```
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## Recommended Resource Changes
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Current Load:
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┌─────────────────┬────────────┬─────────────┬────────────┐
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│ Agent │ Active │ Queue │ Utilization│
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├─────────────────┼────────────┼─────────────┼────────────┤
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│ dev-backend │ 3 tasks │ 2 tasks │ 180% │
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│ dev-frontend │ 0 tasks │ 4 tasks │ 0% │
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│ qa-engineer │ 2 tasks │ 1 task │ 120% │
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│ test-developer │ 1 task │ 0 tasks │ 60% │
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└─────────────────┴────────────┴─────────────┴────────────┘
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Recommendations:
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1. Move TASK-007 (API tests) to test-developer
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2. Assign TASK-009 (UI components) to dev-frontend
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3. Split TASK-003 into backend/frontend components
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```
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### Task Restructuring
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```
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/orchestration/optimize --restructure
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```
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Suggests task modifications:
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```
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## Task Restructuring Opportunities
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Oversized Tasks (>6h estimate):
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- TASK-003: JWT validation (8h)
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→ Split: JWT core (4h) + JWT middleware (3h) + Tests (1h)
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Undersized Tasks (<1h estimate):
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- TASK-011: Update config (0.5h)
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- TASK-012: Fix typos (0.25h)
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→ Merge into maintenance batch
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Mislabeled Dependencies:
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- TASK-008 doesn't actually need TASK-003
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→ Remove dependency, add to parallel execution
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```
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### Workflow Improvements
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```
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/orchestration/optimize --workflow
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```
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Process optimization suggestions:
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```
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## Workflow Optimization
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Status Transition Delays:
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- todos → in_progress: 4.2h avg (target: <2h)
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- in_progress → qa: 1.2h avg (good)
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- qa → completed: 6.8h avg (target: <4h)
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Recommendations:
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1. Implement auto-assignment rules
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2. Add QA capacity during peak hours
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3. Create task preparation checklist
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Communication Improvements:
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- 23% of blocks due to unclear requirements
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- 15% of QA failures from missing context
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- Add requirement review gate before in_progress
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```
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## Historical Analysis
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### Trend Analysis
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```
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/orchestration/optimize --trends --days 30
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```
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Shows performance trends:
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```
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## 30-Day Performance Trends
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Velocity Trend: ↓ -15%
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- Week 1: 3.2 tasks/day
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- Week 2: 2.9 tasks/day
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- Week 3: 2.8 tasks/day
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- Week 4: 2.7 tasks/day
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Quality Trend: ↓ -8%
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- QA rejection rate increasing
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- Rework time per task up 12%
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Efficiency Indicators:
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- Estimate accuracy: 68% (down from 78%)
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- Parallel execution rate: 45% (up from 40%)
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- Blocked task duration: 1.8 days avg (up from 1.2 days)
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```
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### Pattern Recognition
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```
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## Identified Patterns
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Task Types Performance:
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- Features: 3.2h avg (close to estimates)
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- Bugfixes: 2.1h avg (underestimated by 40%)
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- Tests: 1.8h avg (overestimated by 20%)
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- Security: 5.1h avg (significantly underestimated)
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Time-of-Day Patterns:
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- Morning starts: 25% faster completion
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- Post-lunch blocks: 40% more likely
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- End-of-day QA: 60% higher failure rate
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Agent Specialization:
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- dev-backend: 2x faster on API tasks
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- dev-frontend: 30% faster on UI tasks
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- Cross-functional tasks: 50% slower than specialized
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```
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## Optimization Actions
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### Immediate Actions
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```
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/orchestration/optimize --execute immediate
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```
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Applies safe optimizations:
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1. Rebalance current task assignments
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2. Remove identified false dependencies
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3. Update task estimates based on historical data
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4. Reschedule blocked tasks
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### Structural Changes
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```
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/orchestration/optimize --execute structural --confirm
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```
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Requires confirmation for:
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1. Task splitting/merging
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2. Workflow process changes
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3. Agent role modifications
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4. Dependency restructuring
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### Continuous Optimization
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```
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/orchestration/optimize --schedule daily
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```
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Sets up automated optimization:
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- Daily velocity monitoring
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- Weekly bottleneck analysis
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- Monthly trend reporting
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- Automated rebalancing suggestions
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## Simulation Mode
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### What-If Analysis
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```
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/orchestration/optimize --simulate "add agent:dev-fullstack"
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```
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Projects impact of changes:
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```
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## Simulation Results: Adding dev-fullstack
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Projected Improvements:
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- Velocity: 2.7 → 3.4 tasks/day (+26%)
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- Critical path: 24h → 18h (-25%)
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- Queue time: 4.2h → 2.1h (-50%)
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Resource Utilization:
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- Backend overload: 180% → 120% (optimal)
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- Frontend underload: 0% → 80% (good)
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- Overall efficiency: +35%
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ROI Analysis:
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- Cost: +1 team member
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- Delivery speed: +26%
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- Quality impact: Neutral to positive
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```
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## Integration Features
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### Automated Optimization
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```
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/orchestration/optimize --auto-apply --threshold conservative
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```
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Automatically applies optimizations meeting conservative safety criteria.
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### Notification System
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```
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/orchestration/optimize --alerts bottleneck,velocity,quality
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```
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Sets up alerts for optimization opportunities.
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### Historical Learning
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```
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/orchestration/optimize --learn-from previous_projects/
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```
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Incorporates lessons from past orchestrations.
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## Reporting
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### Optimization Report
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```
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/orchestration/optimize --report detailed
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```
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Generates comprehensive optimization report with:
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- Current state analysis
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- Identified opportunities
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- Recommended actions
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- Expected impact metrics
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- Implementation timeline
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### Executive Summary
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```
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/orchestration/optimize --summary executive
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```
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High-level optimization insights for leadership.
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## Best Practices
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1. **Regular Analysis**: Run optimization weekly on active orchestrations
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2. **Incremental Changes**: Apply optimizations gradually to measure impact
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3. **Monitor Impact**: Track metrics before and after optimization
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4. **Team Communication**: Share optimization insights with the team
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5. **Continuous Learning**: Use historical data to improve future orchestrations
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## Examples
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### Example 1: Daily Optimization Check
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```
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/orchestration/optimize --quick --auto-rebalance
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```
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### Example 2: Deep Analysis for Struggling Project
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```
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/orchestration/optimize --date 03_15_2024 --project auth_system --deep-analysis
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```
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### Example 3: Team Performance Review
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```
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/orchestration/optimize --trends --days 90 --team-focus
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```
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## Configuration
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### Optimization Rules
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Set in orchestration config:
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```yaml
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optimization:
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auto_rebalance: true
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bottleneck_threshold: 2h
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velocity_target: 3.0
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quality_threshold: 85%
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parallel_execution_target: 60%
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```
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## Notes
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- All optimizations are reversible through audit trail
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- Simulation mode allows safe experimentation
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- Historical data improves optimization accuracy over time
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- Integrates with all other orchestration commands
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- Supports custom optimization rules per project type
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