Priority Optimization Assistant
This skill helps optimize projects and tasks by intelligently prioritizing issues, creating actionable checklists, offering flexible execution options, performing optimizations, and generating comprehensive reports.
Capabilities
- •Priority Analysis: Automatically categorizes tasks into high, medium, and low priority based on impact, urgency, effort, and dependencies.
- •Checklist Generation: Creates detailed, actionable optimization checklists with estimated effort and expected benefits.
- •Interactive Selection: Offers users options to execute all optimizations, by priority level, or individual items.
- •Optimization Execution: Simulates or generates code/text optimizations, performs quality checks, and validates improvements.
- •Report Generation: Produces professional reports with before/after comparisons, impact metrics, and next-step recommendations.
Input Requirements
- •Project/Task Description: Text description of the project, code issues, or tasks to optimize.
- •Current State: Optional code snippets, file contents, or JSON list of tasks (e.g., [{"task": "Fix slow query", "details": "..."}]).
- •User Preferences: Optional JSON with preferences like {"focus": "performance", "constraints": "time-limited"}.
- •Format: Natural language or structured JSON.
Output Formats
- •Interactive Menu: Markdown table or numbered list for selection.
- •Execution Results: Generated optimizations (code diffs, refactored snippets), quality assurance logs.
- •Report: Markdown/PDF-ready report with sections: Summary, Checklist, Executions, Metrics, Recommendations.
- •Metrics: Effort saved, impact score, completion status.
How to Use
@priority-optimization-assistant Analyze this codebase for performance optimizations and create a prioritized checklist.
Provide a project description or paste code/files, then select from options like "Execute high priority only".
Scripts
- •
priority_optimization_engine.py: Core engine with PriorityAnalyzer, OptimizationPlanner, OptimizationExecutor, and ReportGenerator classes. Orchestrates the full workflow.
Best Practices
- •Provide detailed project context for accurate prioritization.
- •Use structured task lists for complex projects.
- •Review interactive options before execution.
- •Iterate: Use reports to refine future optimizations.
- •Combine with code-review skills for deeper analysis.
Limitations
- •Prioritization is heuristic-based; domain expertise may override.
- •Executions are generative (code suggestions); manual verification needed for production.
- •Best for software/dev tasks; adapt prompts for other domains.
- •Does not modify files directly—outputs diffs/plans for application.