performance-orchestrator

Name: performance-orchestrator
Availability: InStock
Author: SkillPanel

Orchestrate performance optimization workflows via static code analysis and profiling data.

199|26|Updated Nov 27, 2025

Search Tags:#automation #workflow #performance #bottlenecks #static-analysis #code-optimization #maister

Ready to run

npx skills add https://github.com/SkillPanel/maister --skill performance-orchestrator

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: performance-orchestrator
Source: https://github.com/SkillPanel/maister/tree/main/plugins/maister-copilot/skills/performance-orchestrator
Command: npx skills add https://github.com/SkillPanel/maister --skill performance-orchestrator

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Orchestrates end-to-end performance optimization workflows using static code analysis to identify bottlenecks such as N+1 queries, missing indexes, O(n^2) algorithms, blocking I/O, and memory leaks, optionally incorporating user-provided profiling data. It can reuse the standard specification, planning, implementation, and verification phases to structure improvements.

Core Features & Use Cases

Static-analysis-first bottleneck detection across codebases
Phase-driven workflow that covers specification, planning, implementation, and verification
Optional integration of user profiling data and artifact management under .maister/tasks
Flexible orchestration with interactive or automated (YOLO) execution modes

Quick Start

Start a performance optimization workflow with /maister-performance-new describing the bottleneck and goals.

Frequently Asked Questions about performance-orchestrator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I find and fix N+1 queries and O(n^2) algorithm bottlenecks in my codebase?▼

Static code analysis identifies N+1 queries, O(n^2) algorithms, and blocking I/O by scanning your codebase. It orchestrates a structured workflow covering specification, planning, implementation, and verification to systematically resolve detected performance bottlenecks.

Can I incorporate profiling data into an automated code optimization workflow?▼

Yes, you can optionally integrate user-provided profiling data into the performance optimization workflow. The orchestrator combines this data with static analysis to detect memory leaks and missing indexes, then outputs structured results under .maister/tasks for review.

What's the best way to orchestrate end-to-end performance improvements across multiple agents?▼

A phase-driven pipeline coordinates multi-agent analysis and fixes by reusing existing framework patterns. It initializes phase tasks and state, executing specification, planning, implementation, and verification stages to manage artifacts and structure improvements.

Does the performance optimization workflow support automated execution without manual input?▼

Yes, the workflow supports flexible orchestration with interactive or automated YOLO execution modes. You can start an automated performance optimization workflow by providing a task description that outlines the bottleneck and your optimization goals.

When do I need static analysis for detecting memory leaks and blocking I/O?▼

Static analysis is needed when you must proactively detect memory leaks, blocking I/O, and missing database indexes before runtime issues occur. It provides bottleneck detection across codebases without requiring live application traffic or active profiling sessions.