npx skills add https://github.com/adaptationio/skrillz --skill process-optimizerSKILL.md
Process Optimizer
Overview
process-optimizer improves skill development processes by identifying and eliminating inefficiencies, bottlenecks, and waste.
Purpose: Make skill development processes faster and more efficient
The 4 Optimization Operations:
- Identify Bottlenecks - Find process slowdowns and constraints
- Discover Automation - Identify automation opportunities
- Streamline Workflows - Simplify and optimize workflows
- Implement Improvements - Apply process optimizations
Integration: Uses findings from system-reviewer Operation 3 (Process Efficiency Review)
When to Use
- Development processes feel slow or inefficient
- After system-reviewer identifies process issues
- When looking to reduce cycle times
- Before scaling to many skills (optimize early)
- Continuous process improvement
Operations
Operation 1: Identify Bottlenecks
Purpose: Find steps that slow down development
Process:
- Map current process (what are the steps?)
- Measure duration (how long each step?)
- Identify slowest steps (bottlenecks)
- Analyze causes (why is it slow?)
- Prioritize by impact (which to fix first?)
Output: Bottleneck analysis with prioritized fixes
Time: 45-90 minutes
Operation 2: Discover Automation
Purpose: Identify manual work that could be automated
Process:
- List manual steps in process
- Identify repetitive/mechanical work
- Assess automation feasibility (easy/hard/impossible?)
- Estimate ROI (time to automate vs time saved)
- Prioritize automation opportunities
Output: Automation opportunities prioritized by ROI
Time: 45-90 minutes
Operation 3: Streamline Workflows
Purpose: Simplify processes, eliminate unnecessary steps
Process:
- Review each workflow step (is it necessary?)
- Identify redundant work (done twice?)
- Find unnecessary complexity (simpler approach?)
- Combine or eliminate steps
- Design streamlined workflow
Output: Streamlined process with steps eliminated/combined
Time: 60-120 minutes
Operation 4: Implement Improvements
Purpose: Apply process optimizations discovered
Process:
- Select high-priority improvement
- Design implementation (how to apply?)
- Implement (update workflows, tools, guidelines)
- Test (does it actually help?)
- Measure impact (time saved, efficiency gained)
Output: Implemented improvement with measured impact
Time: 1-4 hours (varies by improvement)
Example Process Optimizations
Optimization 1: Automated structure validation
- Before: Manual YAML checking, 30-45 min
- After: validate-structure.py script, 5-10 min automated
- Impact: 75% time reduction, 95% accuracy improvement
Optimization 2: development-workflow
- Before: Ad-hoc skill building, 17-29 hours/skill
- After: Systematic workflow, 12-18 hours/skill
- Impact: 35-40% time reduction, higher quality
Optimization 3: Fast-track approach for simple skills
- Before: Full workflow even for simple skills
- After: Skip task-development, use prompt-first approach
- Impact: 10-15% additional time savings on simple skills
Quick Reference
| Operation | Focus | Time | Output |
|---|---|---|---|
| Identify Bottlenecks | Find slowdowns | 45-90m | Bottleneck analysis |
| Discover Automation | Find automation opportunities | 45-90m | Automation prioritization |
| Streamline Workflows | Simplify processes | 60-120m | Streamlined workflows |
| Implement Improvements | Apply optimizations | 1-4h | Measured improvements |
Integration: system-reviewer (identifies issues) → process-optimizer (fixes them)
process-optimizer makes skill development faster and more efficient through systematic process improvement.