jeremylongshore

windsurf-performance-profiling

@jeremylongshore/windsurf-performance-profiling
jeremylongshore
1,004
123 forks
Updated 1/18/2026
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Profile and optimize code with AI-assisted analysis. Activate when users mention "performance profiling", "optimize performance", "bottleneck analysis", "profiling", or "performance tuning". Handles performance analysis and optimization. Use when working with windsurf performance profiling functionality. Trigger with phrases like "windsurf performance profiling", "windsurf profiling", "windsurf".

Installation

$skills install @jeremylongshore/windsurf-performance-profiling
Claude Code
Cursor
Copilot
Codex
Antigravity

Details

Pathplugins/saas-packs/skill-databases/windsurf/skills/windsurf-performance-profiling/SKILL.md
Branchmain
Scoped Name@jeremylongshore/windsurf-performance-profiling

Usage

After installing, this skill will be available to your AI coding assistant.

Verify installation:

skills list

Skill Instructions


name: "windsurf-performance-profiling" description: | Profile and optimize code with AI-assisted analysis. Activate when users mention "performance profiling", "optimize performance", "bottleneck analysis", "profiling", or "performance tuning". Handles performance analysis and optimization. Use when working with windsurf performance profiling functionality. Trigger with phrases like "windsurf performance profiling", "windsurf profiling", "windsurf". allowed-tools: "Read,Write,Edit,Bash(cmd:*),Grep" version: 1.0.0 license: MIT author: "Jeremy Longshore jeremy@intentsolutions.io"

Windsurf Performance Profiling

Overview

This skill enables AI-assisted performance profiling within Windsurf. Cascade analyzes profiling data to identify bottlenecks, suggest optimizations, and predict impact of changes. It integrates with language-specific profilers and helps prioritize optimization efforts based on actual performance data rather than assumptions.

Prerequisites

  • Windsurf IDE with Cascade enabled
  • Profiling tools installed (Chrome DevTools, node --prof, py-spy, etc.)
  • Application with performance concerns
  • Baseline metrics established
  • Understanding of performance targets

Instructions

  1. Establish Baseline
  2. Collect Profile Data
  3. Analyze with Cascade
  4. Implement Optimizations
  5. Document and Monitor

See {baseDir}/references/implementation.md for detailed implementation guide.

Output

  • Profiling data and analysis
  • Bottleneck identification reports
  • Optimization recommendations
  • Before/after comparison metrics

Error Handling

See {baseDir}/references/errors.md for comprehensive error handling.

Examples

See {baseDir}/references/examples.md for detailed examples.

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