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performance-reviewer

Detect runtime performance issues in code changes during code review.

Updated Mar 14, 2026
Search Tags:#performance#scalability#bottlenecks#code-review#memory-usage#database-queries#async-i-o
One-click install
npx skills add https://github.com/Andreicr1/netz-analysis-engine --skill performance-reviewer-andreicr1
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: performance-reviewer
Source: https://github.com/Andreicr1/netz-analysis-engine/tree/main/.gemini/skills/performance-reviewer
Command: npx skills add https://github.com/Andreicr1/netz-analysis-engine --skill performance-reviewer-andreicr1

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze code changes to identify and report runtime performance issues, helping teams ship faster and more reliable software.

Core Features & Use Cases

  • Performance hotspot detection: flags inefficient patterns in loops, queries, and I/O paths during code review.
  • Scalability & memory safeguards: highlights potential memory growth, missing pagination, and concurrency hazards as data scales.
  • Use Case: during a pull request that touches data-intensive logic, analyze for N+1 queries and unbounded memory usage to prevent regressions.

Quick Start

Review the latest changes in the diff and report performance hotspots such as N+1 queries, unbounded memory use, and blocking I/O.

Frequently Asked Questions about performance-reviewer

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

FAQPage Schema
How do I detect N+1 queries and unbounded memory growth during a code review?▼

Detect N+1 queries and unbounded memory growth during code review by analyzing pull request diffs to flag inefficient database access patterns and potential memory accumulation as data scales. It exposes these runtime performance hotspots before production deployment.

What is blocking I/O in async contexts and how can I identify it in my code changes?▼

Blocking I/O in async contexts occurs when synchronous operations stall concurrent execution. Identify it by analyzing code changes to expose operations that block asynchronous paths, formatting findings with confidence calibration to prevent runtime performance regressions.

How do I check code changes for missing pagination and hot-path allocations?▼

Check code changes for missing pagination and hot-path allocations by applying performance analysis to pull requests across backend services and data-heavy transformations. It identifies these scalability safeguards and reports bottlenecks within the modified diff.

Can I use this to analyze performance issues in data-heavy transformations and I/O-bound paths?▼

You can analyze runtime performance in data-heavy transformations and I/O-bound paths by applying the review process to code changes across backend services. It identifies bottlenecks and highlights concurrency hazards as data scales.

What is the best way to find scalability and memory usage bottlenecks in a pull request?▼

The best way to find scalability and memory usage bottlenecks in a pull request is to analyze the latest changes in the diff. This process highlights potential memory growth, missing pagination, and inefficient patterns in loops and queries.

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