mandate-performance

Assess runtime efficiency and scalability of design approaches by evaluating hot paths, allocations, and threading costs.

2|Updated Mar 17, 2026
One-click install
npx skills add https://github.com/buchananwill/ue-claude-scaffold --skill mandate-performance
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mandate-performance
Source: https://github.com/buchananwill/ue-claude-scaffold/tree/main/skills/mandate-performance
Command: npx skills add https://github.com/buchananwill/ue-claude-scaffold --skill mandate-performance

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Performance evaluation of design choices for runtime efficiency and scalability, enabling teams to identify bottlenecks before shipping.

Core Features & Use Cases

  • Evaluation criteria: hot paths, allocations, cache locality, and tick budgets.
  • Scalability analysis: detect O(n^2) issues, unbounded allocations, redundant iterations.
  • Guidance on implementations: recommends thread-safety strategies, batching, and resource budgeting with measurable targets.

Quick Start

Apply the evaluation framework to a sample workload and report hot paths, budget adherence, and recommended optimizations.

Frequently Asked Questions about mandate-performance

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

FAQPage Schema
How do I evaluate hot paths and tick budgets for real-time system performance?▼

Evaluate hot paths and tick budgets by analyzing per-frame workloads, cache locality, and allocation costs to identify bottlenecks before shipping. The framework assesses runtime efficiency and scalability, recommending lock-free or batching strategies with concrete numbers to maintain latency targets.

What is the best way to detect O(n^2) scalability issues and unbounded allocations in game engine design?▼

Detect O(n^2) scalability issues and unbounded allocations through scalability analysis that reviews redundant iterations and resource budgeting. The evaluation targets runtime efficiency by flagging costly loops and allocation patterns, providing measurable optimization targets for architecture reviews.

How do I analyze threading costs and recommend thread-safety strategies for batch processing workloads?▼

Analyze threading costs and recommend thread-safety strategies by evaluating lock-free approaches and batching for batch processing workloads. The framework measures per-frame impacts and provides concrete examples of resource budgeting to reduce latency in real-time systems.

Does this performance evaluation framework work for game engine design reviews and performance audits?▼

Yes, this performance evaluation framework works for game engine design reviews and performance audits of real-time systems. It evaluates hot paths, assesses tick budgets, and checks cache locality to ensure runtime efficiency and scalability criteria are met before shipping.

Why does runtime performance degrade under per-frame workloads, and how do I profile cache locality?▼

Runtime performance degrades under per-frame workloads due to unbounded allocations, poor cache locality, and redundant iterations. Profile cache locality by applying the evaluation framework to detect O(n^2) issues and measure adherence to tick budgets, recommending batching optimizations.

What limitations exist when evaluating lock-free strategies for real-time architecture performance?▼

Limitations exist when evaluating lock-free strategies because the framework focuses on design-level performance criteria rather than implementation-level profiling. It provides concrete numbers and examples for threading costs, but actual runtime validation requires separate profiling tools to verify batch processing results.