plain-optimize

Analyze observer request traces to identify and fix web performance bottlenecks.

1.0k|27|Updated Mar 22, 2023
One-click install
npx skills add https://github.com/dropseed/plain --skill plain-optimize
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: plain-optimize
Source: https://github.com/dropseed/plain/tree/main/plain-observer/plain/observer/agents/.claude/skills/plain-optimize
Command: npx skills add https://github.com/dropseed/plain --skill plain-optimize

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Performance bottlenecks in modern web apps can degrade user experience, and this skill helps identify and address them by capturing traces and analyzing query patterns.

Core Features & Use Cases

  • Capture traces with observable requests to reveal query counts, duplicates, and bottlenecks.
  • Identify bottlenecks such as N+1 queries, missing indexes, and slow database interactions.
  • Use cases include optimizing pages with slow response times and high query volume.

Quick Start

Analyze and optimize performance by capturing a trace for a target page using the observer workflow and run the optimization steps.

Frequently Asked Questions about plain-optimize

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

FAQPage Schema
How do I identify and fix N+1 query issues in my web application?

To fix N+1 query issues, you need to capture request traces using an observer tool, parse the JSON output for query counts and duplicate spans, and apply targeted optimizations to your database interactions.

What is the best way to debug slow page response times caused by high query volumes?

Debugging slow page response times involves capturing observable request traces to reveal query counts, identifying duplicate queries or missing indexes, and applying performance fixes with a verification step.

How do I capture and parse traces to find performance bottlenecks?

Capture traces by enabling tracing on target requests using the observer request command, then parse the resulting JSON outputs to analyze query_count, duplicate_query_count, and spans for performance bottlenecks.

Can I use observer request tracing to verify if my database optimization fixes worked?

Yes, observer request tracing includes a verification step that allows you to capture a new trace after applying performance fixes to confirm the query count and response times have improved.

Why does my web application have a high duplicate query count in the trace spans?

A high duplicate query count in trace spans typically indicates N+1 query patterns or missing database indexes, which you can identify by analyzing the captured observer request JSON outputs.

Do I need to enable tracing on every request to find missing indexes and slow database interactions?

No, you enable tracing on specific target pages that exhibit slow response times or high query volumes to capture the necessary JSON outputs for analyzing missing indexes and slow database interactions.